":
+ return x.values
+ elif not x:
+ raise ValueError("Cannot transform to numpy.matrix.")
+ else:
+ return to_ndarray(array(x))
diff --git a/baselines/doc.py b/baselines/doc.py
index 9b59883..3a78845 100644
--- a/baselines/doc.py
+++ b/baselines/doc.py
@@ -1,4 +1,4 @@
-import numpy as np
-
-def get_doc(probs1, probs2):
+import numpy as np
+
+def get_doc(probs1, probs2):
return np.mean(probs2) - np.mean(probs1)
\ No newline at end of file
diff --git a/baselines/impweight.py b/baselines/impweight.py
index f144bce..198b3be 100644
--- a/baselines/impweight.py
+++ b/baselines/impweight.py
@@ -1,66 +1,66 @@
-import numpy as np
-from scipy.sparse import issparse, vstack
-from sklearn.linear_model import LogisticRegression
-from sklearn.model_selection import GridSearchCV
-from sklearn.neighbors import KernelDensity
-
-from baselines import densratio
-from baselines.pykliep import DensityRatioEstimator
-
-
-def kliep(Xtr, ytr, Xte):
- kliep = DensityRatioEstimator()
- kliep.fit(Xtr, Xte)
- return kliep.predict(Xtr)
-
-
-def usilf(Xtr, ytr, Xte, alpha=0.0):
- dense_ratio_obj = densratio(Xtr, Xte, alpha=alpha, verbose=False)
- return dense_ratio_obj.compute_density_ratio(Xtr)
-
-
-def logreg(Xtr, ytr, Xte):
- # check "Direct Density Ratio Estimation for
- # Large-scale Covariate Shift Adaptation", Eq.28
-
- if issparse(Xtr):
- X = vstack([Xtr, Xte])
- else:
- X = np.concatenate([Xtr, Xte])
-
- y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
-
- logreg = GridSearchCV(
- LogisticRegression(),
- param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
- n_jobs=-1,
- )
- logreg.fit(X, y)
- probs = logreg.predict_proba(Xtr)
- prob_train, prob_test = probs[:, 0], probs[:, 1]
- prior_train = Xtr.shape[0]
- prior_test = Xte.shape[0]
- w = (prior_train / prior_test) * (prob_test / prob_train)
- return w
-
-
-kdex2_params = {"bandwidth": np.logspace(-1, 1, 20)}
-
-
-def kdex2_lltr(Xtr):
- if issparse(Xtr):
- Xtr = Xtr.toarray()
- return GridSearchCV(KernelDensity(), kdex2_params).fit(Xtr).score_samples(Xtr)
-
-
-def kdex2_weights(Xtr, Xte, log_likelihood_tr):
- log_likelihood_te = (
- GridSearchCV(KernelDensity(), kdex2_params).fit(Xte).score_samples(Xtr)
- )
- likelihood_tr = np.exp(log_likelihood_tr)
- likelihood_te = np.exp(log_likelihood_te)
- return likelihood_te / likelihood_tr
-
-
-def get_acc(tr_preds, ytr, w):
- return np.sum((1.0 * (tr_preds == ytr)) * w) / np.sum(w)
+import numpy as np
+from scipy.sparse import issparse, vstack
+from sklearn.linear_model import LogisticRegression
+from sklearn.model_selection import GridSearchCV
+from sklearn.neighbors import KernelDensity
+
+from baselines import densratio
+from baselines.pykliep import DensityRatioEstimator
+
+
+def kliep(Xtr, ytr, Xte):
+ kliep = DensityRatioEstimator()
+ kliep.fit(Xtr, Xte)
+ return kliep.predict(Xtr)
+
+
+def usilf(Xtr, ytr, Xte, alpha=0.0):
+ dense_ratio_obj = densratio(Xtr, Xte, alpha=alpha, verbose=False)
+ return dense_ratio_obj.compute_density_ratio(Xtr)
+
+
+def logreg(Xtr, ytr, Xte):
+ # check "Direct Density Ratio Estimation for
+ # Large-scale Covariate Shift Adaptation", Eq.28
+
+ if issparse(Xtr):
+ X = vstack([Xtr, Xte])
+ else:
+ X = np.concatenate([Xtr, Xte])
+
+ y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
+
+ logreg = GridSearchCV(
+ LogisticRegression(),
+ param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
+ n_jobs=-1,
+ )
+ logreg.fit(X, y)
+ probs = logreg.predict_proba(Xtr)
+ prob_train, prob_test = probs[:, 0], probs[:, 1]
+ prior_train = Xtr.shape[0]
+ prior_test = Xte.shape[0]
+ w = (prior_train / prior_test) * (prob_test / prob_train)
+ return w
+
+
+kdex2_params = {"bandwidth": np.logspace(-1, 1, 20)}
+
+
+def kdex2_lltr(Xtr):
+ if issparse(Xtr):
+ Xtr = Xtr.toarray()
+ return GridSearchCV(KernelDensity(), kdex2_params).fit(Xtr).score_samples(Xtr)
+
+
+def kdex2_weights(Xtr, Xte, log_likelihood_tr):
+ log_likelihood_te = (
+ GridSearchCV(KernelDensity(), kdex2_params).fit(Xte).score_samples(Xtr)
+ )
+ likelihood_tr = np.exp(log_likelihood_tr)
+ likelihood_te = np.exp(log_likelihood_te)
+ return likelihood_te / likelihood_tr
+
+
+def get_acc(tr_preds, ytr, w):
+ return np.sum((1.0 * (tr_preds == ytr)) * w) / np.sum(w)
diff --git a/baselines/models.py b/baselines/models.py
index a0e8c35..6635f2b 100644
--- a/baselines/models.py
+++ b/baselines/models.py
@@ -1,140 +1,140 @@
-# import itertools
-# from typing import Iterable
-
-# import quapy as qp
-# import quapy.functional as F
-# from densratio import densratio
-# from quapy.method.aggregative import *
-# from quapy.protocol import (
-# AbstractStochasticSeededProtocol,
-# OnLabelledCollectionProtocol,
-# )
-# from scipy.sparse import issparse, vstack
-# from scipy.spatial.distance import cdist
-# from scipy.stats import multivariate_normal
-# from sklearn.linear_model import LogisticRegression
-# from sklearn.model_selection import GridSearchCV
-# from sklearn.neighbors import KernelDensity
-
-import time
-
-import numpy as np
-import sklearn.metrics as metrics
-from pykliep import DensityRatioEstimator
-from quapy.protocol import APP
-from scipy.sparse import issparse, vstack
-from sklearn.linear_model import LogisticRegression
-from sklearn.model_selection import GridSearchCV
-from sklearn.neighbors import KernelDensity
-
-import baselines.impweight as iw
-from baselines.densratio import densratio
-from quacc.dataset import Dataset
-
-
-# ---------------------------------------------------------------------------------------
-# Methods of "importance weight", e.g., by ratio density estimation (KLIEP, SILF, LogReg)
-# ---------------------------------------------------------------------------------------
-class ImportanceWeight:
- def weights(self, Xtr, ytr, Xte):
- ...
-
-
-class KLIEP(ImportanceWeight):
- def __init__(self):
- pass
-
- def weights(self, Xtr, ytr, Xte):
- kliep = DensityRatioEstimator()
- kliep.fit(Xtr, Xte)
- return kliep.predict(Xtr)
-
-
-class USILF(ImportanceWeight):
- def __init__(self, alpha=0.0):
- self.alpha = alpha
-
- def weights(self, Xtr, ytr, Xte):
- dense_ratio_obj = densratio(Xtr, Xte, alpha=self.alpha, verbose=False)
- return dense_ratio_obj.compute_density_ratio(Xtr)
-
-
-class LogReg(ImportanceWeight):
- def __init__(self):
- pass
-
- def weights(self, Xtr, ytr, Xte):
- # check "Direct Density Ratio Estimation for
- # Large-scale Covariate Shift Adaptation", Eq.28
-
- if issparse(Xtr):
- X = vstack([Xtr, Xte])
- else:
- X = np.concatenate([Xtr, Xte])
-
- y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
-
- logreg = GridSearchCV(
- LogisticRegression(),
- param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
- n_jobs=-1,
- )
- logreg.fit(X, y)
- probs = logreg.predict_proba(Xtr)
- prob_train, prob_test = probs[:, 0], probs[:, 1]
- prior_train = Xtr.shape[0]
- prior_test = Xte.shape[0]
- w = (prior_train / prior_test) * (prob_test / prob_train)
- return w
-
-
-class KDEx2(ImportanceWeight):
- def __init__(self):
- pass
-
- def weights(self, Xtr, ytr, Xte):
- params = {"bandwidth": np.logspace(-1, 1, 20)}
- log_likelihood_tr = (
- GridSearchCV(KernelDensity(), params).fit(Xtr).score_samples(Xtr)
- )
- log_likelihood_te = (
- GridSearchCV(KernelDensity(), params).fit(Xte).score_samples(Xtr)
- )
- likelihood_tr = np.exp(log_likelihood_tr)
- likelihood_te = np.exp(log_likelihood_te)
- return likelihood_te / likelihood_tr
-
-
-if __name__ == "__main__":
- # d = Dataset("rcv1", target="CCAT").get_raw()
- d = Dataset("imdb", n_prevalences=1).get()[0]
-
- tstart = time.time()
- lr = LogisticRegression()
- lr.fit(*d.train.Xy)
- val_preds = lr.predict(d.validation.X)
- protocol = APP(
- d.test,
- n_prevalences=21,
- repeats=1,
- sample_size=100,
- return_type="labelled_collection",
- )
-
- results = []
- for sample in protocol():
- wx = iw.kliep(d.validation.X, d.validation.y, sample.X)
- test_preds = lr.predict(sample.X)
- estim_acc = np.sum((1.0 * (val_preds == d.validation.y)) * wx) / np.sum(wx)
- true_acc = metrics.accuracy_score(sample.y, test_preds)
- results.append((sample.prevalence(), estim_acc, true_acc))
-
- tend = time.time()
-
- for r in results:
- print(*r)
-
- print(f"logreg finished [took {tend-tstart:.3f}s]")
- import win11toast
-
- win11toast.notify("models.py", "Completed")
+# import itertools
+# from typing import Iterable
+
+# import quapy as qp
+# import quapy.functional as F
+# from densratio import densratio
+# from quapy.method.aggregative import *
+# from quapy.protocol import (
+# AbstractStochasticSeededProtocol,
+# OnLabelledCollectionProtocol,
+# )
+# from scipy.sparse import issparse, vstack
+# from scipy.spatial.distance import cdist
+# from scipy.stats import multivariate_normal
+# from sklearn.linear_model import LogisticRegression
+# from sklearn.model_selection import GridSearchCV
+# from sklearn.neighbors import KernelDensity
+
+import time
+
+import numpy as np
+import sklearn.metrics as metrics
+from pykliep import DensityRatioEstimator
+from quapy.protocol import APP
+from scipy.sparse import issparse, vstack
+from sklearn.linear_model import LogisticRegression
+from sklearn.model_selection import GridSearchCV
+from sklearn.neighbors import KernelDensity
+
+import baselines.impweight as iw
+from baselines.densratio import densratio
+from quacc.dataset import Dataset
+
+
+# ---------------------------------------------------------------------------------------
+# Methods of "importance weight", e.g., by ratio density estimation (KLIEP, SILF, LogReg)
+# ---------------------------------------------------------------------------------------
+class ImportanceWeight:
+ def weights(self, Xtr, ytr, Xte):
+ ...
+
+
+class KLIEP(ImportanceWeight):
+ def __init__(self):
+ pass
+
+ def weights(self, Xtr, ytr, Xte):
+ kliep = DensityRatioEstimator()
+ kliep.fit(Xtr, Xte)
+ return kliep.predict(Xtr)
+
+
+class USILF(ImportanceWeight):
+ def __init__(self, alpha=0.0):
+ self.alpha = alpha
+
+ def weights(self, Xtr, ytr, Xte):
+ dense_ratio_obj = densratio(Xtr, Xte, alpha=self.alpha, verbose=False)
+ return dense_ratio_obj.compute_density_ratio(Xtr)
+
+
+class LogReg(ImportanceWeight):
+ def __init__(self):
+ pass
+
+ def weights(self, Xtr, ytr, Xte):
+ # check "Direct Density Ratio Estimation for
+ # Large-scale Covariate Shift Adaptation", Eq.28
+
+ if issparse(Xtr):
+ X = vstack([Xtr, Xte])
+ else:
+ X = np.concatenate([Xtr, Xte])
+
+ y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
+
+ logreg = GridSearchCV(
+ LogisticRegression(),
+ param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
+ n_jobs=-1,
+ )
+ logreg.fit(X, y)
+ probs = logreg.predict_proba(Xtr)
+ prob_train, prob_test = probs[:, 0], probs[:, 1]
+ prior_train = Xtr.shape[0]
+ prior_test = Xte.shape[0]
+ w = (prior_train / prior_test) * (prob_test / prob_train)
+ return w
+
+
+class KDEx2(ImportanceWeight):
+ def __init__(self):
+ pass
+
+ def weights(self, Xtr, ytr, Xte):
+ params = {"bandwidth": np.logspace(-1, 1, 20)}
+ log_likelihood_tr = (
+ GridSearchCV(KernelDensity(), params).fit(Xtr).score_samples(Xtr)
+ )
+ log_likelihood_te = (
+ GridSearchCV(KernelDensity(), params).fit(Xte).score_samples(Xtr)
+ )
+ likelihood_tr = np.exp(log_likelihood_tr)
+ likelihood_te = np.exp(log_likelihood_te)
+ return likelihood_te / likelihood_tr
+
+
+if __name__ == "__main__":
+ # d = Dataset("rcv1", target="CCAT").get_raw()
+ d = Dataset("imdb", n_prevalences=1).get()[0]
+
+ tstart = time.time()
+ lr = LogisticRegression()
+ lr.fit(*d.train.Xy)
+ val_preds = lr.predict(d.validation.X)
+ protocol = APP(
+ d.test,
+ n_prevalences=21,
+ repeats=1,
+ sample_size=100,
+ return_type="labelled_collection",
+ )
+
+ results = []
+ for sample in protocol():
+ wx = iw.kliep(d.validation.X, d.validation.y, sample.X)
+ test_preds = lr.predict(sample.X)
+ estim_acc = np.sum((1.0 * (val_preds == d.validation.y)) * wx) / np.sum(wx)
+ true_acc = metrics.accuracy_score(sample.y, test_preds)
+ results.append((sample.prevalence(), estim_acc, true_acc))
+
+ tend = time.time()
+
+ for r in results:
+ print(*r)
+
+ print(f"logreg finished [took {tend-tstart:.3f}s]")
+ import win11toast
+
+ win11toast.notify("models.py", "Completed")
diff --git a/baselines/pykliep.py b/baselines/pykliep.py
index 8c67ea4..caad427 100644
--- a/baselines/pykliep.py
+++ b/baselines/pykliep.py
@@ -1,221 +1,221 @@
-import warnings
-
-import numpy as np
-from scipy.sparse import csr_matrix
-
-
-class DensityRatioEstimator:
- """
- Class to accomplish direct density estimation implementing the original KLIEP
- algorithm from Direct Importance Estimation with Model Selection
- and Its Application to Covariate Shift Adaptation by Sugiyama et al.
-
- The training set is distributed via
- train ~ p(x)
- and the test set is distributed via
- test ~ q(x).
-
- The KLIEP algorithm and its variants approximate w(x) = q(x) / p(x) directly. The predict function returns the
- estimate of w(x). The function w(x) can serve as sample weights for the training set during
- training to modify the expectation function that the model's loss function is optimized via,
- i.e.
-
- E_{x ~ w(x)p(x)} loss(x) = E_{x ~ q(x)} loss(x).
-
- Usage :
- The fit method is used to run the KLIEP algorithm using LCV and returns value of J
- trained on the entire training/test set with the best sigma found.
- Use the predict method on the training set to determine the sample weights from the KLIEP algorithm.
- """
-
- def __init__(
- self,
- max_iter=5000,
- num_params=[0.1, 0.2],
- epsilon=1e-4,
- cv=3,
- sigmas=[0.01, 0.1, 0.25, 0.5, 0.75, 1],
- random_state=None,
- verbose=0,
- ):
- """
- Direct density estimation using an inner LCV loop to estimate the proper model. Can be used with sklearn
- cross validation methods with or without storing the inner CV. To use a standard grid search.
-
-
- max_iter : Number of iterations to perform
- num_params : List of number of test set vectors used to construct the approximation for inner LCV.
- Must be a float. Original paper used 10%, i.e. =.1
- sigmas : List of sigmas to be used in inner LCV loop.
- epsilon : Additive factor in the iterative algorithm for numerical stability.
- """
- self.max_iter = max_iter
- self.num_params = num_params
- self.epsilon = epsilon
- self.verbose = verbose
- self.sigmas = sigmas
- self.cv = cv
- self.random_state = 0
-
- def fit(self, X_train, X_test, alpha_0=None):
- """Uses cross validation to select sigma as in the original paper (LCV).
- In a break from sklearn convention, y=X_test.
- The parameter cv corresponds to R in the original paper.
- Once found, the best sigma is used to train on the full set."""
-
- # LCV loop, shuffle a copy in place for performance.
- cv = self.cv
- chunk = int(X_test.shape[0] / float(cv))
- if self.random_state is not None:
- np.random.seed(self.random_state)
- # if isinstance(X_test, csr_matrix):
- # X_test_shuffled = X_test.toarray()
- # else:
- # X_test_shuffled = X_test.copy()
- X_test_shuffled = X_test.copy()
-
- X_test_index = np.arange(X_test_shuffled.shape[0])
- np.random.shuffle(X_test_index)
- X_test_shuffled = X_test_shuffled[X_test_index, :]
-
- j_scores = {}
-
- if type(self.sigmas) != list:
- self.sigmas = [self.sigmas]
-
- if type(self.num_params) != list:
- self.num_params = [self.num_params]
-
- if len(self.sigmas) * len(self.num_params) > 1:
- # Inner LCV loop
- for num_param in self.num_params:
- for sigma in self.sigmas:
- j_scores[(num_param, sigma)] = np.zeros(cv)
- for k in range(1, cv + 1):
- if self.verbose > 0:
- print("Training: sigma: %s R: %s" % (sigma, k))
- X_test_fold = X_test_shuffled[(k - 1) * chunk : k * chunk, :]
- j_scores[(num_param, sigma)][k - 1] = self._fit(
- X_train=X_train,
- X_test=X_test_fold,
- num_parameters=num_param,
- sigma=sigma,
- )
- j_scores[(num_param, sigma)] = np.mean(j_scores[(num_param, sigma)])
-
- sorted_scores = sorted(
- [x for x in j_scores.items() if np.isfinite(x[1])],
- key=lambda x: x[1],
- reverse=True,
- )
- if len(sorted_scores) == 0:
- warnings.warn("LCV failed to converge for all values of sigma.")
- return self
- self._sigma = sorted_scores[0][0][1]
- self._num_parameters = sorted_scores[0][0][0]
- self._j_scores = sorted_scores
- else:
- self._sigma = self.sigmas[0]
- self._num_parameters = self.num_params[0]
- # best sigma
- self._j = self._fit(
- X_train=X_train,
- X_test=X_test_shuffled,
- num_parameters=self._num_parameters,
- sigma=self._sigma,
- )
-
- return self # Compatibility with sklearn
-
- def _fit(self, X_train, X_test, num_parameters, sigma, alpha_0=None):
- """Fits the estimator with the given parameters w-hat and returns J"""
-
- num_parameters = num_parameters
-
- if type(num_parameters) == float:
- num_parameters = int(X_test.shape[0] * num_parameters)
-
- self._select_param_vectors(
- X_test=X_test, sigma=sigma, num_parameters=num_parameters
- )
-
- # if isinstance(X_train, csr_matrix):
- # X_train = X_train.toarray()
- X_train = self._reshape_X(X_train)
- X_test = self._reshape_X(X_test)
-
- if alpha_0 is None:
- alpha_0 = np.ones(shape=(num_parameters, 1)) / float(num_parameters)
-
- self._find_alpha(
- X_train=X_train,
- X_test=X_test,
- num_parameters=num_parameters,
- epsilon=self.epsilon,
- alpha_0=alpha_0,
- sigma=sigma,
- )
-
- return self._calculate_j(X_test, sigma=sigma)
-
- def _calculate_j(self, X_test, sigma):
- pred = self.predict(X_test, sigma=sigma) + 0.0000001
- log = np.log(pred).sum()
- return log / (X_test.shape[0])
-
- def score(self, X_test):
- """Return the J score, similar to sklearn's API"""
- return self._calculate_j(X_test=X_test, sigma=self._sigma)
-
- @staticmethod
- def _reshape_X(X):
- """Reshape input from mxn to mx1xn to take advantage of numpy broadcasting."""
- if len(X.shape) != 3:
- return X.reshape((X.shape[0], 1, X.shape[1]))
- return X
-
- def _select_param_vectors(self, X_test, sigma, num_parameters):
- """X_test is the test set. b is the number of parameters."""
- indices = np.random.choice(X_test.shape[0], size=num_parameters, replace=False)
- self._test_vectors = X_test[indices, :].copy()
- self._phi_fitted = True
-
- def _phi(self, X, sigma=None):
- if sigma is None:
- sigma = self._sigma
-
- if self._phi_fitted:
- return np.exp(
- -np.sum((X - self._test_vectors) ** 2, axis=-1) / (2 * sigma**2)
- )
- raise Exception("Phi not fitted.")
-
- def _find_alpha(self, alpha_0, X_train, X_test, num_parameters, sigma, epsilon):
- A = np.zeros(shape=(X_test.shape[0], num_parameters))
- b = np.zeros(shape=(num_parameters, 1))
-
- A = self._phi(X_test, sigma)
- b = self._phi(X_train, sigma).sum(axis=0) / X_train.shape[0]
- b = b.reshape((num_parameters, 1))
-
- out = alpha_0.copy()
- for k in range(self.max_iter):
- mat = np.dot(A, out)
- mat += 0.000000001
- out += epsilon * np.dot(np.transpose(A), 1.0 / mat)
- out += b * (
- ((1 - np.dot(np.transpose(b), out)) / np.dot(np.transpose(b), b))
- )
- out = np.maximum(0, out)
- out /= np.dot(np.transpose(b), out)
-
- self._alpha = out
- self._fitted = True
-
- def predict(self, X, sigma=None):
- """Equivalent of w(X) from the original paper."""
-
- X = self._reshape_X(X)
- if not self._fitted:
- raise Exception("Not fitted!")
- return np.dot(self._phi(X, sigma=sigma), self._alpha).reshape((X.shape[0],))
+import warnings
+
+import numpy as np
+from scipy.sparse import csr_matrix
+
+
+class DensityRatioEstimator:
+ """
+ Class to accomplish direct density estimation implementing the original KLIEP
+ algorithm from Direct Importance Estimation with Model Selection
+ and Its Application to Covariate Shift Adaptation by Sugiyama et al.
+
+ The training set is distributed via
+ train ~ p(x)
+ and the test set is distributed via
+ test ~ q(x).
+
+ The KLIEP algorithm and its variants approximate w(x) = q(x) / p(x) directly. The predict function returns the
+ estimate of w(x). The function w(x) can serve as sample weights for the training set during
+ training to modify the expectation function that the model's loss function is optimized via,
+ i.e.
+
+ E_{x ~ w(x)p(x)} loss(x) = E_{x ~ q(x)} loss(x).
+
+ Usage :
+ The fit method is used to run the KLIEP algorithm using LCV and returns value of J
+ trained on the entire training/test set with the best sigma found.
+ Use the predict method on the training set to determine the sample weights from the KLIEP algorithm.
+ """
+
+ def __init__(
+ self,
+ max_iter=5000,
+ num_params=[0.1, 0.2],
+ epsilon=1e-4,
+ cv=3,
+ sigmas=[0.01, 0.1, 0.25, 0.5, 0.75, 1],
+ random_state=None,
+ verbose=0,
+ ):
+ """
+ Direct density estimation using an inner LCV loop to estimate the proper model. Can be used with sklearn
+ cross validation methods with or without storing the inner CV. To use a standard grid search.
+
+
+ max_iter : Number of iterations to perform
+ num_params : List of number of test set vectors used to construct the approximation for inner LCV.
+ Must be a float. Original paper used 10%, i.e. =.1
+ sigmas : List of sigmas to be used in inner LCV loop.
+ epsilon : Additive factor in the iterative algorithm for numerical stability.
+ """
+ self.max_iter = max_iter
+ self.num_params = num_params
+ self.epsilon = epsilon
+ self.verbose = verbose
+ self.sigmas = sigmas
+ self.cv = cv
+ self.random_state = 0
+
+ def fit(self, X_train, X_test, alpha_0=None):
+ """Uses cross validation to select sigma as in the original paper (LCV).
+ In a break from sklearn convention, y=X_test.
+ The parameter cv corresponds to R in the original paper.
+ Once found, the best sigma is used to train on the full set."""
+
+ # LCV loop, shuffle a copy in place for performance.
+ cv = self.cv
+ chunk = int(X_test.shape[0] / float(cv))
+ if self.random_state is not None:
+ np.random.seed(self.random_state)
+ # if isinstance(X_test, csr_matrix):
+ # X_test_shuffled = X_test.toarray()
+ # else:
+ # X_test_shuffled = X_test.copy()
+ X_test_shuffled = X_test.copy()
+
+ X_test_index = np.arange(X_test_shuffled.shape[0])
+ np.random.shuffle(X_test_index)
+ X_test_shuffled = X_test_shuffled[X_test_index, :]
+
+ j_scores = {}
+
+ if type(self.sigmas) != list:
+ self.sigmas = [self.sigmas]
+
+ if type(self.num_params) != list:
+ self.num_params = [self.num_params]
+
+ if len(self.sigmas) * len(self.num_params) > 1:
+ # Inner LCV loop
+ for num_param in self.num_params:
+ for sigma in self.sigmas:
+ j_scores[(num_param, sigma)] = np.zeros(cv)
+ for k in range(1, cv + 1):
+ if self.verbose > 0:
+ print("Training: sigma: %s R: %s" % (sigma, k))
+ X_test_fold = X_test_shuffled[(k - 1) * chunk : k * chunk, :]
+ j_scores[(num_param, sigma)][k - 1] = self._fit(
+ X_train=X_train,
+ X_test=X_test_fold,
+ num_parameters=num_param,
+ sigma=sigma,
+ )
+ j_scores[(num_param, sigma)] = np.mean(j_scores[(num_param, sigma)])
+
+ sorted_scores = sorted(
+ [x for x in j_scores.items() if np.isfinite(x[1])],
+ key=lambda x: x[1],
+ reverse=True,
+ )
+ if len(sorted_scores) == 0:
+ warnings.warn("LCV failed to converge for all values of sigma.")
+ return self
+ self._sigma = sorted_scores[0][0][1]
+ self._num_parameters = sorted_scores[0][0][0]
+ self._j_scores = sorted_scores
+ else:
+ self._sigma = self.sigmas[0]
+ self._num_parameters = self.num_params[0]
+ # best sigma
+ self._j = self._fit(
+ X_train=X_train,
+ X_test=X_test_shuffled,
+ num_parameters=self._num_parameters,
+ sigma=self._sigma,
+ )
+
+ return self # Compatibility with sklearn
+
+ def _fit(self, X_train, X_test, num_parameters, sigma, alpha_0=None):
+ """Fits the estimator with the given parameters w-hat and returns J"""
+
+ num_parameters = num_parameters
+
+ if type(num_parameters) == float:
+ num_parameters = int(X_test.shape[0] * num_parameters)
+
+ self._select_param_vectors(
+ X_test=X_test, sigma=sigma, num_parameters=num_parameters
+ )
+
+ # if isinstance(X_train, csr_matrix):
+ # X_train = X_train.toarray()
+ X_train = self._reshape_X(X_train)
+ X_test = self._reshape_X(X_test)
+
+ if alpha_0 is None:
+ alpha_0 = np.ones(shape=(num_parameters, 1)) / float(num_parameters)
+
+ self._find_alpha(
+ X_train=X_train,
+ X_test=X_test,
+ num_parameters=num_parameters,
+ epsilon=self.epsilon,
+ alpha_0=alpha_0,
+ sigma=sigma,
+ )
+
+ return self._calculate_j(X_test, sigma=sigma)
+
+ def _calculate_j(self, X_test, sigma):
+ pred = self.predict(X_test, sigma=sigma) + 0.0000001
+ log = np.log(pred).sum()
+ return log / (X_test.shape[0])
+
+ def score(self, X_test):
+ """Return the J score, similar to sklearn's API"""
+ return self._calculate_j(X_test=X_test, sigma=self._sigma)
+
+ @staticmethod
+ def _reshape_X(X):
+ """Reshape input from mxn to mx1xn to take advantage of numpy broadcasting."""
+ if len(X.shape) != 3:
+ return X.reshape((X.shape[0], 1, X.shape[1]))
+ return X
+
+ def _select_param_vectors(self, X_test, sigma, num_parameters):
+ """X_test is the test set. b is the number of parameters."""
+ indices = np.random.choice(X_test.shape[0], size=num_parameters, replace=False)
+ self._test_vectors = X_test[indices, :].copy()
+ self._phi_fitted = True
+
+ def _phi(self, X, sigma=None):
+ if sigma is None:
+ sigma = self._sigma
+
+ if self._phi_fitted:
+ return np.exp(
+ -np.sum((X - self._test_vectors) ** 2, axis=-1) / (2 * sigma**2)
+ )
+ raise Exception("Phi not fitted.")
+
+ def _find_alpha(self, alpha_0, X_train, X_test, num_parameters, sigma, epsilon):
+ A = np.zeros(shape=(X_test.shape[0], num_parameters))
+ b = np.zeros(shape=(num_parameters, 1))
+
+ A = self._phi(X_test, sigma)
+ b = self._phi(X_train, sigma).sum(axis=0) / X_train.shape[0]
+ b = b.reshape((num_parameters, 1))
+
+ out = alpha_0.copy()
+ for k in range(self.max_iter):
+ mat = np.dot(A, out)
+ mat += 0.000000001
+ out += epsilon * np.dot(np.transpose(A), 1.0 / mat)
+ out += b * (
+ ((1 - np.dot(np.transpose(b), out)) / np.dot(np.transpose(b), b))
+ )
+ out = np.maximum(0, out)
+ out /= np.dot(np.transpose(b), out)
+
+ self._alpha = out
+ self._fitted = True
+
+ def predict(self, X, sigma=None):
+ """Equivalent of w(X) from the original paper."""
+
+ X = self._reshape_X(X)
+ if not self._fitted:
+ raise Exception("Not fitted!")
+ return np.dot(self._phi(X, sigma=sigma), self._alpha).reshape((X.shape[0],))
diff --git a/baselines/rca.py b/baselines/rca.py
index d85b8d8..2ce307a 100644
--- a/baselines/rca.py
+++ b/baselines/rca.py
@@ -1,14 +1,14 @@
-import numpy as np
-from sklearn import clone
-from sklearn.base import BaseEstimator
-
-
-def clone_fit(c_model: BaseEstimator, data, labels):
- c_model2 = clone(c_model)
- c_model2.fit(data, labels)
- return c_model2
-
-def get_score(pred1, pred2, labels):
- return np.mean((pred1 == labels).astype(int) - (pred2 == labels).astype(int))
-
-
+import numpy as np
+from sklearn import clone
+from sklearn.base import BaseEstimator
+
+
+def clone_fit(c_model: BaseEstimator, data, labels):
+ c_model2 = clone(c_model)
+ c_model2.fit(data, labels)
+ return c_model2
+
+def get_score(pred1, pred2, labels):
+ return np.mean((pred1 == labels).astype(int) - (pred2 == labels).astype(int))
+
+
diff --git a/conf.yaml b/conf.yaml
index fb49814..8ff1057 100644
--- a/conf.yaml
+++ b/conf.yaml
@@ -1,233 +1,233 @@
-debug_conf: &debug_conf
- global:
- METRICS:
- - acc
- DATASET_N_PREVS: 5
- DATASET_PREVS:
- # - 0.2
- - 0.5
- # - 0.8
-
- confs:
- - DATASET_NAME: rcv1
- DATASET_TARGET: CCAT
-
- plot_confs:
- debug:
- PLOT_ESTIMATORS:
- - mulmc_sld
- - atc_mc
- PLOT_STDEV: true
-
-mc_conf: &mc_conf
- global:
- METRICS:
- - acc
- DATASET_N_PREVS: 9
- DATASET_DIR_UPDATE: true
-
- confs:
- - DATASET_NAME: rcv1
- DATASET_TARGET: CCAT
- # - DATASET_NAME: imdb
-
- plot_confs:
- debug3:
- PLOT_ESTIMATORS:
- - binmc_sld
- - mulmc_sld
- - binne_sld
- - mulne_sld
- - bin_sld_gs
- - mul_sld_gs
- - atc_mc
- PLOT_STDEV: true
-
-test_conf: &test_conf
- global:
- METRICS:
- - acc
- - f1
- DATASET_N_PREVS: 9
-
- confs:
- - DATASET_NAME: rcv1
- DATASET_TARGET: CCAT
- # - DATASET_NAME: imdb
-
- plot_confs:
- gs_vs_gsq:
- PLOT_ESTIMATORS:
- - bin_sld
- - bin_sld_gs
- - bin_sld_gsq
- - mul_sld
- - mul_sld_gs
- - mul_sld_gsq
- gs_vs_atc:
- PLOT_ESTIMATORS:
- - bin_sld
- - bin_sld_gs
- - mul_sld
- - mul_sld_gs
- - atc_mc
- - atc_ne
- sld_vs_pacc:
- PLOT_ESTIMATORS:
- - bin_sld
- - bin_sld_gs
- - mul_sld
- - mul_sld_gs
- - bin_pacc
- - bin_pacc_gs
- - mul_pacc
- - mul_pacc_gs
- - atc_mc
- - atc_ne
- pacc_vs_atc:
- PLOT_ESTIMATORS:
- - bin_pacc
- - bin_pacc_gs
- - mul_pacc
- - mul_pacc_gs
- - atc_mc
- - atc_ne
-
-main_conf: &main_conf
-
- global:
- METRICS:
- - acc
- - f1
- DATASET_N_PREVS: 9
- DATASET_DIR_UPDATE: true
-
- confs:
- - DATASET_NAME: rcv1
- DATASET_TARGET: CCAT
- - DATASET_NAME: imdb
- confs_next:
- - DATASET_NAME: rcv1
- DATASET_TARGET: GCAT
- - DATASET_NAME: rcv1
- DATASET_TARGET: MCAT
-
- plot_confs:
- gs_vs_qgs:
- PLOT_ESTIMATORS:
- - mul_sld_gs
- - bin_sld_gs
- - mul_sld_gsq
- - bin_sld_gsq
- - atc_mc
- - atc_ne
- PLOT_STDEV: true
- plot_confs_completed:
- max_conf_vs_atc_pacc:
- PLOT_ESTIMATORS:
- - bin_pacc
- - binmc_pacc
- - mul_pacc
- - mulmc_pacc
- - atc_mc
- PLOT_STDEV: true
- max_conf_vs_entropy_pacc:
- PLOT_ESTIMATORS:
- - binmc_pacc
- - binne_pacc
- - mulmc_pacc
- - mulne_pacc
- - atc_mc
- PLOT_STDEV: true
- gs_vs_atc:
- PLOT_ESTIMATORS:
- - mul_sld_gs
- - bin_sld_gs
- - mul_pacc_gs
- - bin_pacc_gs
- - atc_mc
- - atc_ne
- PLOT_STDEV: true
- gs_vs_all:
- PLOT_ESTIMATORS:
- - mul_sld_gs
- - bin_sld_gs
- - mul_pacc_gs
- - bin_pacc_gs
- - atc_mc
- - doc_feat
- - kfcv
- PLOT_STDEV: true
- gs_vs_qgs:
- PLOT_ESTIMATORS:
- - mul_sld_gs
- - bin_sld_gs
- - mul_sld_gsq
- - bin_sld_gsq
- - atc_mc
- - atc_ne
- PLOT_STDEV: true
- cc_vs_other:
- PLOT_ESTIMATORS:
- - mul_cc
- - bin_cc
- - mul_sld
- - bin_sld
- - mul_pacc
- - bin_pacc
- PLOT_STDEV: true
- max_conf_vs_atc:
- PLOT_ESTIMATORS:
- - bin_sld
- - binmc_sld
- - mul_sld
- - mulmc_sld
- - atc_mc
- PLOT_STDEV: true
- max_conf_vs_entropy:
- PLOT_ESTIMATORS:
- - binmc_sld
- - binne_sld
- - mulmc_sld
- - mulne_sld
- - atc_mc
- PLOT_STDEV: true
- sld_vs_pacc:
- PLOT_ESTIMATORS:
- - bin_sld
- - mul_sld
- - bin_pacc
- - mul_pacc
- - atc_mc
- PLOT_STDEV: true
- plot_confs_other:
- best_vs_atc:
- PLOT_ESTIMATORS:
- - mul_sld_bcts
- - mul_sld_gs
- - bin_sld_bcts
- - bin_sld_gs
- - atc_mc
- - atc_ne
- all_vs_atc:
- PLOT_ESTIMATORS:
- - bin_sld
- - bin_sld_bcts
- - bin_sld_gs
- - mul_sld
- - mul_sld_bcts
- - mul_sld_gs
- - atc_mc
- - atc_ne
- best_vs_all:
- PLOT_ESTIMATORS:
- - bin_sld_bcts
- - bin_sld_gs
- - mul_sld_bcts
- - mul_sld_gs
- - kfcv
- - atc_mc
- - atc_ne
- - doc_feat
-
+debug_conf: &debug_conf
+ global:
+ METRICS:
+ - acc
+ DATASET_N_PREVS: 5
+ DATASET_PREVS:
+ # - 0.2
+ - 0.5
+ # - 0.8
+
+ confs:
+ - DATASET_NAME: rcv1
+ DATASET_TARGET: CCAT
+
+ plot_confs:
+ debug:
+ PLOT_ESTIMATORS:
+ - mulmc_sld
+ - atc_mc
+ PLOT_STDEV: true
+
+mc_conf: &mc_conf
+ global:
+ METRICS:
+ - acc
+ DATASET_N_PREVS: 9
+ DATASET_DIR_UPDATE: true
+
+ confs:
+ - DATASET_NAME: rcv1
+ DATASET_TARGET: CCAT
+ # - DATASET_NAME: imdb
+
+ plot_confs:
+ debug3:
+ PLOT_ESTIMATORS:
+ - binmc_sld
+ - mulmc_sld
+ - binne_sld
+ - mulne_sld
+ - bin_sld_gs
+ - mul_sld_gs
+ - atc_mc
+ PLOT_STDEV: true
+
+test_conf: &test_conf
+ global:
+ METRICS:
+ - acc
+ - f1
+ DATASET_N_PREVS: 9
+
+ confs:
+ - DATASET_NAME: rcv1
+ DATASET_TARGET: CCAT
+ # - DATASET_NAME: imdb
+
+ plot_confs:
+ gs_vs_gsq:
+ PLOT_ESTIMATORS:
+ - bin_sld
+ - bin_sld_gs
+ - bin_sld_gsq
+ - mul_sld
+ - mul_sld_gs
+ - mul_sld_gsq
+ gs_vs_atc:
+ PLOT_ESTIMATORS:
+ - bin_sld
+ - bin_sld_gs
+ - mul_sld
+ - mul_sld_gs
+ - atc_mc
+ - atc_ne
+ sld_vs_pacc:
+ PLOT_ESTIMATORS:
+ - bin_sld
+ - bin_sld_gs
+ - mul_sld
+ - mul_sld_gs
+ - bin_pacc
+ - bin_pacc_gs
+ - mul_pacc
+ - mul_pacc_gs
+ - atc_mc
+ - atc_ne
+ pacc_vs_atc:
+ PLOT_ESTIMATORS:
+ - bin_pacc
+ - bin_pacc_gs
+ - mul_pacc
+ - mul_pacc_gs
+ - atc_mc
+ - atc_ne
+
+main_conf: &main_conf
+
+ global:
+ METRICS:
+ - acc
+ - f1
+ DATASET_N_PREVS: 9
+ DATASET_DIR_UPDATE: true
+
+ confs:
+ - DATASET_NAME: rcv1
+ DATASET_TARGET: CCAT
+ - DATASET_NAME: imdb
+ confs_next:
+ - DATASET_NAME: rcv1
+ DATASET_TARGET: GCAT
+ - DATASET_NAME: rcv1
+ DATASET_TARGET: MCAT
+
+ plot_confs:
+ gs_vs_qgs:
+ PLOT_ESTIMATORS:
+ - mul_sld_gs
+ - bin_sld_gs
+ - mul_sld_gsq
+ - bin_sld_gsq
+ - atc_mc
+ - atc_ne
+ PLOT_STDEV: true
+ plot_confs_completed:
+ max_conf_vs_atc_pacc:
+ PLOT_ESTIMATORS:
+ - bin_pacc
+ - binmc_pacc
+ - mul_pacc
+ - mulmc_pacc
+ - atc_mc
+ PLOT_STDEV: true
+ max_conf_vs_entropy_pacc:
+ PLOT_ESTIMATORS:
+ - binmc_pacc
+ - binne_pacc
+ - mulmc_pacc
+ - mulne_pacc
+ - atc_mc
+ PLOT_STDEV: true
+ gs_vs_atc:
+ PLOT_ESTIMATORS:
+ - mul_sld_gs
+ - bin_sld_gs
+ - mul_pacc_gs
+ - bin_pacc_gs
+ - atc_mc
+ - atc_ne
+ PLOT_STDEV: true
+ gs_vs_all:
+ PLOT_ESTIMATORS:
+ - mul_sld_gs
+ - bin_sld_gs
+ - mul_pacc_gs
+ - bin_pacc_gs
+ - atc_mc
+ - doc_feat
+ - kfcv
+ PLOT_STDEV: true
+ gs_vs_qgs:
+ PLOT_ESTIMATORS:
+ - mul_sld_gs
+ - bin_sld_gs
+ - mul_sld_gsq
+ - bin_sld_gsq
+ - atc_mc
+ - atc_ne
+ PLOT_STDEV: true
+ cc_vs_other:
+ PLOT_ESTIMATORS:
+ - mul_cc
+ - bin_cc
+ - mul_sld
+ - bin_sld
+ - mul_pacc
+ - bin_pacc
+ PLOT_STDEV: true
+ max_conf_vs_atc:
+ PLOT_ESTIMATORS:
+ - bin_sld
+ - binmc_sld
+ - mul_sld
+ - mulmc_sld
+ - atc_mc
+ PLOT_STDEV: true
+ max_conf_vs_entropy:
+ PLOT_ESTIMATORS:
+ - binmc_sld
+ - binne_sld
+ - mulmc_sld
+ - mulne_sld
+ - atc_mc
+ PLOT_STDEV: true
+ sld_vs_pacc:
+ PLOT_ESTIMATORS:
+ - bin_sld
+ - mul_sld
+ - bin_pacc
+ - mul_pacc
+ - atc_mc
+ PLOT_STDEV: true
+ plot_confs_other:
+ best_vs_atc:
+ PLOT_ESTIMATORS:
+ - mul_sld_bcts
+ - mul_sld_gs
+ - bin_sld_bcts
+ - bin_sld_gs
+ - atc_mc
+ - atc_ne
+ all_vs_atc:
+ PLOT_ESTIMATORS:
+ - bin_sld
+ - bin_sld_bcts
+ - bin_sld_gs
+ - mul_sld
+ - mul_sld_bcts
+ - mul_sld_gs
+ - atc_mc
+ - atc_ne
+ best_vs_all:
+ PLOT_ESTIMATORS:
+ - bin_sld_bcts
+ - bin_sld_gs
+ - mul_sld_bcts
+ - mul_sld_gs
+ - kfcv
+ - atc_mc
+ - atc_ne
+ - doc_feat
+
exec: *main_conf
\ No newline at end of file
diff --git a/out_imdb.md b/out_imdb.md
index d3bd704..0d5144f 100644
--- a/out_imdb.md
+++ b/out_imdb.md
@@ -1,445 +1,445 @@
-
-target: default
-train: [0.5 0.5]
-validation: [0.5 0.5]
-evaluate_binary: 277.300s
-evaluate_multiclass: 139.986s
-kfcv: 98.625s
-atc_mc: 93.304s
-atc_ne: 91.201s
-doc_feat: 29.930s
-rca_score: 1018.341s
-rca_star_score: 1013.733s
-tot: 1054.413s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0154 |
- 0.0177 |
- 0.0249 |
- 0.0291 |
- 0.0291 |
- 0.0248 |
- 0.2705 |
- 0.2413 |
-
-
- | (0.05, 0.95) |
- 0.0309 |
- 0.0284 |
- 0.0252 |
- 0.0300 |
- 0.0300 |
- 0.0247 |
- 0.2796 |
- 0.2504 |
-
-
- | (0.1, 0.9) |
- 0.0309 |
- 0.0302 |
- 0.0251 |
- 0.0279 |
- 0.0279 |
- 0.0250 |
- 0.2722 |
- 0.2430 |
-
-
- | (0.15, 0.85) |
- 0.0310 |
- 0.0339 |
- 0.0245 |
- 0.0269 |
- 0.0269 |
- 0.0244 |
- 0.2684 |
- 0.2392 |
-
-
- | (0.2, 0.8) |
- 0.0411 |
- 0.0407 |
- 0.0259 |
- 0.0292 |
- 0.0292 |
- 0.0257 |
- 0.2724 |
- 0.2432 |
-
-
- | (0.25, 0.75) |
- 0.0381 |
- 0.0376 |
- 0.0262 |
- 0.0319 |
- 0.0319 |
- 0.0259 |
- 0.2701 |
- 0.2409 |
-
-
- | (0.3, 0.7) |
- 0.0442 |
- 0.0452 |
- 0.0254 |
- 0.0273 |
- 0.0273 |
- 0.0256 |
- 0.2650 |
- 0.2358 |
-
-
- | (0.35, 0.65) |
- 0.0480 |
- 0.0498 |
- 0.0236 |
- 0.0257 |
- 0.0257 |
- 0.0235 |
- 0.2640 |
- 0.2347 |
-
-
- | (0.4, 0.6) |
- 0.0401 |
- 0.0431 |
- 0.0222 |
- 0.0296 |
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+target: default
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+validation: [0.5 0.5]
+evaluate_binary: 277.300s
+evaluate_multiclass: 139.986s
+kfcv: 98.625s
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+atc_ne: 91.201s
+doc_feat: 29.930s
+rca_score: 1018.341s
+rca_star_score: 1013.733s
+tot: 1054.413s
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diff --git a/out_rcv1.md b/out_rcv1.md
index 17c6121..c5ac70e 100644
--- a/out_rcv1.md
+++ b/out_rcv1.md
@@ -1,17355 +1,17355 @@
-
-target: C12
-train: [0.98358389 0.01641611]
-validation: [0.98349892 0.01650108]
-evaluate_binary: 258.363s
-evaluate_multiclass: 116.180s
-kfcv: 104.789s
-atc_mc: 154.996s
-atc_ne: 144.298s
-doc_feat: 88.728s
-rca_score: 909.590s
-rca_star_score: 899.370s
-tot: 951.474s
-
-
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- |
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- | (0.85, 0.15) |
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- 0.5783 |
- 0.0859 |
- 0.0859 |
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- | (0.9, 0.1) |
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- 0.0837 |
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- | (1.0, 0.0) |
- 0.0000 |
- 0.0000 |
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- 0.0000 |
- 0.0000 |
-
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-
-
-target: C13
-train: [0.95913254 0.04086746]
-validation: [0.95904968 0.04095032]
-evaluate_binary: 293.415s
-evaluate_multiclass: 130.949s
-kfcv: 164.741s
-atc_mc: 163.221s
-atc_ne: 98.244s
-doc_feat: 127.361s
-rca_score: 661.548s
-rca_star_score: 635.802s
-tot: 705.253s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
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- | (0.3, 0.7) |
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-
-
- | (0.45, 0.55) |
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- 0.0388 |
- 0.0388 |
-
-
- | (0.5, 0.5) |
- 0.0265 |
- 0.0409 |
- 0.4646 |
- 0.0416 |
- 0.0416 |
-
-
- | (0.55, 0.45) |
- 0.0254 |
- 0.0334 |
- 0.4724 |
- 0.0337 |
- 0.0337 |
-
-
- | (0.6, 0.4) |
- 0.0255 |
- 0.0347 |
- 0.4708 |
- 0.0354 |
- 0.0354 |
-
-
- | (0.65, 0.35) |
- 0.0280 |
- 0.0395 |
- 0.4656 |
- 0.0405 |
- 0.0405 |
-
-
- | (0.7, 0.3) |
- 0.0302 |
- 0.0398 |
- 0.4651 |
- 0.0410 |
- 0.0410 |
-
-
- | (0.75, 0.25) |
- 0.0278 |
- 0.0401 |
- 0.4633 |
- 0.0429 |
- 0.0429 |
-
-
- | (0.8, 0.2) |
- 0.0246 |
- 0.0377 |
- 0.4679 |
- 0.0383 |
- 0.0383 |
-
-
- | (0.85, 0.15) |
- 0.0120 |
- 0.0236 |
- 0.4850 |
- 0.0211 |
- 0.0211 |
-
-
- | (0.9, 0.1) |
- 0.0298 |
- 0.0455 |
- 0.4667 |
- 0.0394 |
- 0.0394 |
-
-
- | (0.95, 0.05) |
- 0.0269 |
- 0.0338 |
- 0.4795 |
- 0.0267 |
- 0.0267 |
-
-
- | (1.0, 0.0) |
- 0.0000 |
- 0.0253 |
- 0.5061 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: C15
-train: [0.81950924 0.18049076]
-validation: [0.81943844 0.18056156]
-evaluate_binary: 329.208s
-evaluate_multiclass: 130.846s
-kfcv: 170.297s
-atc_mc: 170.842s
-atc_ne: 107.158s
-doc_feat: 71.484s
-rca_score: 1210.284s
-rca_star_score: 1189.765s
-tot: 1265.086s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0066 |
- 0.0143 |
- 0.1796 |
- 0.0613 |
- 0.0613 |
- 0.1828 |
- 0.5585 |
- 0.5360 |
-
-
- | (0.05, 0.95) |
- 0.0400 |
- 0.0404 |
- 0.1774 |
- 0.0671 |
- 0.0671 |
- 0.1806 |
- 0.5588 |
- 0.5363 |
-
-
- | (0.1, 0.9) |
- 0.0459 |
- 0.0461 |
- 0.1637 |
- 0.0596 |
- 0.0596 |
- 0.1670 |
- 0.5707 |
- 0.5483 |
-
-
- | (0.15, 0.85) |
- 0.0375 |
- 0.0379 |
- 0.1456 |
- 0.0516 |
- 0.0516 |
- 0.1490 |
- 0.5338 |
- 0.5155 |
-
-
- | (0.2, 0.8) |
- 0.0430 |
- 0.0425 |
- 0.1439 |
- 0.0552 |
- 0.0552 |
- 0.1473 |
- 0.4091 |
- 0.3967 |
-
-
- | (0.25, 0.75) |
- 0.0326 |
- 0.0325 |
- 0.1241 |
- 0.0505 |
- 0.0505 |
- 0.1276 |
- 0.2468 |
- 0.2473 |
-
-
- | (0.3, 0.7) |
- 0.0351 |
- 0.0380 |
- 0.1151 |
- 0.0482 |
- 0.0482 |
- 0.1186 |
- 0.1403 |
- 0.1543 |
-
-
- | (0.35, 0.65) |
- 0.0291 |
- 0.0299 |
- 0.1070 |
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- 0.0468 |
- 0.1106 |
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-
-
- | (0.4, 0.6) |
- 0.0299 |
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- 0.0374 |
- 0.0374 |
- 0.1014 |
- 0.0805 |
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-
-
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- 0.0872 |
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-
-
- | (0.5, 0.5) |
- 0.0318 |
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- 0.0335 |
- 0.0335 |
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-
-
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- 0.0299 |
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-
-
- | (0.6, 0.4) |
- 0.0277 |
- 0.0262 |
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- 0.0293 |
- 0.0293 |
- 0.0534 |
- 0.0361 |
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-
-
- | (0.65, 0.35) |
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- 0.0479 |
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-
-
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-
- | (0.75, 0.25) |
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-
-
- | (0.8, 0.2) |
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-
-
- | (0.85, 0.15) |
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-
-
- | (0.9, 0.1) |
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-
-
- | (0.95, 0.05) |
- 0.0182 |
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-
-
- | (1.0, 0.0) |
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- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0044 |
- 0.0093 |
- 0.0478 |
- 0.0268 |
- 0.0268 |
-
-
- | (0.05, 0.95) |
- 0.0213 |
- 0.0224 |
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-
-
- | (0.1, 0.9) |
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-
-
- | (0.15, 0.85) |
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-
-
- | (0.2, 0.8) |
- 0.0274 |
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- 0.0544 |
- 0.0298 |
- 0.0298 |
-
-
- | (0.25, 0.75) |
- 0.0216 |
- 0.0224 |
- 0.0490 |
- 0.0300 |
- 0.0300 |
-
-
- | (0.3, 0.7) |
- 0.0246 |
- 0.0282 |
- 0.0512 |
- 0.0306 |
- 0.0306 |
-
-
- | (0.35, 0.65) |
- 0.0226 |
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- 0.0536 |
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- 0.0336 |
-
-
- | (0.4, 0.6) |
- 0.0253 |
- 0.0258 |
- 0.0556 |
- 0.0282 |
- 0.0282 |
-
-
- | (0.45, 0.55) |
- 0.0313 |
- 0.0294 |
- 0.0538 |
- 0.0348 |
- 0.0348 |
-
-
- | (0.5, 0.5) |
- 0.0328 |
- 0.0354 |
- 0.0539 |
- 0.0331 |
- 0.0331 |
-
-
- | (0.55, 0.45) |
- 0.0378 |
- 0.0365 |
- 0.0504 |
- 0.0353 |
- 0.0353 |
-
-
- | (0.6, 0.4) |
- 0.0348 |
- 0.0337 |
- 0.0549 |
- 0.0374 |
- 0.0374 |
-
-
- | (0.65, 0.35) |
- 0.0432 |
- 0.0481 |
- 0.0656 |
- 0.0428 |
- 0.0428 |
-
-
- | (0.7, 0.3) |
- 0.0548 |
- 0.0488 |
- 0.0585 |
- 0.0446 |
- 0.0446 |
-
-
- | (0.75, 0.25) |
- 0.0569 |
- 0.0535 |
- 0.0633 |
- 0.0547 |
- 0.0547 |
-
-
- | (0.8, 0.2) |
- 0.0767 |
- 0.0770 |
- 0.0743 |
- 0.0576 |
- 0.0576 |
-
-
- | (0.85, 0.15) |
- 0.0867 |
- 0.0781 |
- 0.0843 |
- 0.0726 |
- 0.0726 |
-
-
- | (0.9, 0.1) |
- 0.1097 |
- 0.1000 |
- 0.0942 |
- 0.0807 |
- 0.0807 |
-
-
- | (0.95, 0.05) |
- 0.1811 |
- 0.1514 |
- 0.1311 |
- 0.1193 |
- 0.1193 |
-
-
- | (1.0, 0.0) |
- 0.0363 |
- 0.0363 |
- 0.9218 |
- 0.1003 |
- 0.1003 |
-
-
-
-
-target: C151
-train: [0.89778815 0.10221185]
-validation: [0.89779698 0.10220302]
-evaluate_binary: 355.746s
-evaluate_multiclass: 136.969s
-kfcv: 195.146s
-atc_mc: 193.365s
-atc_ne: 187.934s
-doc_feat: 73.112s
-rca_score: 1235.567s
-rca_star_score: 1236.092s
-tot: 1294.815s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0003 |
- 0.0108 |
- 0.2236 |
- 0.0827 |
- 0.0827 |
- 0.2239 |
- 0.6096 |
- 0.5989 |
-
-
- | (0.05, 0.95) |
- 0.0465 |
- 0.0475 |
- 0.2216 |
- 0.0861 |
- 0.0861 |
- 0.2220 |
- 0.5229 |
- 0.5149 |
-
-
- | (0.1, 0.9) |
- 0.0567 |
- 0.0587 |
- 0.2062 |
- 0.0719 |
- 0.0719 |
- 0.2066 |
- 0.4247 |
- 0.4188 |
-
-
- | (0.15, 0.85) |
- 0.0444 |
- 0.0468 |
- 0.1846 |
- 0.0671 |
- 0.0671 |
- 0.1851 |
- 0.2919 |
- 0.2922 |
-
-
- | (0.2, 0.8) |
- 0.0453 |
- 0.0458 |
- 0.1784 |
- 0.0681 |
- 0.0681 |
- 0.1790 |
- 0.1858 |
- 0.1927 |
-
-
- | (0.25, 0.75) |
- 0.0335 |
- 0.0402 |
- 0.1652 |
- 0.0624 |
- 0.0624 |
- 0.1658 |
- 0.1830 |
- 0.1919 |
-
-
- | (0.3, 0.7) |
- 0.0304 |
- 0.0320 |
- 0.1517 |
- 0.0561 |
- 0.0561 |
- 0.1524 |
- 0.1600 |
- 0.1702 |
-
-
- | (0.35, 0.65) |
- 0.0278 |
- 0.0333 |
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- | (0.7, 0.3) |
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- | (0.8, 0.2) |
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- | (0.85, 0.15) |
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- | (0.9, 0.1) |
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-
-target: C1511
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-kfcv: 102.539s
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-atc_ne: 92.903s
-doc_feat: 78.631s
-rca_score: 1097.941s
-rca_star_score: 1093.801s
-tot: 1139.243s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
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- doc_feat |
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-
-
-
-
- | (0.0, 1.0) |
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-
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-
- | (0.55, 0.45) |
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-
- | (0.6, 0.4) |
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- 0.1324 |
-
-
- | (0.65, 0.35) |
- 0.0221 |
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- 0.4546 |
- 0.1451 |
- 0.1451 |
-
-
- | (0.7, 0.3) |
- 0.0222 |
- 0.1914 |
- 0.4608 |
- 0.1460 |
- 0.1460 |
-
-
- | (0.75, 0.25) |
- 0.0326 |
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- 0.4585 |
- 0.1449 |
- 0.1449 |
-
-
- | (0.8, 0.2) |
- 0.0318 |
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- 0.4688 |
- 0.1652 |
- 0.1652 |
-
-
- | (0.85, 0.15) |
- 0.0457 |
- 0.1769 |
- 0.4617 |
- 0.1827 |
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-
-
- | (0.9, 0.1) |
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- 0.1641 |
- 0.1641 |
-
-
- | (0.95, 0.05) |
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-
-
- | (1.0, 0.0) |
- 0.0399 |
- 0.0422 |
- 0.6605 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: C152
-train: [0.91662347 0.08337653]
-validation: [0.91663067 0.08336933]
-evaluate_binary: 225.296s
-evaluate_multiclass: 165.847s
-kfcv: 126.786s
-atc_mc: 102.362s
-atc_ne: 91.713s
-doc_feat: 74.154s
-rca_score: 1219.516s
-rca_star_score: 1213.375s
-tot: 1270.692s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0005 |
- 0.0153 |
- 0.4699 |
- 0.1758 |
- 0.1758 |
- 0.4709 |
- 0.4878 |
- 0.5104 |
-
-
- | (0.05, 0.95) |
- 0.0517 |
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- 0.4323 |
- 0.1531 |
- 0.1531 |
- 0.4333 |
- 0.4561 |
- 0.4786 |
-
-
- | (0.1, 0.9) |
- 0.0818 |
- 0.0707 |
- 0.4037 |
- 0.1357 |
- 0.1357 |
- 0.4048 |
- 0.4274 |
- 0.4502 |
-
-
- | (0.15, 0.85) |
- 0.0880 |
- 0.0714 |
- 0.3916 |
- 0.1426 |
- 0.1426 |
- 0.3928 |
- 0.4136 |
- 0.4363 |
-
-
- | (0.2, 0.8) |
- 0.0780 |
- 0.0695 |
- 0.3625 |
- 0.1373 |
- 0.1373 |
- 0.3639 |
- 0.3851 |
- 0.4076 |
-
-
- | (0.25, 0.75) |
- 0.0693 |
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- 0.3312 |
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-
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-
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-
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-
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- 0.0440 |
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- 0.0853 |
-
-
- | (0.7, 0.3) |
- 0.0425 |
- 0.0516 |
- 0.1310 |
- 0.0810 |
- 0.0810 |
-
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- | (0.75, 0.25) |
- 0.0714 |
- 0.0718 |
- 0.1410 |
- 0.0910 |
- 0.0910 |
-
-
- | (0.8, 0.2) |
- 0.0772 |
- 0.0780 |
- 0.1511 |
- 0.1024 |
- 0.1024 |
-
-
- | (0.85, 0.15) |
- 0.0975 |
- 0.1035 |
- 0.1539 |
- 0.1219 |
- 0.1219 |
-
-
- | (0.9, 0.1) |
- 0.1470 |
- 0.1368 |
- 0.1694 |
- 0.1688 |
- 0.1688 |
-
-
- | (0.95, 0.05) |
- 0.2420 |
- 0.2045 |
- 0.2175 |
- 0.2185 |
- 0.2185 |
-
-
- | (1.0, 0.0) |
- 0.1206 |
- 0.0775 |
- 0.7803 |
- 0.0245 |
- 0.0245 |
-
-
-
-
-target: C17
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-validation: [0.94937365 0.05062635]
-evaluate_binary: 398.040s
-evaluate_multiclass: 149.938s
-kfcv: 165.629s
-atc_mc: 170.907s
-atc_ne: 103.307s
-doc_feat: 77.863s
-rca_score: 1203.842s
-rca_star_score: 1177.692s
-tot: 1248.888s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.1162 |
- 0.0588 |
- 0.6563 |
- 0.1936 |
- 0.1936 |
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- 0.6763 |
- 0.6893 |
-
-
- | (0.05, 0.95) |
- 0.1455 |
- 0.1297 |
- 0.6218 |
- 0.1786 |
- 0.1786 |
- 0.6225 |
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- 0.6542 |
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-
- | (0.1, 0.9) |
- 0.1821 |
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-
- | (0.15, 0.85) |
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- | (0.2, 0.8) |
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- | (0.35, 0.65) |
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-
- | (0.45, 0.55) |
- 0.2190 |
- 0.1878 |
- 0.2667 |
- 0.2183 |
- 0.2183 |
-
-
- | (0.5, 0.5) |
- 0.2100 |
- 0.1682 |
- 0.2673 |
- 0.2279 |
- 0.2279 |
-
-
- | (0.55, 0.45) |
- 0.1942 |
- 0.1849 |
- 0.2671 |
- 0.2253 |
- 0.2253 |
-
-
- | (0.6, 0.4) |
- 0.1733 |
- 0.1825 |
- 0.2581 |
- 0.2526 |
- 0.2526 |
-
-
- | (0.65, 0.35) |
- 0.1950 |
- 0.1793 |
- 0.2707 |
- 0.2424 |
- 0.2424 |
-
-
- | (0.7, 0.3) |
- 0.1907 |
- 0.1685 |
- 0.2484 |
- 0.2353 |
- 0.2353 |
-
-
- | (0.75, 0.25) |
- 0.1923 |
- 0.1787 |
- 0.2640 |
- 0.2427 |
- 0.2427 |
-
-
- | (0.8, 0.2) |
- 0.1929 |
- 0.1678 |
- 0.2706 |
- 0.2505 |
- 0.2505 |
-
-
- | (0.85, 0.15) |
- 0.2010 |
- 0.1825 |
- 0.2819 |
- 0.2513 |
- 0.2513 |
-
-
- | (0.9, 0.1) |
- 0.2261 |
- 0.1853 |
- 0.2750 |
- 0.2727 |
- 0.2727 |
-
-
- | (0.95, 0.05) |
- 0.2660 |
- 0.2221 |
- 0.2764 |
- 0.3408 |
- 0.3408 |
-
-
- | (1.0, 0.0) |
- 0.0684 |
- 0.0535 |
- 0.7291 |
- 0.0100 |
- 0.0100 |
-
-
-
-
-target: C172
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-validation: [0.98764579 0.01235421]
-evaluate_binary: 369.199s
-evaluate_multiclass: 215.109s
-kfcv: 103.301s
-atc_mc: 107.211s
-atc_ne: 167.924s
-doc_feat: 135.162s
-rca_score: 1176.166s
-rca_star_score: 1152.207s
-tot: 1217.302s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.3096 |
- 0.0555 |
- 0.6820 |
- 0.2176 |
- 0.2176 |
- 0.6796 |
- 0.6874 |
- 0.6923 |
-
-
- | (0.05, 0.95) |
- 0.3491 |
- 0.1131 |
- 0.6422 |
- 0.1993 |
- 0.1993 |
- 0.6399 |
- 0.6475 |
- 0.6525 |
-
-
- | (0.1, 0.9) |
- 0.3785 |
- 0.1724 |
- 0.6116 |
- 0.1955 |
- 0.1955 |
- 0.6094 |
- 0.6169 |
- 0.6218 |
-
-
- | (0.15, 0.85) |
- 0.4072 |
- 0.2255 |
- 0.5823 |
- 0.1957 |
- 0.1957 |
- 0.5802 |
- 0.5873 |
- 0.5922 |
-
-
- | (0.2, 0.8) |
- 0.4481 |
- 0.2891 |
- 0.5435 |
- 0.1771 |
- 0.1771 |
- 0.5415 |
- 0.5485 |
- 0.5533 |
-
-
- | (0.25, 0.75) |
- 0.4769 |
- 0.3674 |
- 0.5097 |
- 0.1687 |
- 0.1687 |
- 0.5078 |
- 0.5145 |
- 0.5193 |
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-
- | (0.3, 0.7) |
- 0.5156 |
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- 0.4790 |
- 0.4838 |
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-
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-
- | (0.4, 0.6) |
- 0.5748 |
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-
- | (0.45, 0.55) |
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-
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- 0.3388 |
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-
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- 0.5763 |
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-
- | (0.6, 0.4) |
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- 0.2725 |
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-
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-
- | (0.7, 0.3) |
- 0.3819 |
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-
- | (0.75, 0.25) |
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-
- | (0.85, 0.15) |
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-
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- | (1.0, 0.0) |
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-
-
-
-
-
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-
- |
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-
-
-
-
- | (0.0, 1.0) |
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-
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- | (0.4, 0.6) |
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-
-
- | (0.45, 0.55) |
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-
-
- | (0.5, 0.5) |
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- 0.3128 |
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- 0.4299 |
-
-
- | (0.55, 0.45) |
- 0.4440 |
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- 0.4143 |
- 0.4143 |
-
-
- | (0.6, 0.4) |
- 0.4536 |
- 0.4554 |
- 0.3215 |
- 0.4122 |
- 0.4122 |
-
-
- | (0.65, 0.35) |
- 0.4428 |
- 0.4429 |
- 0.3252 |
- 0.4079 |
- 0.4079 |
-
-
- | (0.7, 0.3) |
- 0.4626 |
- 0.4518 |
- 0.3110 |
- 0.4156 |
- 0.4156 |
-
-
- | (0.75, 0.25) |
- 0.4703 |
- 0.4547 |
- 0.2965 |
- 0.4391 |
- 0.4391 |
-
-
- | (0.8, 0.2) |
- 0.3880 |
- 0.3981 |
- 0.3409 |
- 0.3975 |
- 0.3975 |
-
-
- | (0.85, 0.15) |
- 0.4300 |
- 0.4058 |
- 0.3227 |
- 0.4217 |
- 0.4217 |
-
-
- | (0.9, 0.1) |
- 0.4235 |
- 0.4052 |
- 0.3121 |
- 0.4473 |
- 0.4473 |
-
-
- | (0.95, 0.05) |
- 0.3325 |
- 0.2850 |
- 0.4158 |
- 0.3516 |
- 0.3516 |
-
-
- | (1.0, 0.0) |
- 0.0100 |
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- 0.7895 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: C18
-train: [0.9368412 0.0631588]
-validation: [0.93684665 0.06315335]
-evaluate_binary: 335.349s
-evaluate_multiclass: 166.267s
-kfcv: 103.911s
-atc_mc: 97.746s
-atc_ne: 91.184s
-doc_feat: 75.425s
-rca_score: 1144.163s
-rca_star_score: 1141.640s
-tot: 1192.245s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0121 |
- 0.0514 |
- 0.6302 |
- 0.1223 |
- 0.1223 |
- 0.6307 |
- 0.6571 |
- 0.6765 |
-
-
- | (0.05, 0.95) |
- 0.0619 |
- 0.0985 |
- 0.6004 |
- 0.1230 |
- 0.1230 |
- 0.6010 |
- 0.6272 |
- 0.6466 |
-
-
- | (0.1, 0.9) |
- 0.0980 |
- 0.1197 |
- 0.5645 |
- 0.1110 |
- 0.1110 |
- 0.5652 |
- 0.5913 |
- 0.6108 |
-
-
- | (0.15, 0.85) |
- 0.0996 |
- 0.1222 |
- 0.5310 |
- 0.1082 |
- 0.1082 |
- 0.5319 |
- 0.5578 |
- 0.5772 |
-
-
- | (0.2, 0.8) |
- 0.0974 |
- 0.1109 |
- 0.4996 |
- 0.0979 |
- 0.0979 |
- 0.5006 |
- 0.5264 |
- 0.5458 |
-
-
- | (0.25, 0.75) |
- 0.0926 |
- 0.1129 |
- 0.4642 |
- 0.0916 |
- 0.0916 |
- 0.4653 |
- 0.4910 |
- 0.5104 |
-
-
- | (0.3, 0.7) |
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- |
- bin |
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- atc_mc |
- atc_ne |
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- | (0.0, 1.0) |
- 0.0156 |
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- 0.2175 |
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- 0.0583 |
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- | (0.45, 0.55) |
- 0.0627 |
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- 0.2260 |
- 0.2260 |
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- | (0.5, 0.5) |
- 0.0737 |
- 0.1209 |
- 0.2314 |
- 0.2148 |
- 0.2148 |
-
-
- | (0.55, 0.45) |
- 0.0655 |
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- 0.2250 |
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- 0.1986 |
-
-
- | (0.6, 0.4) |
- 0.0774 |
- 0.1057 |
- 0.2263 |
- 0.2182 |
- 0.2182 |
-
-
- | (0.65, 0.35) |
- 0.0824 |
- 0.1143 |
- 0.2287 |
- 0.2177 |
- 0.2177 |
-
-
- | (0.7, 0.3) |
- 0.0645 |
- 0.1457 |
- 0.2355 |
- 0.2328 |
- 0.2328 |
-
-
- | (0.75, 0.25) |
- 0.0695 |
- 0.1415 |
- 0.2268 |
- 0.2299 |
- 0.2299 |
-
-
- | (0.8, 0.2) |
- 0.0932 |
- 0.1654 |
- 0.2381 |
- 0.2437 |
- 0.2437 |
-
-
- | (0.85, 0.15) |
- 0.1328 |
- 0.1778 |
- 0.2285 |
- 0.2642 |
- 0.2642 |
-
-
- | (0.9, 0.1) |
- 0.1340 |
- 0.1642 |
- 0.2949 |
- 0.2280 |
- 0.2280 |
-
-
- | (0.95, 0.05) |
- 0.2025 |
- 0.2279 |
- 0.2915 |
- 0.2769 |
- 0.2769 |
-
-
- | (1.0, 0.0) |
- 0.0847 |
- 0.1003 |
- 0.7047 |
- 0.0267 |
- 0.0267 |
-
-
-
-
-target: C181
-train: [0.94798687 0.05201313]
-validation: [0.94790497 0.05209503]
-evaluate_binary: 381.404s
-evaluate_multiclass: 222.049s
-kfcv: 197.485s
-atc_mc: 198.730s
-atc_ne: 199.850s
-doc_feat: 79.764s
-rca_score: 1126.500s
-rca_star_score: 1125.388s
-tot: 1178.360s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0325 |
- 0.0483 |
- 0.7090 |
- 0.1760 |
- 0.1760 |
- 0.7081 |
- 0.7381 |
- 0.7500 |
-
-
- | (0.05, 0.95) |
- 0.0863 |
- 0.0969 |
- 0.6584 |
- 0.1531 |
- 0.1531 |
- 0.6576 |
- 0.6875 |
- 0.6994 |
-
-
- | (0.1, 0.9) |
- 0.1419 |
- 0.1447 |
- 0.6332 |
- 0.1547 |
- 0.1547 |
- 0.6325 |
- 0.6623 |
- 0.6742 |
-
-
- | (0.15, 0.85) |
- 0.1847 |
- 0.1538 |
- 0.5945 |
- 0.1396 |
- 0.1396 |
- 0.5939 |
- 0.6236 |
- 0.6355 |
-
-
- | (0.2, 0.8) |
- 0.1668 |
- 0.1507 |
- 0.5563 |
- 0.1381 |
- 0.1381 |
- 0.5559 |
- 0.5854 |
- 0.5973 |
-
-
- | (0.25, 0.75) |
- 0.1496 |
- 0.1405 |
- 0.5189 |
- 0.1257 |
- 0.1257 |
- 0.5186 |
- 0.5480 |
- 0.5599 |
-
-
- | (0.3, 0.7) |
- 0.1292 |
- 0.1250 |
- 0.4858 |
- 0.1238 |
- 0.1238 |
- 0.4856 |
- 0.5149 |
- 0.5268 |
-
-
- | (0.35, 0.65) |
- 0.1182 |
- 0.1109 |
- 0.4399 |
- 0.1068 |
- 0.1068 |
- 0.4398 |
- 0.4690 |
- 0.4809 |
-
-
- | (0.4, 0.6) |
- 0.1200 |
- 0.1035 |
- 0.4057 |
- 0.0983 |
- 0.0983 |
- 0.4057 |
- 0.4348 |
- 0.4467 |
-
-
- | (0.45, 0.55) |
- 0.1049 |
- 0.0955 |
- 0.3698 |
- 0.0934 |
- 0.0934 |
- 0.3700 |
- 0.3989 |
- 0.4108 |
-
-
- | (0.5, 0.5) |
- 0.0924 |
- 0.0796 |
- 0.3361 |
- 0.0913 |
- 0.0913 |
- 0.3364 |
- 0.3652 |
- 0.3771 |
-
-
- | (0.55, 0.45) |
- 0.0856 |
- 0.0709 |
- 0.3002 |
- 0.0838 |
- 0.0838 |
- 0.3006 |
- 0.3293 |
- 0.3412 |
-
-
- | (0.6, 0.4) |
- 0.0803 |
- 0.0683 |
- 0.2595 |
- 0.0698 |
- 0.0698 |
- 0.2600 |
- 0.2886 |
- 0.3005 |
-
-
- | (0.65, 0.35) |
- 0.0726 |
- 0.0594 |
- 0.2211 |
- 0.0558 |
- 0.0558 |
- 0.2217 |
- 0.2502 |
- 0.2621 |
-
-
- | (0.7, 0.3) |
- 0.0534 |
- 0.0472 |
- 0.1861 |
- 0.0545 |
- 0.0545 |
- 0.1869 |
- 0.2152 |
- 0.2271 |
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-
- | (0.75, 0.25) |
- 0.0470 |
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- 0.1451 |
- 0.0388 |
- 0.0388 |
- 0.1460 |
- 0.1742 |
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- | (0.8, 0.2) |
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- 0.1140 |
- 0.0366 |
- 0.0366 |
- 0.1150 |
- 0.1431 |
- 0.1550 |
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-
- | (0.85, 0.15) |
- 0.0302 |
- 0.0278 |
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- 0.0333 |
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- NaN |
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- | (1.0, 0.0) |
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- NaN |
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-
-
-
-
-
- |
- bin |
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- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0493 |
- 0.0660 |
- 0.2735 |
- 0.2224 |
- 0.2224 |
-
-
- | (0.05, 0.95) |
- 0.0714 |
- 0.0825 |
- 0.2560 |
- 0.2430 |
- 0.2430 |
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-
- | (0.1, 0.9) |
- 0.1006 |
- 0.1052 |
- 0.2726 |
- 0.2338 |
- 0.2338 |
-
-
- | (0.15, 0.85) |
- 0.1411 |
- 0.1092 |
- 0.2704 |
- 0.2370 |
- 0.2370 |
-
-
- | (0.2, 0.8) |
- 0.1247 |
- 0.1146 |
- 0.2698 |
- 0.2388 |
- 0.2388 |
-
-
- | (0.25, 0.75) |
- 0.1129 |
- 0.1124 |
- 0.2693 |
- 0.2299 |
- 0.2299 |
-
-
- | (0.3, 0.7) |
- 0.0982 |
- 0.1064 |
- 0.2785 |
- 0.2268 |
- 0.2268 |
-
-
- | (0.35, 0.65) |
- 0.0981 |
- 0.0995 |
- 0.2611 |
- 0.2153 |
- 0.2153 |
-
-
- | (0.4, 0.6) |
- 0.1301 |
- 0.1044 |
- 0.2676 |
- 0.2413 |
- 0.2413 |
-
-
- | (0.45, 0.55) |
- 0.1170 |
- 0.1030 |
- 0.2700 |
- 0.2219 |
- 0.2219 |
-
-
- | (0.5, 0.5) |
- 0.1240 |
- 0.1038 |
- 0.2803 |
- 0.2124 |
- 0.2124 |
-
-
- | (0.55, 0.45) |
- 0.1378 |
- 0.1075 |
- 0.2849 |
- 0.2180 |
- 0.2180 |
-
-
- | (0.6, 0.4) |
- 0.1560 |
- 0.1292 |
- 0.2778 |
- 0.2365 |
- 0.2365 |
-
-
- | (0.65, 0.35) |
- 0.1583 |
- 0.1120 |
- 0.2726 |
- 0.2423 |
- 0.2423 |
-
-
- | (0.7, 0.3) |
- 0.1267 |
- 0.1095 |
- 0.2850 |
- 0.2335 |
- 0.2335 |
-
-
- | (0.75, 0.25) |
- 0.1268 |
- 0.1289 |
- 0.2691 |
- 0.2349 |
- 0.2349 |
-
-
- | (0.8, 0.2) |
- 0.1666 |
- 0.1541 |
- 0.3075 |
- 0.2236 |
- 0.2236 |
-
-
- | (0.85, 0.15) |
- 0.1435 |
- 0.1399 |
- 0.3107 |
- 0.2485 |
- 0.2485 |
-
-
- | (0.9, 0.1) |
- 0.2017 |
- 0.1681 |
- 0.2914 |
- 0.2582 |
- 0.2582 |
-
-
- | (0.95, 0.05) |
- 0.2070 |
- 0.1951 |
- 0.3503 |
- 0.2298 |
- 0.2298 |
-
-
- | (1.0, 0.0) |
- 0.0364 |
- 0.0794 |
- 0.6713 |
- 0.0100 |
- 0.0100 |
-
-
-
-
-target: C21
-train: [0.96578538 0.03421462]
-validation: [0.96570194 0.03429806]
-evaluate_binary: 311.430s
-evaluate_multiclass: 127.753s
-kfcv: 169.599s
-atc_mc: 171.895s
-atc_ne: 99.774s
-doc_feat: 132.229s
-rca_score: 928.435s
-rca_star_score: 903.426s
-tot: 975.778s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0424 |
- 0.0492 |
- 0.9072 |
- 0.4914 |
- 0.4914 |
- 0.9070 |
- 0.9379 |
- 0.9402 |
-
-
- | (0.05, 0.95) |
- 0.0890 |
- 0.0948 |
- 0.8638 |
- 0.4779 |
- 0.4779 |
- 0.8637 |
- 0.8945 |
- 0.8968 |
-
-
- | (0.1, 0.9) |
- 0.1222 |
- 0.1388 |
- 0.8194 |
- 0.4604 |
- 0.4604 |
- 0.8193 |
- 0.8501 |
- 0.8524 |
-
-
- | (0.15, 0.85) |
- 0.1817 |
- 0.1739 |
- 0.7708 |
- 0.4230 |
- 0.4230 |
- 0.7708 |
- 0.8015 |
- 0.8038 |
-
-
- | (0.2, 0.8) |
- 0.2163 |
- 0.1888 |
- 0.7203 |
- 0.4059 |
- 0.4059 |
- 0.7204 |
- NaN |
- NaN |
-
-
- | (0.25, 0.75) |
- 0.2301 |
- 0.1784 |
- 0.6752 |
- 0.3696 |
- 0.3696 |
- 0.6753 |
- NaN |
- NaN |
-
-
- | (0.3, 0.7) |
- 0.2284 |
- 0.1706 |
- 0.6278 |
- 0.3453 |
- 0.3453 |
- 0.6280 |
- 0.6585 |
- 0.6608 |
-
-
- | (0.35, 0.65) |
- 0.1928 |
- 0.1427 |
- 0.5795 |
- 0.3232 |
- 0.3232 |
- 0.5797 |
- NaN |
- NaN |
-
-
- | (0.4, 0.6) |
- 0.1619 |
- 0.1168 |
- 0.5346 |
- 0.3000 |
- 0.3000 |
- 0.5349 |
- NaN |
- NaN |
-
-
- | (0.45, 0.55) |
- 0.1625 |
- 0.1188 |
- 0.4839 |
- 0.2670 |
- 0.2670 |
- 0.4843 |
- NaN |
- NaN |
-
-
- | (0.5, 0.5) |
- 0.1408 |
- 0.1015 |
- 0.4380 |
- 0.2343 |
- 0.2343 |
- 0.4384 |
- NaN |
- NaN |
-
-
- | (0.55, 0.45) |
- 0.1077 |
- 0.0741 |
- 0.3937 |
- 0.2192 |
- 0.2192 |
- 0.3942 |
- NaN |
- NaN |
-
-
- | (0.6, 0.4) |
- 0.0949 |
- 0.0718 |
- 0.3457 |
- 0.1931 |
- 0.1931 |
- 0.3463 |
- NaN |
- NaN |
-
-
- | (0.65, 0.35) |
- 0.0664 |
- 0.0492 |
- 0.2980 |
- 0.1698 |
- 0.1698 |
- 0.2986 |
- NaN |
- NaN |
-
-
- | (0.7, 0.3) |
- 0.0617 |
- 0.0463 |
- 0.2509 |
- 0.1387 |
- 0.1387 |
- 0.2516 |
- NaN |
- NaN |
-
-
- | (0.75, 0.25) |
- 0.0529 |
- 0.0446 |
- 0.2023 |
- 0.1169 |
- 0.1169 |
- 0.2031 |
- NaN |
- NaN |
-
-
- | (0.8, 0.2) |
- 0.0440 |
- 0.0403 |
- 0.1564 |
- 0.0924 |
- 0.0924 |
- 0.1572 |
- NaN |
- NaN |
-
-
- | (0.85, 0.15) |
- 0.0414 |
- 0.0393 |
- 0.1070 |
- 0.0626 |
- 0.0626 |
- 0.1079 |
- NaN |
- NaN |
-
-
- | (0.9, 0.1) |
- 0.0314 |
- 0.0342 |
- 0.0620 |
- 0.0394 |
- 0.0394 |
- 0.0630 |
- NaN |
- NaN |
-
-
- | (0.95, 0.05) |
- 0.0271 |
- 0.0251 |
- 0.0149 |
- 0.0185 |
- 0.0185 |
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- NaN |
- NaN |
-
-
- | (1.0, 0.0) |
- 0.0066 |
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- 0.0142 |
- 0.0142 |
- 0.0316 |
- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0790 |
- 0.0915 |
- 0.4290 |
- 0.1109 |
- 0.1109 |
-
-
- | (0.05, 0.95) |
- 0.0784 |
- 0.0891 |
- 0.4355 |
- 0.1028 |
- 0.1028 |
-
-
- | (0.1, 0.9) |
- 0.0522 |
- 0.0884 |
- 0.4410 |
- 0.0992 |
- 0.0992 |
-
-
- | (0.15, 0.85) |
- 0.0785 |
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- 0.4387 |
- 0.1020 |
- 0.1020 |
-
-
- | (0.2, 0.8) |
- 0.0767 |
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- 0.1078 |
- 0.1078 |
-
-
- | (0.25, 0.75) |
- 0.0742 |
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- 0.1036 |
- 0.1036 |
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- 0.0731 |
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- 0.1077 |
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- 0.0632 |
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- 0.0991 |
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- | (0.45, 0.55) |
- 0.0810 |
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- 0.4286 |
- 0.1106 |
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- | (0.5, 0.5) |
- 0.0765 |
- 0.0920 |
- 0.4326 |
- 0.1057 |
- 0.1057 |
-
-
- | (0.55, 0.45) |
- 0.0588 |
- 0.0776 |
- 0.4436 |
- 0.0963 |
- 0.0963 |
-
-
- | (0.6, 0.4) |
- 0.0645 |
- 0.0837 |
- 0.4409 |
- 0.1006 |
- 0.1006 |
-
-
- | (0.65, 0.35) |
- 0.0670 |
- 0.0835 |
- 0.4390 |
- 0.1017 |
- 0.1017 |
-
-
- | (0.7, 0.3) |
- 0.0678 |
- 0.0796 |
- 0.4417 |
- 0.0968 |
- 0.0968 |
-
-
- | (0.75, 0.25) |
- 0.0744 |
- 0.0867 |
- 0.4331 |
- 0.1063 |
- 0.1063 |
-
-
- | (0.8, 0.2) |
- 0.0764 |
- 0.0747 |
- 0.4439 |
- 0.0968 |
- 0.0968 |
-
-
- | (0.85, 0.15) |
- 0.0806 |
- 0.0903 |
- 0.4193 |
- 0.1214 |
- 0.1214 |
-
-
- | (0.9, 0.1) |
- 0.0688 |
- 0.0793 |
- 0.4515 |
- 0.0892 |
- 0.0892 |
-
-
- | (0.95, 0.05) |
- 0.0553 |
- 0.0714 |
- 0.4621 |
- 0.0846 |
- 0.0846 |
-
-
- | (1.0, 0.0) |
- 0.0097 |
- 0.0103 |
- 0.5407 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: C24
-train: [0.96016935 0.03983065]
-validation: [0.96017279 0.03982721]
-evaluate_binary: 341.390s
-evaluate_multiclass: 134.762s
-kfcv: 115.097s
-atc_mc: 166.466s
-atc_ne: 156.922s
-doc_feat: 127.605s
-rca_score: 1002.111s
-rca_star_score: 1016.135s
-tot: 1070.690s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0465 |
- 0.0483 |
- 0.8791 |
- 0.4200 |
- 0.4200 |
- 0.8782 |
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-
- | (0.05, 0.95) |
- 0.0927 |
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- 0.8313 |
- 0.3948 |
- 0.3948 |
- 0.8305 |
- 0.8640 |
- 0.8679 |
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-
- | (0.1, 0.9) |
- 0.1434 |
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- 0.7798 |
- 0.3744 |
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- 0.8125 |
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-
- | (0.15, 0.85) |
- 0.1894 |
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- | (0.2, 0.8) |
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- 0.6955 |
- 0.3308 |
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- 0.6949 |
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- | (0.25, 0.75) |
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- 0.1901 |
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- | (0.4, 0.6) |
- 0.1490 |
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- | (1.0, 0.0) |
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- 0.0355 |
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- NaN |
-
-
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-
-
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-
- |
- bin |
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- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0844 |
- 0.0868 |
- 0.4205 |
- 0.1451 |
- 0.1451 |
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-
- | (0.05, 0.95) |
- 0.0859 |
- 0.0909 |
- 0.4167 |
- 0.1510 |
- 0.1510 |
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- | (0.1, 0.9) |
- 0.0946 |
- 0.0998 |
- 0.4062 |
- 0.1593 |
- 0.1593 |
-
-
- | (0.15, 0.85) |
- 0.1019 |
- 0.1112 |
- 0.4000 |
- 0.1662 |
- 0.1662 |
-
-
- | (0.2, 0.8) |
- 0.0859 |
- 0.1090 |
- 0.4197 |
- 0.1484 |
- 0.1484 |
-
-
- | (0.25, 0.75) |
- 0.1053 |
- 0.1127 |
- 0.3996 |
- 0.1629 |
- 0.1629 |
-
-
- | (0.3, 0.7) |
- 0.0930 |
- 0.1063 |
- 0.4118 |
- 0.1549 |
- 0.1549 |
-
-
- | (0.35, 0.65) |
- 0.0988 |
- 0.1069 |
- 0.4093 |
- 0.1554 |
- 0.1554 |
-
-
- | (0.4, 0.6) |
- 0.0991 |
- 0.0989 |
- 0.4132 |
- 0.1484 |
- 0.1484 |
-
-
- | (0.45, 0.55) |
- 0.1127 |
- 0.1160 |
- 0.4000 |
- 0.1687 |
- 0.1687 |
-
-
- | (0.5, 0.5) |
- 0.0940 |
- 0.0946 |
- 0.4113 |
- 0.1528 |
- 0.1528 |
-
-
- | (0.55, 0.45) |
- 0.0803 |
- 0.0967 |
- 0.4075 |
- 0.1614 |
- 0.1614 |
-
-
- | (0.6, 0.4) |
- 0.1085 |
- 0.1072 |
- 0.4071 |
- 0.1603 |
- 0.1603 |
-
-
- | (0.65, 0.35) |
- 0.0847 |
- 0.1035 |
- 0.4113 |
- 0.1552 |
- 0.1552 |
-
-
- | (0.7, 0.3) |
- 0.0859 |
- 0.0889 |
- 0.4098 |
- 0.1575 |
- 0.1575 |
-
-
- | (0.75, 0.25) |
- 0.0927 |
- 0.1003 |
- 0.4153 |
- 0.1535 |
- 0.1535 |
-
-
- | (0.8, 0.2) |
- 0.0953 |
- 0.1051 |
- 0.4006 |
- 0.1606 |
- 0.1606 |
-
-
- | (0.85, 0.15) |
- 0.0957 |
- 0.1026 |
- 0.4118 |
- 0.1563 |
- 0.1563 |
-
-
- | (0.9, 0.1) |
- 0.1292 |
- 0.1486 |
- 0.3944 |
- 0.1756 |
- 0.1756 |
-
-
- | (0.95, 0.05) |
- 0.1311 |
- 0.1574 |
- 0.4179 |
- 0.1544 |
- 0.1544 |
-
-
- | (1.0, 0.0) |
- 0.0001 |
- 0.0320 |
- 0.5748 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: C31
-train: [0.95429411 0.04570589]
-validation: [0.95429806 0.04570194]
-evaluate_binary: 242.965s
-evaluate_multiclass: 161.716s
-kfcv: 142.016s
-atc_mc: 101.146s
-atc_ne: 92.376s
-doc_feat: 76.202s
-rca_score: 834.193s
-rca_star_score: 832.758s
-tot: 884.843s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0365 |
- 0.0378 |
- 0.9167 |
- 0.5280 |
- 0.5280 |
- 0.9160 |
- 0.9552 |
- 0.9591 |
-
-
- | (0.05, 0.95) |
- 0.0891 |
- 0.0891 |
- 0.8674 |
- 0.5052 |
- 0.5052 |
- 0.8668 |
- NaN |
- NaN |
-
-
- | (0.1, 0.9) |
- 0.1320 |
- 0.1322 |
- 0.8230 |
- 0.4735 |
- 0.4735 |
- 0.8225 |
- NaN |
- NaN |
-
-
- | (0.15, 0.85) |
- 0.1762 |
- 0.1713 |
- 0.7775 |
- 0.4506 |
- 0.4506 |
- 0.7770 |
- NaN |
- NaN |
-
-
- | (0.2, 0.8) |
- 0.2229 |
- 0.1975 |
- 0.7284 |
- 0.4166 |
- 0.4166 |
- 0.7280 |
- NaN |
- NaN |
-
-
- | (0.25, 0.75) |
- 0.2490 |
- 0.1889 |
- 0.6805 |
- 0.4011 |
- 0.4011 |
- 0.6802 |
- NaN |
- NaN |
-
-
- | (0.3, 0.7) |
- 0.2541 |
- 0.1879 |
- 0.6279 |
- 0.3506 |
- 0.3506 |
- 0.6276 |
- NaN |
- NaN |
-
-
- | (0.35, 0.65) |
- 0.2324 |
- 0.1645 |
- 0.5811 |
- 0.3347 |
- 0.3347 |
- 0.5809 |
- NaN |
- NaN |
-
-
- | (0.4, 0.6) |
- 0.2133 |
- 0.1533 |
- 0.5314 |
- 0.3060 |
- 0.3060 |
- 0.5313 |
- NaN |
- NaN |
-
-
- | (0.45, 0.55) |
- 0.1887 |
- 0.1317 |
- 0.4867 |
- 0.2859 |
- 0.2859 |
- 0.4866 |
- NaN |
- NaN |
-
-
- | (0.5, 0.5) |
- 0.1642 |
- 0.1148 |
- 0.4366 |
- 0.2592 |
- 0.2592 |
- 0.4366 |
- NaN |
- NaN |
-
-
- | (0.55, 0.45) |
- 0.1468 |
- 0.1010 |
- 0.3916 |
- 0.2293 |
- 0.2293 |
- 0.3917 |
- NaN |
- NaN |
-
-
- | (0.6, 0.4) |
- 0.1187 |
- 0.0832 |
- 0.3424 |
- 0.2001 |
- 0.2001 |
- 0.3425 |
- NaN |
- NaN |
-
-
- | (0.65, 0.35) |
- 0.0952 |
- 0.0644 |
- 0.2952 |
- 0.1761 |
- 0.1761 |
- 0.2954 |
- NaN |
- NaN |
-
-
- | (0.7, 0.3) |
- 0.0779 |
- 0.0564 |
- 0.2451 |
- 0.1452 |
- 0.1452 |
- 0.2454 |
- NaN |
- NaN |
-
-
- | (0.75, 0.25) |
- 0.0646 |
- 0.0503 |
- 0.1981 |
- 0.1177 |
- 0.1177 |
- 0.1984 |
- NaN |
- NaN |
-
-
- | (0.8, 0.2) |
- 0.0527 |
- 0.0453 |
- 0.1513 |
- 0.0943 |
- 0.0943 |
- 0.1517 |
- NaN |
- NaN |
-
-
- | (0.85, 0.15) |
- 0.0425 |
- 0.0372 |
- 0.1021 |
- 0.0625 |
- 0.0625 |
- 0.1026 |
- NaN |
- NaN |
-
-
- | (0.9, 0.1) |
- 0.0383 |
- 0.0368 |
- 0.0547 |
- 0.0358 |
- 0.0358 |
- 0.0552 |
- NaN |
- NaN |
-
-
- | (0.95, 0.05) |
- 0.0319 |
- 0.0292 |
- 0.0068 |
- 0.0162 |
- 0.0162 |
- 0.0072 |
- NaN |
- NaN |
-
-
- | (1.0, 0.0) |
- 0.0058 |
- 0.0045 |
- 0.0420 |
- 0.0168 |
- 0.0168 |
- 0.0413 |
- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0696 |
- 0.0719 |
- 0.4854 |
- 0.0748 |
- 0.0748 |
-
-
- | (0.05, 0.95) |
- 0.0784 |
- 0.0785 |
- 0.4830 |
- 0.0781 |
- 0.0781 |
-
-
- | (0.1, 0.9) |
- 0.0686 |
- 0.0707 |
- 0.4902 |
- 0.0684 |
- 0.0684 |
-
-
- | (0.15, 0.85) |
- 0.0609 |
- 0.0648 |
- 0.4958 |
- 0.0643 |
- 0.0643 |
-
-
- | (0.2, 0.8) |
- 0.0643 |
- 0.0684 |
- 0.4938 |
- 0.0670 |
- 0.0670 |
-
-
- | (0.25, 0.75) |
- 0.0645 |
- 0.0672 |
- 0.4943 |
- 0.0664 |
- 0.0664 |
-
-
- | (0.3, 0.7) |
- 0.0715 |
- 0.0770 |
- 0.4826 |
- 0.0782 |
- 0.0782 |
-
-
- | (0.35, 0.65) |
- 0.0722 |
- 0.0750 |
- 0.4856 |
- 0.0750 |
- 0.0750 |
-
-
- | (0.4, 0.6) |
- 0.0715 |
- 0.0775 |
- 0.4807 |
- 0.0785 |
- 0.0785 |
-
-
- | (0.45, 0.55) |
- 0.0615 |
- 0.0685 |
- 0.4911 |
- 0.0704 |
- 0.0704 |
-
-
- | (0.5, 0.5) |
- 0.0722 |
- 0.0758 |
- 0.4837 |
- 0.0787 |
- 0.0787 |
-
-
- | (0.55, 0.45) |
- 0.0618 |
- 0.0636 |
- 0.4954 |
- 0.0673 |
- 0.0673 |
-
-
- | (0.6, 0.4) |
- 0.0634 |
- 0.0663 |
- 0.4910 |
- 0.0700 |
- 0.0700 |
-
-
- | (0.65, 0.35) |
- 0.0554 |
- 0.0618 |
- 0.4955 |
- 0.0649 |
- 0.0649 |
-
-
- | (0.7, 0.3) |
- 0.0679 |
- 0.0693 |
- 0.4852 |
- 0.0777 |
- 0.0777 |
-
-
- | (0.75, 0.25) |
- 0.0563 |
- 0.0581 |
- 0.4915 |
- 0.0713 |
- 0.0713 |
-
-
- | (0.8, 0.2) |
- 0.0510 |
- 0.0528 |
- 0.5034 |
- 0.0601 |
- 0.0601 |
-
-
- | (0.85, 0.15) |
- 0.0601 |
- 0.0619 |
- 0.4965 |
- 0.0651 |
- 0.0651 |
-
-
- | (0.9, 0.1) |
- 0.0515 |
- 0.0578 |
- 0.5060 |
- 0.0575 |
- 0.0575 |
-
-
- | (0.95, 0.05) |
- 0.0769 |
- 0.0907 |
- 0.4911 |
- 0.0724 |
- 0.0724 |
-
-
- | (1.0, 0.0) |
- 0.0000 |
- 0.0099 |
- 0.5635 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: C42
-train: [0.98522551 0.01477449]
-validation: [0.98514039 0.01485961]
-evaluate_binary: 216.862s
-evaluate_multiclass: 148.154s
-kfcv: 142.768s
-atc_mc: 101.557s
-atc_ne: 93.067s
-doc_feat: 77.781s
-rca_score: 983.309s
-rca_star_score: 974.280s
-tot: 1025.959s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0000 |
- 0.0788 |
- 0.9071 |
- 0.3390 |
- 0.3390 |
- 0.9066 |
- 0.9188 |
- 0.9209 |
-
-
- | (0.05, 0.95) |
- 0.0500 |
- 0.1224 |
- 0.8635 |
- 0.3205 |
- 0.3205 |
- 0.8630 |
- 0.8752 |
- 0.8773 |
-
-
- | (0.1, 0.9) |
- 0.1000 |
- 0.1640 |
- 0.8220 |
- 0.3077 |
- 0.3077 |
- 0.8216 |
- 0.8337 |
- 0.8358 |
-
-
- | (0.15, 0.85) |
- 0.1499 |
- 0.2091 |
- 0.7768 |
- 0.2870 |
- 0.2870 |
- 0.7765 |
- 0.7885 |
- 0.7906 |
-
-
- | (0.2, 0.8) |
- 0.1999 |
- 0.2601 |
- 0.7254 |
- 0.2651 |
- 0.2651 |
- 0.7252 |
- 0.7371 |
- 0.7392 |
-
-
- | (0.25, 0.75) |
- 0.2498 |
- 0.3046 |
- 0.6770 |
- 0.2535 |
- 0.2535 |
- 0.6768 |
- NaN |
- NaN |
-
-
- | (0.3, 0.7) |
- 0.2995 |
- 0.3300 |
- 0.6312 |
- 0.2318 |
- 0.2318 |
- 0.6311 |
- NaN |
- NaN |
-
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-
-target: E12
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-atc_ne: 159.501s
-doc_feat: 79.566s
-rca_score: 940.772s
-rca_star_score: 955.992s
-tot: 1005.211s
-
-
-
-
- |
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- | (0.7, 0.3) |
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- | (0.75, 0.25) |
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- | (0.8, 0.2) |
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- | (0.85, 0.15) |
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- | (0.9, 0.1) |
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-
-
-
-target: E21
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-validation: [0.94574514 0.05425486]
-evaluate_binary: 339.478s
-evaluate_multiclass: 127.963s
-kfcv: 161.870s
-atc_mc: 171.427s
-atc_ne: 103.308s
-doc_feat: 77.827s
-rca_score: 1211.965s
-rca_star_score: 1184.838s
-tot: 1259.208s
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-
-
-
- |
- bin |
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- rca |
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-
-
-
- | (0.0, 1.0) |
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-
- | (0.05, 0.95) |
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-
- | (0.15, 0.85) |
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-validation: [0.98237581 0.01762419]
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-evaluate_multiclass: 123.957s
-kfcv: 112.571s
-atc_mc: 170.547s
-atc_ne: 167.429s
-doc_feat: 129.581s
-rca_score: 1011.800s
-rca_star_score: 1025.452s
-tot: 1076.046s
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- | (0.55, 0.45) |
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- 0.1557 |
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- | (0.65, 0.35) |
- 0.1487 |
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- 0.1481 |
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-
- | (0.7, 0.3) |
- 0.1490 |
- 0.1609 |
- 0.4366 |
- 0.1612 |
- 0.1612 |
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- | (0.75, 0.25) |
- 0.1558 |
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- 0.4281 |
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- | (0.85, 0.15) |
- 0.1484 |
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- | (0.9, 0.1) |
- 0.1491 |
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- | (0.95, 0.05) |
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- 0.0099 |
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- 0.0000 |
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-
-
-
-target: E212
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-validation: [0.96311015 0.03688985]
-evaluate_binary: 233.509s
-evaluate_multiclass: 178.371s
-kfcv: 145.769s
-atc_mc: 124.033s
-atc_ne: 91.719s
-doc_feat: 78.459s
-rca_score: 1204.775s
-rca_star_score: 1188.268s
-tot: 1247.499s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0010 |
- 0.0341 |
- 0.4860 |
- 0.1411 |
- 0.1411 |
- 0.4860 |
- 0.4993 |
- 0.5061 |
-
-
- | (0.05, 0.95) |
- 0.0525 |
- 0.0923 |
- 0.4539 |
- 0.1209 |
- 0.1209 |
- 0.4540 |
- 0.4680 |
- 0.4747 |
-
-
- | (0.1, 0.9) |
- 0.1010 |
- 0.1433 |
- 0.4379 |
- 0.1263 |
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- 0.4381 |
- 0.4504 |
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-
-
- | (0.15, 0.85) |
- 0.1482 |
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- 0.4097 |
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- 0.1114 |
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- 0.4215 |
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-
-
- | (0.2, 0.8) |
- 0.1706 |
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- 0.3810 |
- 0.1099 |
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-
- | (0.25, 0.75) |
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-
- |
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-
-
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-
-
- | (0.45, 0.55) |
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-
-
- | (0.5, 0.5) |
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-
-
- | (0.55, 0.45) |
- 0.0664 |
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- 0.1745 |
- 0.0897 |
- 0.0897 |
-
-
- | (0.6, 0.4) |
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- 0.0797 |
- 0.0797 |
-
-
- | (0.65, 0.35) |
- 0.0755 |
- 0.1035 |
- 0.1897 |
- 0.0900 |
- 0.0900 |
-
-
- | (0.7, 0.3) |
- 0.0701 |
- 0.0864 |
- 0.1931 |
- 0.0919 |
- 0.0919 |
-
-
- | (0.75, 0.25) |
- 0.0760 |
- 0.0957 |
- 0.1830 |
- 0.1043 |
- 0.1043 |
-
-
- | (0.8, 0.2) |
- 0.0816 |
- 0.0989 |
- 0.1833 |
- 0.1187 |
- 0.1187 |
-
-
- | (0.85, 0.15) |
- 0.0974 |
- 0.1087 |
- 0.1921 |
- 0.1385 |
- 0.1385 |
-
-
- | (0.9, 0.1) |
- 0.1292 |
- 0.1308 |
- 0.2095 |
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-
-
- | (0.95, 0.05) |
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-
-
- | (1.0, 0.0) |
- 0.0000 |
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- 0.0000 |
- 0.0000 |
-
-
-
-
-target: E41
-train: [0.98064628 0.01935372]
-validation: [0.98056156 0.01943844]
-evaluate_binary: 279.480s
-evaluate_multiclass: 130.254s
-kfcv: 167.427s
-atc_mc: 141.283s
-atc_ne: 169.435s
-doc_feat: 82.077s
-rca_score: 1007.269s
-rca_star_score: 1022.263s
-tot: 1072.119s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0000 |
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- 0.8822 |
- 0.2738 |
- 0.2738 |
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- 0.8962 |
- 0.8990 |
-
-
- | (0.05, 0.95) |
- 0.0500 |
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- 0.2700 |
- 0.2700 |
- 0.8374 |
- 0.8529 |
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-
-
- | (0.1, 0.9) |
- 0.0998 |
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- 0.2581 |
- 0.2581 |
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-
-
- | (0.15, 0.85) |
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- 0.2337 |
- 0.7477 |
- 0.7631 |
- 0.7659 |
-
-
- | (0.2, 0.8) |
- 0.1996 |
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- 0.7003 |
- 0.2210 |
- 0.2210 |
- 0.6990 |
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- 0.7171 |
-
-
- | (0.25, 0.75) |
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-
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-
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-
-target: E51
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-atc_ne: 106.609s
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-rca_score: 937.639s
-rca_star_score: 952.963s
-tot: 1000.226s
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-
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-
- | (0.7, 0.3) |
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-
-
-
-target: ECAT
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-evaluate_binary: 264.961s
-evaluate_multiclass: 139.511s
-kfcv: 164.571s
-atc_mc: 164.474s
-atc_ne: 104.597s
-doc_feat: 120.243s
-rca_score: 1226.111s
-rca_star_score: 1194.784s
-tot: 1281.006s
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-
-
-
- |
- bin |
- mul |
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- doc_feat |
- rca |
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-
-
-
-
- | (0.0, 1.0) |
- 0.0195 |
- 0.0263 |
- 0.4086 |
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-
-
- | (0.05, 0.95) |
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-
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-
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-
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- 0.0752 |
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-
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- 0.0825 |
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-
- | (0.7, 0.3) |
- 0.0738 |
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-
- | (0.8, 0.2) |
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-
-
- | (0.85, 0.15) |
- 0.1357 |
- 0.1169 |
- 0.1837 |
- 0.1113 |
- 0.1113 |
-
-
- | (0.9, 0.1) |
- 0.1805 |
- 0.1409 |
- 0.1926 |
- 0.1364 |
- 0.1364 |
-
-
- | (0.95, 0.05) |
- 0.2762 |
- 0.2447 |
- 0.2562 |
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- 0.1996 |
-
-
- | (1.0, 0.0) |
- 0.0356 |
- 0.0791 |
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- 0.0928 |
- 0.0928 |
-
-
-
-
-target: G15
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-validation: [0.98427646 0.01572354]
-evaluate_binary: 353.823s
-evaluate_multiclass: 120.493s
-kfcv: 151.945s
-atc_mc: 155.115s
-atc_ne: 92.674s
-doc_feat: 76.970s
-rca_score: 1121.730s
-rca_star_score: 1112.820s
-tot: 1165.059s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.1394 |
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-
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-
-
- | (0.45, 0.55) |
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- 0.2245 |
- 0.2245 |
-
-
- | (0.5, 0.5) |
- 0.2252 |
- 0.2226 |
- 0.3828 |
- 0.1944 |
- 0.1944 |
-
-
- | (0.55, 0.45) |
- 0.2588 |
- 0.2516 |
- 0.3506 |
- 0.2283 |
- 0.2283 |
-
-
- | (0.6, 0.4) |
- 0.2429 |
- 0.2411 |
- 0.3584 |
- 0.2216 |
- 0.2216 |
-
-
- | (0.65, 0.35) |
- 0.2377 |
- 0.2333 |
- 0.3687 |
- 0.2124 |
- 0.2124 |
-
-
- | (0.7, 0.3) |
- 0.2315 |
- 0.2277 |
- 0.3673 |
- 0.2160 |
- 0.2160 |
-
-
- | (0.75, 0.25) |
- 0.2340 |
- 0.2201 |
- 0.3671 |
- 0.2217 |
- 0.2217 |
-
-
- | (0.8, 0.2) |
- 0.2046 |
- 0.2061 |
- 0.3782 |
- 0.2073 |
- 0.2073 |
-
-
- | (0.85, 0.15) |
- 0.2335 |
- 0.2194 |
- 0.3625 |
- 0.2275 |
- 0.2275 |
-
-
- | (0.9, 0.1) |
- 0.2054 |
- 0.1963 |
- 0.3676 |
- 0.2355 |
- 0.2355 |
-
-
- | (0.95, 0.05) |
- 0.1776 |
- 0.1420 |
- 0.4064 |
- 0.2039 |
- 0.2039 |
-
-
- | (1.0, 0.0) |
- 0.0000 |
- 0.0116 |
- 0.6145 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: GCAT
-train: [0.69889407 0.30110593]
-validation: [0.69892009 0.30107991]
-evaluate_binary: 267.282s
-evaluate_multiclass: 139.971s
-kfcv: 180.088s
-atc_mc: 180.896s
-atc_ne: 172.480s
-doc_feat: 138.047s
-rca_score: 1202.504s
-rca_star_score: 1201.723s
-tot: 1263.883s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0121 |
- 0.0155 |
- 0.0762 |
- 0.0293 |
- 0.0293 |
- 0.0768 |
- 0.5284 |
- 0.5080 |
-
-
- | (0.05, 0.95) |
- 0.0320 |
- 0.0285 |
- 0.0729 |
- 0.0320 |
- 0.0320 |
- 0.0735 |
- 0.5319 |
- 0.5115 |
-
-
- | (0.1, 0.9) |
- 0.0290 |
- 0.0279 |
- 0.0654 |
- 0.0352 |
- 0.0352 |
- 0.0661 |
- 0.5395 |
- 0.5191 |
-
-
- | (0.15, 0.85) |
- 0.0267 |
- 0.0255 |
- 0.0588 |
- 0.0263 |
- 0.0263 |
- 0.0595 |
- 0.5460 |
- 0.5256 |
-
-
- | (0.2, 0.8) |
- 0.0244 |
- 0.0273 |
- 0.0503 |
- 0.0249 |
- 0.0249 |
- 0.0511 |
- 0.5549 |
- 0.5345 |
-
-
- | (0.25, 0.75) |
- 0.0257 |
- 0.0263 |
- 0.0528 |
- 0.0265 |
- 0.0265 |
- 0.0537 |
- 0.5476 |
- 0.5268 |
-
-
- | (0.3, 0.7) |
- 0.0292 |
- 0.0298 |
- 0.0458 |
- 0.0258 |
- 0.0258 |
- 0.0465 |
- 0.5200 |
- 0.4984 |
-
-
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- 0.0326 |
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-
-
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- 0.0246 |
- 0.0356 |
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-
-
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-
-
- | (0.5, 0.5) |
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- 0.0315 |
- 0.0754 |
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-
-
- | (0.55, 0.45) |
- 0.0312 |
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- 0.0248 |
- 0.0251 |
- 0.0251 |
- 0.0254 |
- 0.1536 |
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-
-
- | (0.6, 0.4) |
- 0.0313 |
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- 0.1920 |
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-
-
- | (0.65, 0.35) |
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-
-
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-
-
- | (0.75, 0.25) |
- 0.0261 |
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- 0.0171 |
- 0.0152 |
- 0.0152 |
- 0.0172 |
- 0.2047 |
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-
-
- | (0.8, 0.2) |
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- 0.0187 |
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-
-
- | (0.85, 0.15) |
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- 0.0171 |
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-
-
- | (0.9, 0.1) |
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-
-
- | (0.95, 0.05) |
- 0.0161 |
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- 0.0130 |
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-
-
- | (1.0, 0.0) |
- 0.0078 |
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- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0071 |
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-
-
- | (0.05, 0.95) |
- 0.0184 |
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-
-
- | (0.1, 0.9) |
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-
-
- | (0.15, 0.85) |
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-
-
- | (0.2, 0.8) |
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- 0.0165 |
-
-
- | (0.25, 0.75) |
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- 0.0196 |
- 0.0187 |
- 0.0187 |
-
-
- | (0.3, 0.7) |
- 0.0230 |
- 0.0230 |
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-
-
- | (0.35, 0.65) |
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- 0.0251 |
- 0.0251 |
-
-
- | (0.4, 0.6) |
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- 0.0234 |
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- 0.0239 |
-
-
- | (0.45, 0.55) |
- 0.0315 |
- 0.0285 |
- 0.0217 |
- 0.0226 |
- 0.0226 |
-
-
- | (0.5, 0.5) |
- 0.0336 |
- 0.0348 |
- 0.0289 |
- 0.0279 |
- 0.0279 |
-
-
- | (0.55, 0.45) |
- 0.0393 |
- 0.0384 |
- 0.0285 |
- 0.0306 |
- 0.0306 |
-
-
- | (0.6, 0.4) |
- 0.0442 |
- 0.0418 |
- 0.0306 |
- 0.0325 |
- 0.0325 |
-
-
- | (0.65, 0.35) |
- 0.0385 |
- 0.0384 |
- 0.0332 |
- 0.0286 |
- 0.0286 |
-
-
- | (0.7, 0.3) |
- 0.0525 |
- 0.0484 |
- 0.0343 |
- 0.0358 |
- 0.0358 |
-
-
- | (0.75, 0.25) |
- 0.0582 |
- 0.0569 |
- 0.0520 |
- 0.0329 |
- 0.0329 |
-
-
- | (0.8, 0.2) |
- 0.0686 |
- 0.0636 |
- 0.0508 |
- 0.0500 |
- 0.0500 |
-
-
- | (0.85, 0.15) |
- 0.0854 |
- 0.0803 |
- 0.0710 |
- 0.0563 |
- 0.0563 |
-
-
- | (0.9, 0.1) |
- 0.1258 |
- 0.1150 |
- 0.1043 |
- 0.0775 |
- 0.0775 |
-
-
- | (0.95, 0.05) |
- 0.1870 |
- 0.1546 |
- 0.1405 |
- 0.1032 |
- 0.1032 |
-
-
- | (1.0, 0.0) |
- 0.0590 |
- 0.0903 |
- 0.9417 |
- 0.4025 |
- 0.4025 |
-
-
-
-
-target: GCRIM
-train: [0.95109729 0.04890271]
-validation: [0.95101512 0.04898488]
-evaluate_binary: 351.759s
-evaluate_multiclass: 190.396s
-kfcv: 163.725s
-atc_mc: 109.508s
-atc_ne: 103.056s
-doc_feat: 131.868s
-rca_score: 1163.895s
-rca_star_score: 1137.033s
-tot: 1206.507s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0479 |
- 0.0720 |
- 0.6550 |
- 0.1394 |
- 0.1394 |
- 0.6543 |
- 0.6693 |
- 0.6846 |
-
-
- | (0.05, 0.95) |
- 0.0955 |
- 0.1220 |
- 0.6194 |
- 0.1355 |
- 0.1355 |
- 0.6189 |
- 0.6337 |
- 0.6489 |
-
-
- | (0.1, 0.9) |
- 0.1340 |
- 0.1645 |
- 0.5863 |
- 0.1282 |
- 0.1282 |
- 0.5859 |
- 0.6006 |
- 0.6158 |
-
-
- | (0.15, 0.85) |
- 0.1637 |
- 0.1813 |
- 0.5465 |
- 0.1158 |
- 0.1158 |
- 0.5462 |
- 0.5608 |
- 0.5760 |
-
-
- | (0.2, 0.8) |
- 0.1560 |
- 0.1771 |
- 0.5157 |
- 0.1185 |
- 0.1185 |
- 0.5155 |
- 0.5300 |
- 0.5452 |
-
-
- | (0.25, 0.75) |
- 0.1725 |
- 0.1763 |
- 0.4900 |
- 0.1061 |
- 0.1061 |
- 0.4899 |
- 0.5043 |
- 0.5195 |
-
-
- | (0.3, 0.7) |
- 0.1464 |
- 0.1532 |
- 0.4459 |
- 0.0944 |
- 0.0944 |
- 0.4459 |
- 0.4602 |
- 0.4754 |
-
-
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-
-target: GDIP
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-validation: [0.95663067 0.04336933]
-evaluate_binary: 413.043s
-evaluate_multiclass: 184.927s
-kfcv: 111.445s
-atc_mc: 110.721s
-atc_ne: 109.317s
-doc_feat: 127.169s
-rca_score: 1106.672s
-rca_star_score: 1122.975s
-tot: 1177.098s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0579 |
- 0.0936 |
- 0.7770 |
- 0.3906 |
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-
-
- | (0.05, 0.95) |
- 0.0984 |
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-
- | (0.1, 0.9) |
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-
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-
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- | (0.55, 0.45) |
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- | (0.6, 0.4) |
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- 0.1548 |
- 0.1548 |
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-
- | (0.65, 0.35) |
- 0.1107 |
- 0.1423 |
- 0.4052 |
- 0.1409 |
- 0.1409 |
-
-
- | (0.7, 0.3) |
- 0.1128 |
- 0.1437 |
- 0.4064 |
- 0.1615 |
- 0.1615 |
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-
- | (0.75, 0.25) |
- 0.1323 |
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- 0.4118 |
- 0.1728 |
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-
- | (0.8, 0.2) |
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-
- | (0.85, 0.15) |
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- 0.2084 |
- 0.2084 |
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-
- | (0.9, 0.1) |
- 0.1769 |
- 0.1760 |
- 0.3812 |
- 0.2472 |
- 0.2472 |
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-
- | (0.95, 0.05) |
- 0.2056 |
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- 0.2543 |
- 0.2543 |
-
-
- | (1.0, 0.0) |
- 0.0101 |
- 0.0440 |
- 0.7173 |
- 0.0067 |
- 0.0067 |
-
-
-
-
-target: GPOL
-train: [0.92889234 0.07110766]
-validation: [0.9288121 0.0711879]
-evaluate_binary: 269.509s
-evaluate_multiclass: 195.577s
-kfcv: 109.578s
-atc_mc: 112.040s
-atc_ne: 171.498s
-doc_feat: 127.471s
-rca_score: 1224.001s
-rca_star_score: 1196.316s
-tot: 1275.440s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0002 |
- 0.0348 |
- 0.5552 |
- 0.1919 |
- 0.1919 |
- 0.5562 |
- 0.5713 |
- 0.5899 |
-
-
- | (0.05, 0.95) |
- 0.0494 |
- 0.0880 |
- 0.5312 |
- 0.1880 |
- 0.1880 |
- 0.5324 |
- 0.5456 |
- 0.5643 |
-
-
- | (0.1, 0.9) |
- 0.0897 |
- 0.1241 |
- 0.5109 |
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- 0.1771 |
- 0.5121 |
- 0.5236 |
- 0.5424 |
-
-
- | (0.15, 0.85) |
- 0.0897 |
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- 0.4609 |
- 0.1606 |
- 0.1606 |
- 0.4623 |
- 0.4741 |
- 0.4929 |
-
-
- | (0.2, 0.8) |
- 0.0865 |
- 0.1198 |
- 0.4488 |
- 0.1553 |
- 0.1553 |
- 0.4503 |
- 0.4607 |
- 0.4795 |
-
-
- | (0.25, 0.75) |
- 0.0789 |
- 0.1117 |
- 0.4130 |
- 0.1352 |
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- 0.4146 |
- 0.4249 |
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-
- | (0.3, 0.7) |
- 0.0675 |
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-
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-
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-
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-
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-
-
- | (0.75, 0.25) |
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-
- |
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- 0.0748 |
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- 0.1414 |
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- | (0.95, 0.05) |
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- 0.0938 |
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-
-target: GVIO
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-validation: [0.95179266 0.04820734]
-evaluate_binary: 348.091s
-evaluate_multiclass: 119.628s
-kfcv: 101.483s
-atc_mc: 99.585s
-atc_ne: 93.777s
-doc_feat: 105.866s
-rca_score: 1212.214s
-rca_star_score: 1206.863s
-tot: 1254.673s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
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-
-
-
-
- | (0.0, 1.0) |
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- 0.3654 |
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- | (0.4, 0.6) |
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- 0.1692 |
- 0.1692 |
-
-
- | (0.45, 0.55) |
- 0.3429 |
- 0.2175 |
- 0.3080 |
- 0.1520 |
- 0.1520 |
-
-
- | (0.5, 0.5) |
- 0.3541 |
- 0.2390 |
- 0.3222 |
- 0.1718 |
- 0.1718 |
-
-
- | (0.55, 0.45) |
- 0.3511 |
- 0.2404 |
- 0.3006 |
- 0.1666 |
- 0.1666 |
-
-
- | (0.6, 0.4) |
- 0.3761 |
- 0.2613 |
- 0.3075 |
- 0.1877 |
- 0.1877 |
-
-
- | (0.65, 0.35) |
- 0.3395 |
- 0.2429 |
- 0.3063 |
- 0.1731 |
- 0.1731 |
-
-
- | (0.7, 0.3) |
- 0.3303 |
- 0.2322 |
- 0.3031 |
- 0.1754 |
- 0.1754 |
-
-
- | (0.75, 0.25) |
- 0.3659 |
- 0.2758 |
- 0.2916 |
- 0.1900 |
- 0.1900 |
-
-
- | (0.8, 0.2) |
- 0.3330 |
- 0.2645 |
- 0.3360 |
- 0.1986 |
- 0.1986 |
-
-
- | (0.85, 0.15) |
- 0.3368 |
- 0.2671 |
- 0.3177 |
- 0.2187 |
- 0.2187 |
-
-
- | (0.9, 0.1) |
- 0.3129 |
- 0.2731 |
- 0.3336 |
- 0.2263 |
- 0.2263 |
-
-
- | (0.95, 0.05) |
- 0.3385 |
- 0.2961 |
- 0.3269 |
- 0.2767 |
- 0.2767 |
-
-
- | (1.0, 0.0) |
- 0.0201 |
- 0.0412 |
- 0.7910 |
- 0.0067 |
- 0.0067 |
-
-
-
-
-target: GVOTE
-train: [0.9850527 0.0149473]
-validation: [0.985054 0.014946]
-evaluate_binary: 411.703s
-evaluate_multiclass: 176.863s
-kfcv: 110.327s
-atc_mc: 169.946s
-atc_ne: 103.675s
-doc_feat: 82.976s
-rca_score: 939.116s
-rca_star_score: 952.807s
-tot: 999.321s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0460 |
- 0.0643 |
- 0.9242 |
- 0.6730 |
- 0.6730 |
- 0.9234 |
- 0.9313 |
- 0.9356 |
-
-
- | (0.05, 0.95) |
- 0.0888 |
- 0.1053 |
- 0.8832 |
- 0.6560 |
- 0.6560 |
- 0.8825 |
- NaN |
- NaN |
-
-
- | (0.1, 0.9) |
- 0.1341 |
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- 0.6189 |
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- 0.8431 |
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- 0.1799 |
- 0.1965 |
- 0.7917 |
- 0.5908 |
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- NaN |
- NaN |
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-
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- NaN |
- NaN |
-
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- 0.5133 |
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- 0.3236 |
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- 0.4821 |
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- NaN |
- NaN |
-
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- NaN |
- NaN |
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- NaN |
- NaN |
-
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- NaN |
- NaN |
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- NaN |
- NaN |
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- 0.3113 |
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- NaN |
- NaN |
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-
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- 0.3634 |
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- NaN |
- NaN |
-
-
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- NaN |
- NaN |
-
-
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- NaN |
- NaN |
-
-
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- 0.2250 |
- 0.1749 |
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- NaN |
- NaN |
-
-
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- 0.1360 |
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- NaN |
- NaN |
-
-
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- 0.1297 |
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- 0.1014 |
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- NaN |
- NaN |
-
-
- | (0.9, 0.1) |
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- 0.0224 |
- 0.0823 |
- 0.0683 |
- 0.0683 |
- 0.0830 |
- NaN |
- NaN |
-
-
- | (0.95, 0.05) |
- 0.0208 |
- 0.0192 |
- 0.0362 |
- 0.0360 |
- 0.0360 |
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- NaN |
- NaN |
-
-
- | (1.0, 0.0) |
- 0.0011 |
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- 0.0114 |
- 0.0004 |
- 0.0004 |
- 0.0106 |
- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0855 |
- 0.1197 |
- 0.5744 |
- 0.0949 |
- 0.0949 |
-
-
- | (0.05, 0.95) |
- 0.0779 |
- 0.1092 |
- 0.5851 |
- 0.0875 |
- 0.0875 |
-
-
- | (0.1, 0.9) |
- 0.0745 |
- 0.1091 |
- 0.5851 |
- 0.0902 |
- 0.0902 |
-
-
- | (0.15, 0.85) |
- 0.0714 |
- 0.1036 |
- 0.5908 |
- 0.0797 |
- 0.0797 |
-
-
- | (0.2, 0.8) |
- 0.0864 |
- 0.1142 |
- 0.5802 |
- 0.0859 |
- 0.0859 |
-
-
- | (0.25, 0.75) |
- 0.0838 |
- 0.1133 |
- 0.5810 |
- 0.0816 |
- 0.0816 |
-
-
- | (0.3, 0.7) |
- 0.0829 |
- 0.1067 |
- 0.5877 |
- 0.0843 |
- 0.0843 |
-
-
- | (0.35, 0.65) |
- 0.0854 |
- 0.1114 |
- 0.5830 |
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- 0.0855 |
-
-
- | (0.4, 0.6) |
- 0.0872 |
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- 0.5798 |
- 0.0937 |
- 0.0937 |
-
-
- | (0.45, 0.55) |
- 0.0867 |
- 0.1094 |
- 0.5849 |
- 0.0922 |
- 0.0922 |
-
-
- | (0.5, 0.5) |
- 0.0889 |
- 0.1172 |
- 0.5771 |
- 0.0851 |
- 0.0851 |
-
-
- | (0.55, 0.45) |
- 0.0774 |
- 0.1027 |
- 0.5913 |
- 0.0902 |
- 0.0902 |
-
-
- | (0.6, 0.4) |
- 0.0823 |
- 0.1163 |
- 0.5776 |
- 0.0963 |
- 0.0963 |
-
-
- | (0.65, 0.35) |
- 0.0797 |
- 0.1155 |
- 0.5773 |
- 0.1015 |
- 0.1015 |
-
-
- | (0.7, 0.3) |
- 0.0715 |
- 0.0973 |
- 0.5963 |
- 0.0893 |
- 0.0893 |
-
-
- | (0.75, 0.25) |
- 0.0762 |
- 0.0989 |
- 0.5953 |
- 0.0954 |
- 0.0954 |
-
-
- | (0.8, 0.2) |
- 0.0930 |
- 0.1105 |
- 0.5817 |
- 0.1116 |
- 0.1116 |
-
-
- | (0.85, 0.15) |
- 0.0847 |
- 0.1023 |
- 0.5880 |
- 0.1028 |
- 0.1028 |
-
-
- | (0.9, 0.1) |
- 0.0762 |
- 0.1029 |
- 0.5820 |
- 0.1125 |
- 0.1125 |
-
-
- | (0.95, 0.05) |
- 0.0726 |
- 0.0648 |
- 0.6172 |
- 0.0824 |
- 0.0824 |
-
-
- | (1.0, 0.0) |
- 0.0000 |
- 0.0000 |
- 0.6944 |
- 0.0000 |
- 0.0000 |
-
-
-
-
-target: GWEA
-train: [0.99421116 0.00578884]
-validation: [0.99412527 0.00587473]
-evaluate_binary: 262.208s
-evaluate_multiclass: 108.019s
-kfcv: 97.840s
-atc_mc: 135.028s
-atc_ne: 94.500s
-doc_feat: 82.704s
-rca_score: 374.076s
-rca_star_score: 374.355s
-tot: 415.864s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0065 |
- 0.0073 |
- 0.9874 |
- 0.6409 |
- 0.6409 |
- 0.9869 |
- NaN |
- NaN |
-
-
- | (0.05, 0.95) |
- 0.0548 |
- 0.0555 |
- 0.9392 |
- 0.6198 |
- 0.6198 |
- 0.9387 |
- NaN |
- NaN |
-
-
- | (0.1, 0.9) |
- 0.1041 |
- 0.1052 |
- 0.8894 |
- 0.5877 |
- 0.5877 |
- 0.8890 |
- NaN |
- NaN |
-
-
- | (0.15, 0.85) |
- 0.1538 |
- 0.1547 |
- 0.8399 |
- 0.5488 |
- 0.5488 |
- 0.8395 |
- NaN |
- NaN |
-
-
- | (0.2, 0.8) |
- 0.2038 |
- 0.2049 |
- 0.7895 |
- 0.5267 |
- 0.5267 |
- 0.7892 |
- NaN |
- NaN |
-
-
- | (0.25, 0.75) |
- 0.2555 |
- 0.2565 |
- 0.7376 |
- 0.4843 |
- 0.4843 |
- 0.7373 |
- NaN |
- NaN |
-
-
- | (0.3, 0.7) |
- 0.3040 |
- 0.3026 |
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- 0.4579 |
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- NaN |
- NaN |
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- 0.0164 |
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-
-
-target: M11
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-validation: [0.94410367 0.05589633]
-evaluate_binary: 350.246s
-evaluate_multiclass: 186.170s
-kfcv: 106.680s
-atc_mc: 169.230s
-atc_ne: 99.756s
-doc_feat: 75.310s
-rca_score: 1245.803s
-rca_star_score: 1216.185s
-tot: 1288.407s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
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- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0023 |
- 0.0219 |
- 0.3491 |
- 0.0863 |
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-
-
- | (0.05, 0.95) |
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-
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-
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-
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- | (0.6, 0.4) |
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- 0.0599 |
- 0.0599 |
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-
- | (0.65, 0.35) |
- 0.0464 |
- 0.0650 |
- 0.1282 |
- 0.0702 |
- 0.0702 |
-
-
- | (0.7, 0.3) |
- 0.0666 |
- 0.0780 |
- 0.1251 |
- 0.0732 |
- 0.0732 |
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-
- | (0.75, 0.25) |
- 0.0618 |
- 0.0630 |
- 0.1208 |
- 0.0717 |
- 0.0717 |
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-
- | (0.8, 0.2) |
- 0.1169 |
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- 0.1240 |
- 0.0962 |
- 0.0962 |
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-
- | (0.85, 0.15) |
- 0.1162 |
- 0.0982 |
- 0.1268 |
- 0.0994 |
- 0.0994 |
-
-
- | (0.9, 0.1) |
- 0.1245 |
- 0.1044 |
- 0.1286 |
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-
- | (0.95, 0.05) |
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-
- | (1.0, 0.0) |
- 0.0368 |
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- 0.0500 |
- 0.0500 |
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-
-
-
-target: M12
-train: [0.9683774 0.0316226]
-validation: [0.96838013 0.03161987]
-evaluate_binary: 388.733s
-evaluate_multiclass: 144.432s
-kfcv: 199.371s
-atc_mc: 127.456s
-atc_ne: 206.927s
-doc_feat: 172.047s
-rca_score: 1212.021s
-rca_star_score: 1206.772s
-tot: 1256.777s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0030 |
- 0.0328 |
- 0.6541 |
- 0.1457 |
- 0.1457 |
- 0.6541 |
- 0.6675 |
- 0.6782 |
-
-
- | (0.05, 0.95) |
- 0.0536 |
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- 0.6255 |
- 0.1392 |
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- 0.6256 |
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- 0.6493 |
-
-
- | (0.1, 0.9) |
- 0.1040 |
- 0.1432 |
- 0.5807 |
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- 0.5938 |
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-
-
- | (0.15, 0.85) |
- 0.1500 |
- 0.1820 |
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- 0.5536 |
- 0.5661 |
- 0.5768 |
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-
- | (0.2, 0.8) |
- 0.1469 |
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- 0.5093 |
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- 0.5098 |
- 0.5220 |
- 0.5327 |
-
-
- | (0.25, 0.75) |
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-
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-
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-
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-
-
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-
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- 0.0666 |
- 0.1183 |
- 0.2320 |
- 0.2335 |
- 0.2335 |
-
-
- | (0.4, 0.6) |
- 0.0596 |
- 0.1128 |
- 0.2233 |
- 0.2311 |
- 0.2311 |
-
-
- | (0.45, 0.55) |
- 0.0657 |
- 0.1138 |
- 0.2313 |
- 0.2405 |
- 0.2405 |
-
-
- | (0.5, 0.5) |
- 0.0592 |
- 0.1057 |
- 0.2215 |
- 0.2402 |
- 0.2402 |
-
-
- | (0.55, 0.45) |
- 0.0617 |
- 0.1050 |
- 0.2201 |
- 0.2322 |
- 0.2322 |
-
-
- | (0.6, 0.4) |
- 0.0593 |
- 0.1089 |
- 0.2122 |
- 0.2715 |
- 0.2715 |
-
-
- | (0.65, 0.35) |
- 0.0642 |
- 0.1180 |
- 0.2497 |
- 0.2050 |
- 0.2050 |
-
-
- | (0.7, 0.3) |
- 0.0621 |
- 0.1181 |
- 0.2454 |
- 0.2367 |
- 0.2367 |
-
-
- | (0.75, 0.25) |
- 0.1027 |
- 0.1130 |
- 0.2273 |
- 0.2325 |
- 0.2325 |
-
-
- | (0.8, 0.2) |
- 0.0839 |
- 0.1212 |
- 0.2340 |
- 0.2342 |
- 0.2342 |
-
-
- | (0.85, 0.15) |
- 0.1276 |
- 0.1550 |
- 0.2151 |
- 0.2605 |
- 0.2605 |
-
-
- | (0.9, 0.1) |
- 0.1423 |
- 0.1724 |
- 0.2465 |
- 0.2551 |
- 0.2551 |
-
-
- | (0.95, 0.05) |
- 0.1928 |
- 0.2059 |
- 0.3203 |
- 0.2870 |
- 0.2870 |
-
-
- | (1.0, 0.0) |
- 0.0167 |
- 0.0393 |
- 0.7109 |
- 0.0100 |
- 0.0100 |
-
-
-
-
-target: M13
-train: [0.93105236 0.06894764]
-validation: [0.93105832 0.06894168]
-evaluate_binary: 325.372s
-evaluate_multiclass: 189.027s
-kfcv: 110.743s
-atc_mc: 176.696s
-atc_ne: 105.095s
-doc_feat: 77.559s
-rca_score: 1219.115s
-rca_star_score: 1234.910s
-tot: 1284.729s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0010 |
- 0.0213 |
- 0.3685 |
- 0.1115 |
- 0.1115 |
- 0.3667 |
- 0.4427 |
- 0.4345 |
-
-
- | (0.05, 0.95) |
- 0.0534 |
- 0.0757 |
- 0.3361 |
- 0.0887 |
- 0.0887 |
- 0.3344 |
- 0.3953 |
- 0.3930 |
-
-
- | (0.1, 0.9) |
- 0.0902 |
- 0.1136 |
- 0.3287 |
- 0.0975 |
- 0.0975 |
- 0.3271 |
- 0.3173 |
- 0.3267 |
-
-
- | (0.15, 0.85) |
- 0.0903 |
- 0.1147 |
- 0.3039 |
- 0.0914 |
- 0.0914 |
- 0.3025 |
- 0.2832 |
- 0.2987 |
-
-
- | (0.2, 0.8) |
- 0.0772 |
- 0.0962 |
- 0.2763 |
- 0.0842 |
- 0.0842 |
- 0.2750 |
- 0.2709 |
- 0.2862 |
-
-
- | (0.25, 0.75) |
- 0.0756 |
- 0.0962 |
- 0.2708 |
- 0.0870 |
- 0.0870 |
- 0.2696 |
- 0.2745 |
- 0.2912 |
-
-
- | (0.3, 0.7) |
- 0.0608 |
- 0.0763 |
- 0.2495 |
- 0.0858 |
- 0.0858 |
- 0.2484 |
- 0.2498 |
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-
- | (0.35, 0.65) |
- 0.0565 |
- 0.0750 |
- 0.2303 |
- 0.0814 |
- 0.0814 |
- 0.2293 |
- 0.2253 |
- 0.2418 |
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-
- | (0.4, 0.6) |
- 0.0502 |
- 0.0713 |
- 0.2122 |
- 0.0631 |
- 0.0631 |
- 0.2113 |
- 0.2007 |
- 0.2172 |
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-
- | (0.45, 0.55) |
- 0.0480 |
- 0.0614 |
- 0.1844 |
- 0.0601 |
- 0.0601 |
- 0.1836 |
- 0.1695 |
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-
- | (0.5, 0.5) |
- 0.0387 |
- 0.0495 |
- 0.1750 |
- 0.0574 |
- 0.0574 |
- 0.1744 |
- 0.1550 |
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-
- | (0.55, 0.45) |
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- 0.0504 |
- 0.0504 |
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- 0.1321 |
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- | (0.6, 0.4) |
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-
- | (0.75, 0.25) |
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- 0.0288 |
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-
- | (0.85, 0.15) |
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- 0.0389 |
- 0.0243 |
- 0.0243 |
- 0.0391 |
- 0.0193 |
- 0.0322 |
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-
- | (0.9, 0.1) |
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- | (1.0, 0.0) |
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- 0.0038 |
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- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
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-
-
-
-
- | (0.0, 1.0) |
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- 0.0348 |
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-
- | (0.05, 0.95) |
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- 0.0458 |
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- | (0.1, 0.9) |
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-
- | (0.15, 0.85) |
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-
- | (0.2, 0.8) |
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-
- | (0.25, 0.75) |
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- 0.1434 |
- 0.0431 |
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-
- | (0.3, 0.7) |
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- 0.1420 |
- 0.0474 |
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-
-
- | (0.35, 0.65) |
- 0.0390 |
- 0.0629 |
- 0.1427 |
- 0.0470 |
- 0.0470 |
-
-
- | (0.4, 0.6) |
- 0.0369 |
- 0.0657 |
- 0.1440 |
- 0.0401 |
- 0.0401 |
-
-
- | (0.45, 0.55) |
- 0.0393 |
- 0.0592 |
- 0.1319 |
- 0.0417 |
- 0.0417 |
-
-
- | (0.5, 0.5) |
- 0.0343 |
- 0.0534 |
- 0.1471 |
- 0.0408 |
- 0.0408 |
-
-
- | (0.55, 0.45) |
- 0.0393 |
- 0.0609 |
- 0.1455 |
- 0.0535 |
- 0.0535 |
-
-
- | (0.6, 0.4) |
- 0.0351 |
- 0.0520 |
- 0.1372 |
- 0.0551 |
- 0.0551 |
-
-
- | (0.65, 0.35) |
- 0.0418 |
- 0.0584 |
- 0.1511 |
- 0.0608 |
- 0.0608 |
-
-
- | (0.7, 0.3) |
- 0.0480 |
- 0.0616 |
- 0.1447 |
- 0.0638 |
- 0.0638 |
-
-
- | (0.75, 0.25) |
- 0.0607 |
- 0.0722 |
- 0.1321 |
- 0.0593 |
- 0.0593 |
-
-
- | (0.8, 0.2) |
- 0.0784 |
- 0.0847 |
- 0.1595 |
- 0.0717 |
- 0.0717 |
-
-
- | (0.85, 0.15) |
- 0.0776 |
- 0.0947 |
- 0.1630 |
- 0.1019 |
- 0.1019 |
-
-
- | (0.9, 0.1) |
- 0.1181 |
- 0.1320 |
- 0.1537 |
- 0.1078 |
- 0.1078 |
-
-
- | (0.95, 0.05) |
- 0.2088 |
- 0.1783 |
- 0.1868 |
- 0.1860 |
- 0.1860 |
-
-
- | (1.0, 0.0) |
- 0.0399 |
- 0.0728 |
- 0.8990 |
- 0.1200 |
- 0.1200 |
-
-
-
-
-target: M131
-train: [0.95930534 0.04069466]
-validation: [0.95922246 0.04077754]
-evaluate_binary: 301.469s
-evaluate_multiclass: 233.836s
-kfcv: 197.763s
-atc_mc: 208.329s
-atc_ne: 203.979s
-doc_feat: 76.945s
-rca_score: 1221.431s
-rca_star_score: 1220.546s
-tot: 1273.127s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0008 |
- 0.0205 |
- 0.3872 |
- 0.0672 |
- 0.0672 |
- 0.3880 |
- 0.4122 |
- 0.4139 |
-
-
- | (0.05, 0.95) |
- 0.0506 |
- 0.0703 |
- 0.3731 |
- 0.0684 |
- 0.0684 |
- 0.3741 |
- 0.3759 |
- 0.3844 |
-
-
- | (0.1, 0.9) |
- 0.0944 |
- 0.1074 |
- 0.3449 |
- 0.0578 |
- 0.0578 |
- 0.3459 |
- 0.3448 |
- 0.3558 |
-
-
- | (0.15, 0.85) |
- 0.1050 |
- 0.1047 |
- 0.3346 |
- 0.0613 |
- 0.0613 |
- 0.3358 |
- 0.3430 |
- 0.3545 |
-
-
- | (0.2, 0.8) |
- 0.0937 |
- 0.0909 |
- 0.3051 |
- 0.0577 |
- 0.0577 |
- 0.3064 |
- 0.3169 |
- 0.3284 |
-
-
- | (0.25, 0.75) |
- 0.0848 |
- 0.0844 |
- 0.2914 |
- 0.0550 |
- 0.0550 |
- 0.2928 |
- 0.3017 |
- 0.3135 |
-
-
- | (0.3, 0.7) |
- 0.0640 |
- 0.0661 |
- 0.2651 |
- 0.0536 |
- 0.0536 |
- 0.2666 |
- 0.2744 |
- 0.2862 |
-
-
- | (0.35, 0.65) |
- 0.0626 |
- 0.0609 |
- 0.2503 |
- 0.0527 |
- 0.0527 |
- 0.2519 |
- 0.2564 |
- 0.2684 |
-
-
- | (0.4, 0.6) |
- 0.0547 |
- 0.0568 |
- 0.2316 |
- 0.0562 |
- 0.0562 |
- 0.2334 |
- 0.2346 |
- 0.2467 |
-
-
- | (0.45, 0.55) |
- 0.0449 |
- 0.0458 |
- 0.2024 |
- 0.0454 |
- 0.0454 |
- 0.2043 |
- 0.2038 |
- 0.2159 |
-
-
- | (0.5, 0.5) |
- 0.0388 |
- 0.0414 |
- 0.1915 |
- 0.0473 |
- 0.0473 |
- 0.1935 |
- 0.1895 |
- 0.2014 |
-
-
- | (0.55, 0.45) |
- 0.0322 |
- 0.0321 |
- 0.1652 |
- 0.0406 |
- 0.0406 |
- 0.1673 |
- 0.1615 |
- 0.1734 |
-
-
- | (0.6, 0.4) |
- 0.0269 |
- 0.0317 |
- 0.1432 |
- 0.0380 |
- 0.0380 |
- 0.1454 |
- 0.1380 |
- 0.1498 |
-
-
- | (0.65, 0.35) |
- 0.0204 |
- 0.0239 |
- 0.1250 |
- 0.0353 |
- 0.0353 |
- 0.1274 |
- 0.1191 |
- 0.1309 |
-
-
- | (0.7, 0.3) |
- 0.0236 |
- 0.0266 |
- 0.1093 |
- 0.0356 |
- 0.0356 |
- 0.1118 |
- 0.1029 |
- 0.1148 |
-
-
- | (0.75, 0.25) |
- 0.0258 |
- 0.0314 |
- 0.0839 |
- 0.0254 |
- 0.0254 |
- 0.0865 |
- 0.0775 |
- 0.0893 |
-
-
- | (0.8, 0.2) |
- 0.0200 |
- 0.0275 |
- 0.0626 |
- 0.0244 |
- 0.0244 |
- 0.0653 |
- 0.0562 |
- 0.0680 |
-
-
- | (0.85, 0.15) |
- 0.0237 |
- 0.0250 |
- 0.0447 |
- 0.0216 |
- 0.0216 |
- 0.0475 |
- 0.0383 |
- 0.0501 |
-
-
- | (0.9, 0.1) |
- 0.0194 |
- 0.0212 |
- 0.0265 |
- 0.0188 |
- 0.0188 |
- 0.0292 |
- 0.0211 |
- 0.0315 |
-
-
- | (0.95, 0.05) |
- 0.0149 |
- 0.0141 |
- 0.0074 |
- 0.0115 |
- 0.0115 |
- 0.0086 |
- 0.0088 |
- 0.0096 |
-
-
- | (1.0, 0.0) |
- 0.0026 |
- 0.0019 |
- 0.0172 |
- 0.0025 |
- 0.0025 |
- 0.0140 |
- NaN |
- NaN |
-
-
-
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
-
-
-
-
- | (0.0, 1.0) |
- 0.0006 |
- 0.0166 |
- 0.1116 |
- 0.0647 |
- 0.0647 |
-
-
- | (0.05, 0.95) |
- 0.0242 |
- 0.0416 |
- 0.1169 |
- 0.0615 |
- 0.0615 |
-
-
- | (0.1, 0.9) |
- 0.0461 |
- 0.0639 |
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- 0.0745 |
-
-
- | (0.15, 0.85) |
- 0.0530 |
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- 0.0688 |
- 0.0688 |
-
-
- | (0.2, 0.8) |
- 0.0504 |
- 0.0596 |
- 0.1111 |
- 0.0678 |
- 0.0678 |
-
-
- | (0.25, 0.75) |
- 0.0487 |
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- 0.1180 |
- 0.0684 |
- 0.0684 |
-
-
- | (0.3, 0.7) |
- 0.0401 |
- 0.0519 |
- 0.1117 |
- 0.0693 |
- 0.0693 |
-
-
- | (0.35, 0.65) |
- 0.0428 |
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- 0.1182 |
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- 0.0689 |
-
-
- | (0.4, 0.6) |
- 0.0411 |
- 0.0522 |
- 0.1217 |
- 0.0743 |
- 0.0743 |
-
-
- | (0.45, 0.55) |
- 0.0375 |
- 0.0457 |
- 0.1105 |
- 0.0801 |
- 0.0801 |
-
-
- | (0.5, 0.5) |
- 0.0356 |
- 0.0481 |
- 0.1253 |
- 0.0755 |
- 0.0755 |
-
-
- | (0.55, 0.45) |
- 0.0326 |
- 0.0406 |
- 0.1150 |
- 0.0763 |
- 0.0763 |
-
-
- | (0.6, 0.4) |
- 0.0347 |
- 0.0471 |
- 0.1115 |
- 0.0868 |
- 0.0868 |
-
-
- | (0.65, 0.35) |
- 0.0264 |
- 0.0404 |
- 0.1187 |
- 0.0828 |
- 0.0828 |
-
-
- | (0.7, 0.3) |
- 0.0448 |
- 0.0573 |
- 0.1312 |
- 0.0876 |
- 0.0876 |
-
-
- | (0.75, 0.25) |
- 0.0600 |
- 0.0764 |
- 0.1205 |
- 0.0982 |
- 0.0982 |
-
-
- | (0.8, 0.2) |
- 0.0537 |
- 0.0773 |
- 0.1167 |
- 0.0992 |
- 0.0992 |
-
-
- | (0.85, 0.15) |
- 0.1014 |
- 0.1041 |
- 0.1302 |
- 0.1202 |
- 0.1202 |
-
-
- | (0.9, 0.1) |
- 0.1109 |
- 0.1288 |
- 0.1593 |
- 0.1479 |
- 0.1479 |
-
-
- | (0.95, 0.05) |
- 0.2059 |
- 0.1809 |
- 0.1532 |
- 0.1841 |
- 0.1841 |
-
-
- | (1.0, 0.0) |
- 0.0436 |
- 0.0627 |
- 0.8558 |
- 0.0533 |
- 0.0533 |
-
-
-
-
-target: M132
-train: [0.96984621 0.03015379]
-validation: [0.96976242 0.03023758]
-evaluate_binary: 321.525s
-evaluate_multiclass: 206.725s
-kfcv: 173.106s
-atc_mc: 170.535s
-atc_ne: 107.990s
-doc_feat: 84.375s
-rca_score: 1216.493s
-rca_star_score: 1232.990s
-tot: 1283.130s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0321 |
- 0.0555 |
- 0.5060 |
- 0.1270 |
- 0.1270 |
- 0.5057 |
- 0.5117 |
- 0.5245 |
-
-
- | (0.05, 0.95) |
- 0.1024 |
- 0.1150 |
- 0.4899 |
- 0.1208 |
- 0.1208 |
- 0.4897 |
- 0.5004 |
- 0.5133 |
-
-
- | (0.1, 0.9) |
- 0.1253 |
- 0.1636 |
- 0.4543 |
- 0.1083 |
- 0.1083 |
- 0.4542 |
- 0.4647 |
- 0.4774 |
-
-
- | (0.15, 0.85) |
- 0.1881 |
- 0.2076 |
- 0.4293 |
- 0.1052 |
- 0.1052 |
- 0.4294 |
- 0.4383 |
- 0.4511 |
-
-
- | (0.2, 0.8) |
- 0.2069 |
- 0.2170 |
- 0.4093 |
- 0.0996 |
- 0.0996 |
- 0.4095 |
- 0.4160 |
- 0.4288 |
-
-
- | (0.25, 0.75) |
- 0.1893 |
- 0.2036 |
- 0.3772 |
- 0.0889 |
- 0.0889 |
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-
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-
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- 0.1239 |
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-
- | (0.85, 0.15) |
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- 0.1316 |
-
-
- | (0.9, 0.1) |
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-
-target: M14
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-validation: [0.89019438 0.10980562]
-evaluate_binary: 221.946s
-evaluate_multiclass: 119.692s
-kfcv: 142.085s
-atc_mc: 136.098s
-atc_ne: 89.356s
-doc_feat: 74.912s
-rca_score: 1226.222s
-rca_star_score: 1225.357s
-tot: 1281.699s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0029 |
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-
- | (0.05, 0.95) |
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-
- | (0.1, 0.9) |
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-
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-
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-
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-
- | (0.5, 0.5) |
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-
- | (0.55, 0.45) |
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-
- | (0.6, 0.4) |
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-
- | (0.65, 0.35) |
- 0.0331 |
- 0.0428 |
- 0.0786 |
- 0.0404 |
- 0.0404 |
-
-
- | (0.7, 0.3) |
- 0.0312 |
- 0.0473 |
- 0.0678 |
- 0.0501 |
- 0.0501 |
-
-
- | (0.75, 0.25) |
- 0.0448 |
- 0.0526 |
- 0.0721 |
- 0.0542 |
- 0.0542 |
-
-
- | (0.8, 0.2) |
- 0.0468 |
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- 0.0761 |
- 0.0641 |
- 0.0641 |
-
-
- | (0.85, 0.15) |
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- 0.0614 |
- 0.0733 |
- 0.0743 |
- 0.0743 |
-
-
- | (0.9, 0.1) |
- 0.1205 |
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- 0.0884 |
- 0.0884 |
-
-
- | (0.95, 0.05) |
- 0.1565 |
- 0.1238 |
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- 0.1289 |
-
-
- | (1.0, 0.0) |
- 0.0353 |
- 0.0644 |
- 0.9221 |
- 0.1380 |
- 0.1380 |
-
-
-
-
-target: M141
-train: [0.93485398 0.06514602]
-validation: [0.93485961 0.06514039]
-evaluate_binary: 300.410s
-evaluate_multiclass: 211.143s
-kfcv: 106.019s
-atc_mc: 193.164s
-atc_ne: 168.442s
-doc_feat: 154.162s
-rca_score: 1231.179s
-rca_star_score: 1227.842s
-tot: 1275.118s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0063 |
- 0.0256 |
- 0.2921 |
- 0.0568 |
- 0.0568 |
- 0.2915 |
- 0.5947 |
- 0.5748 |
-
-
- | (0.05, 0.95) |
- 0.0529 |
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- 0.2684 |
- 0.0450 |
- 0.0450 |
- 0.2680 |
- 0.6035 |
- 0.5845 |
-
-
- | (0.1, 0.9) |
- 0.0779 |
- 0.0875 |
- 0.2530 |
- 0.0461 |
- 0.0461 |
- 0.2527 |
- 0.5370 |
- 0.5222 |
-
-
- | (0.15, 0.85) |
- 0.0739 |
- 0.0818 |
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- 0.0456 |
- 0.2360 |
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-
-
- | (0.2, 0.8) |
- 0.0715 |
- 0.0774 |
- 0.2196 |
- 0.0380 |
- 0.0380 |
- 0.2195 |
- 0.2505 |
- 0.2598 |
-
-
- | (0.25, 0.75) |
- 0.0631 |
- 0.0712 |
- 0.2129 |
- 0.0398 |
- 0.0398 |
- 0.2129 |
- 0.2163 |
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-
-
- | (0.3, 0.7) |
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- 0.0362 |
- 0.1817 |
- 0.1849 |
- 0.2042 |
-
-
- | (0.35, 0.65) |
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-
-
- | (0.4, 0.6) |
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-
-
- | (0.45, 0.55) |
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-
-
- | (0.5, 0.5) |
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-
-
- | (0.55, 0.45) |
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- 0.0319 |
- 0.0319 |
- 0.1223 |
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-
-
- | (0.6, 0.4) |
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-
-
- | (0.65, 0.35) |
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-
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-
-
- | (0.75, 0.25) |
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-
-
- | (0.8, 0.2) |
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-
-
- | (0.85, 0.15) |
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-
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-
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-
- | (1.0, 0.0) |
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-
-
-
-
-
-
-
- |
- bin |
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-
-
-
- | (0.0, 1.0) |
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-
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- 0.1079 |
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- 0.0986 |
- 0.0905 |
- 0.0905 |
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-
- | (0.9, 0.1) |
- 0.1545 |
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- 0.2456 |
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- 0.0100 |
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- 0.0267 |
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-
-target: M142
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-validation: [0.98652268 0.01347732]
-evaluate_binary: 360.311s
-evaluate_multiclass: 147.946s
-kfcv: 160.268s
-atc_mc: 107.097s
-atc_ne: 160.737s
-doc_feat: 79.718s
-rca_score: 1250.102s
-rca_star_score: 1217.368s
-tot: 1290.194s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
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- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
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-
- | (0.05, 0.95) |
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-
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- 0.2313 |
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-
- | (0.6, 0.4) |
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- 0.2563 |
- 0.2563 |
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-
- | (0.65, 0.35) |
- 0.0529 |
- 0.2882 |
- 0.2163 |
- 0.2698 |
- 0.2698 |
-
-
- | (0.7, 0.3) |
- 0.0522 |
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- 0.2316 |
- 0.2384 |
- 0.2384 |
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-
- | (0.75, 0.25) |
- 0.0503 |
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- 0.2361 |
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- 0.2468 |
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-
- | (0.8, 0.2) |
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-
- | (0.85, 0.15) |
- 0.0596 |
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-
- | (0.9, 0.1) |
- 0.1113 |
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-
- | (0.95, 0.05) |
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- | (1.0, 0.0) |
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- 0.0000 |
- 0.0000 |
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-
-
-
-target: M143
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-validation: [0.97382289 0.02617711]
-evaluate_binary: 473.804s
-evaluate_multiclass: 228.844s
-kfcv: 156.644s
-atc_mc: 102.505s
-atc_ne: 101.586s
-doc_feat: 79.162s
-rca_score: 1232.456s
-rca_star_score: 1207.609s
-tot: 1277.000s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.3004 |
- 0.0273 |
- 0.4414 |
- 0.1547 |
- 0.1547 |
- 0.4412 |
- 0.4471 |
- 0.4553 |
-
-
- | (0.05, 0.95) |
- 0.3697 |
- 0.0897 |
- 0.4127 |
- 0.1511 |
- 0.1511 |
- 0.4126 |
- 0.4190 |
- 0.4283 |
-
-
- | (0.1, 0.9) |
- 0.3678 |
- 0.1564 |
- 0.3906 |
- 0.1270 |
- 0.1270 |
- 0.3906 |
- 0.3989 |
- 0.4083 |
-
-
- | (0.15, 0.85) |
- 0.3959 |
- 0.2215 |
- 0.3634 |
- 0.1238 |
- 0.1238 |
- 0.3635 |
- 0.3719 |
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-
-
- | (0.2, 0.8) |
- 0.4299 |
- 0.2887 |
- 0.3489 |
- 0.1196 |
- 0.1196 |
- 0.3491 |
- 0.3558 |
- 0.3653 |
-
-
- | (0.25, 0.75) |
- 0.3529 |
- 0.3275 |
- 0.3288 |
- 0.1260 |
- 0.1260 |
- 0.3292 |
- 0.3343 |
- 0.3437 |
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-
- | (0.3, 0.7) |
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- 0.3045 |
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-
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-
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- 0.3132 |
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- 0.2592 |
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-
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-
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-
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- 0.1971 |
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-
- | (0.6, 0.4) |
- 0.1718 |
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- 0.0645 |
- 0.1681 |
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-
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-
- | (0.7, 0.3) |
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- 0.1270 |
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-
- | (0.75, 0.25) |
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- 0.0424 |
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-
- | (0.8, 0.2) |
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- 0.0331 |
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-
- | (0.85, 0.15) |
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-
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-
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-
-
- |
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- kfcv |
- atc_mc |
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-
-
-
-
- | (0.0, 1.0) |
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-
- | (0.4, 0.6) |
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-
-
- | (0.45, 0.55) |
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- 0.0610 |
- 0.0610 |
-
-
- | (0.5, 0.5) |
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-
-
- | (0.55, 0.45) |
- 0.3622 |
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- 0.1540 |
- 0.0592 |
- 0.0592 |
-
-
- | (0.6, 0.4) |
- 0.4027 |
- 0.2114 |
- 0.1484 |
- 0.0720 |
- 0.0720 |
-
-
- | (0.65, 0.35) |
- 0.4341 |
- 0.2089 |
- 0.1577 |
- 0.0725 |
- 0.0725 |
-
-
- | (0.7, 0.3) |
- 0.3635 |
- 0.1884 |
- 0.1521 |
- 0.0732 |
- 0.0732 |
-
-
- | (0.75, 0.25) |
- 0.3953 |
- 0.1813 |
- 0.1453 |
- 0.0840 |
- 0.0840 |
-
-
- | (0.8, 0.2) |
- 0.3744 |
- 0.1759 |
- 0.1587 |
- 0.0802 |
- 0.0802 |
-
-
- | (0.85, 0.15) |
- 0.3957 |
- 0.1756 |
- 0.1540 |
- 0.0909 |
- 0.0909 |
-
-
- | (0.9, 0.1) |
- 0.3841 |
- 0.1867 |
- 0.1756 |
- 0.1344 |
- 0.1344 |
-
-
- | (0.95, 0.05) |
- 0.3583 |
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- 0.1836 |
- 0.1836 |
-
-
- | (1.0, 0.0) |
- 0.0000 |
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- 0.0200 |
- 0.0200 |
-
-
-
-
-target: MCAT
-train: [0.74589597 0.25410403]
-validation: [0.74591793 0.25408207]
-evaluate_binary: 239.003s
-evaluate_multiclass: 125.654s
-kfcv: 109.511s
-atc_mc: 133.150s
-atc_ne: 93.708s
-doc_feat: 96.904s
-rca_score: 1237.329s
-rca_star_score: 1220.138s
-tot: 1304.368s
-
-
-
-
- |
- bin |
- mul |
- kfcv |
- atc_mc |
- atc_ne |
- doc_feat |
- rca |
- rca_star |
-
-
-
-
- | (0.0, 1.0) |
- 0.0116 |
- 0.0170 |
- 0.1198 |
- 0.0430 |
- 0.0430 |
- 0.1237 |
- 0.5387 |
- 0.5136 |
-
-
- | (0.05, 0.95) |
- 0.0247 |
- 0.0297 |
- 0.1142 |
- 0.0434 |
- 0.0434 |
- 0.1182 |
- 0.5443 |
- 0.5192 |
-
-
- | (0.1, 0.9) |
- 0.0262 |
- 0.0307 |
- 0.1065 |
- 0.0421 |
- 0.0421 |
- 0.1105 |
- 0.5520 |
- 0.5269 |
-
-
- | (0.15, 0.85) |
- 0.0256 |
- 0.0324 |
- 0.0964 |
- 0.0379 |
- 0.0379 |
- 0.1005 |
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diff --git a/out_spambase.md b/out_spambase.md
index e8ad65b..8686607 100644
--- a/out_spambase.md
+++ b/out_spambase.md
@@ -1,445 +1,445 @@
-
-target: default
-train: [0.60621118 0.39378882]
-validation: [0.60559006 0.39440994]
-evaluate_binary: 31.883s
-evaluate_multiclass: 24.748s
-kfcv: 23.957s
-atc_mc: 36.062s
-atc_ne: 37.123s
-doc_feat: 7.063s
-rca_score: 148.420s
-rca_star_score: 145.690s
-tot: 149.118s
-
-
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diff --git a/poetry.lock b/poetry.lock
index 8b37102..f017988 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,1489 +1,1489 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
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-]
-
-[package.dependencies]
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-scipy = ">=1.1.0"
-
-[[package]]
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diff --git a/pyproject.toml b/pyproject.toml
index 06d68d2..1a9bbb2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,40 +1,40 @@
-[tool.poetry]
-name = "quacc"
-version = "0.1.0"
-description = ""
-authors = ["Lorenzo Volpi "]
-readme = "README.md"
-
-[tool.poetry.dependencies]
-python = "^3.11"
-quapy = "^0.1.7"
-pandas = "^2.0.3"
-jinja2 = "^3.1.2"
-pyyaml = "^6.0.1"
-logging = "^0.4.9.6"
-
-[tool.poetry.scripts]
-main = "quacc.main:main"
-comp = "quacc.main:estimate_comparison"
-tohost = "scp_sync:scp_sync_to_host"
-
-
-[tool.poetry.group.dev.dependencies]
-pytest = "^7.4.0"
-pylance = "^0.5.9"
-pytest-mock = "^3.11.1"
-pytest-cov = "^4.1.0"
-win11toast = "^0.32"
-tabulate = "^0.9.0"
-paramiko = "^3.3.1"
-
-[tool.pytest.ini_options]
-addopts = "--cov=quacc --capture=tee-sys"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
-
-[virtualenvs]
-in-project = true
-
+[tool.poetry]
+name = "quacc"
+version = "0.1.0"
+description = ""
+authors = ["Lorenzo Volpi "]
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = "^3.11"
+quapy = "^0.1.7"
+pandas = "^2.0.3"
+jinja2 = "^3.1.2"
+pyyaml = "^6.0.1"
+logging = "^0.4.9.6"
+
+[tool.poetry.scripts]
+main = "quacc.main:main"
+comp = "quacc.main:estimate_comparison"
+tohost = "scp_sync:scp_sync_to_host"
+
+
+[tool.poetry.group.dev.dependencies]
+pytest = "^7.4.0"
+pylance = "^0.5.9"
+pytest-mock = "^3.11.1"
+pytest-cov = "^4.1.0"
+win11toast = "^0.32"
+tabulate = "^0.9.0"
+paramiko = "^3.3.1"
+
+[tool.pytest.ini_options]
+addopts = "--cov=quacc --capture=tee-sys"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[virtualenvs]
+in-project = true
+
diff --git a/quacc.log b/quacc.log
index 5dbaffd..e2f6455 100644
--- a/quacc.log
+++ b/quacc.log
@@ -1,4671 +1,4671 @@
-----------------------------------------------------------------------------------------------------
-30/10/23 14:14:05| INFO: dataset imdb
-----------------------------------------------------------------------------------------------------
-30/10/23 14:14:24| INFO: dataset imdb
-30/10/23 14:14:31| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 14:14:35| WARNING: Method ref failed. Exception: 'dict' object has no attribute 'Keys'
-30/10/23 14:14:35| WARNING: Method atc_mc failed. Exception: 'dict' object has no attribute 'Keys'
-30/10/23 14:14:35| WARNING: Method atc_ne failed. Exception: 'dict' object has no attribute 'Keys'
-30/10/23 14:14:42| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:14:52| WARNING: Method mul_sld failed. Exception: 'dict' object has no attribute 'Keys'
-30/10/23 14:14:52| INFO: Dataset sample 0.90 of dataset imdb finished [took 21.1198s]
-30/10/23 14:14:52| WARNING: Dataset sample 0.90 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 14:14:52| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
-30/10/23 14:14:52| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 14:16:15| INFO: dataset imdb
-30/10/23 14:16:22| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 14:16:34| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:16:36| INFO: ref finished [took 11.6636s]
-30/10/23 14:16:39| INFO: atc_mc finished [took 14.8672s]
-30/10/23 14:16:39| INFO: atc_ne finished [took 14.8614s]
-30/10/23 14:16:49| INFO: mul_sld finished [took 24.6212s]
-30/10/23 14:16:49| INFO: Dataset sample 0.90 of dataset imdb finished [took 26.7805s]
-30/10/23 14:16:49| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 14:17:02| INFO: ref finished [took 13.0129s]
-30/10/23 14:17:06| INFO: atc_mc finished [took 16.0277s]
-30/10/23 14:17:06| INFO: atc_ne finished [took 16.1381s]
-30/10/23 14:17:17| INFO: mul_sld finished [took 28.1917s]
-30/10/23 14:17:23| INFO: mul_sld_bcts finished [took 33.5628s]
-30/10/23 14:17:23| INFO: Dataset sample 0.80 of dataset imdb finished [took 34.3680s]
-30/10/23 14:17:23| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 14:17:36| INFO: ref finished [took 12.5930s]
-30/10/23 14:17:40| INFO: atc_mc finished [took 16.1461s]
-30/10/23 14:17:40| INFO: atc_ne finished [took 16.1788s]
-30/10/23 14:17:52| INFO: mul_sld finished [took 28.5367s]
-30/10/23 14:18:00| INFO: mul_sld_bcts finished [took 36.0452s]
-30/10/23 14:18:00| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.7488s]
-30/10/23 14:18:00| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 14:18:13| INFO: ref finished [took 12.3910s]
-30/10/23 14:18:17| INFO: atc_mc finished [took 15.8804s]
-30/10/23 14:18:17| INFO: atc_ne finished [took 15.7115s]
-30/10/23 14:18:32| INFO: mul_sld_bcts finished [took 31.9997s]
-30/10/23 14:18:34| INFO: mul_sld finished [took 33.3735s]
-30/10/23 14:18:34| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.9557s]
-30/10/23 14:18:34| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 14:18:44| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:18:46| INFO: ref finished [took 11.7451s]
-30/10/23 14:18:50| INFO: atc_mc finished [took 15.2294s]
-30/10/23 14:18:50| INFO: atc_ne finished [took 15.1239s]
-30/10/23 14:18:55| INFO: mul_sld finished [took 21.3092s]
-30/10/23 14:18:55| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.7186s]
-30/10/23 14:18:55| ERROR: Configuration imdb_1prevs failed. Exception: 'mul_sld_bcts'
-30/10/23 14:18:55| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 14:32:36| INFO: dataset imdb
-30/10/23 14:32:43| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 14:32:56| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:32:58| INFO: ref finished [took 12.0197s]
-30/10/23 14:33:01| INFO: atc_mc finished [took 15.0884s]
-30/10/23 14:33:01| INFO: atc_ne finished [took 15.0503s]
-30/10/23 14:33:10| INFO: mul_sld finished [took 24.4470s]
-30/10/23 14:33:10| INFO: Dataset sample 0.90 of dataset imdb finished [took 26.6099s]
-30/10/23 14:33:10| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 14:33:23| INFO: ref finished [took 12.1812s]
-30/10/23 14:33:27| INFO: atc_mc finished [took 15.5589s]
-30/10/23 14:33:27| INFO: atc_ne finished [took 15.5283s]
-30/10/23 14:33:38| INFO: mul_sld finished [took 27.1282s]
-30/10/23 14:33:44| INFO: mul_sld_bcts finished [took 33.1098s]
-30/10/23 14:33:44| INFO: Dataset sample 0.80 of dataset imdb finished [took 33.9196s]
-30/10/23 14:33:44| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 14:33:57| INFO: ref finished [took 12.5959s]
-30/10/23 14:34:01| INFO: atc_mc finished [took 15.9389s]
-30/10/23 14:34:01| INFO: atc_ne finished [took 16.0795s]
-30/10/23 14:34:13| INFO: mul_sld finished [took 28.1568s]
-30/10/23 14:34:20| INFO: mul_sld_bcts finished [took 35.7147s]
-30/10/23 14:34:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.3828s]
-30/10/23 14:34:20| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 14:34:33| INFO: ref finished [took 12.2399s]
-30/10/23 14:34:37| INFO: atc_mc finished [took 15.4570s]
-30/10/23 14:34:37| INFO: atc_ne finished [took 15.5302s]
-30/10/23 14:34:52| INFO: mul_sld_bcts finished [took 31.1972s]
-30/10/23 14:34:54| INFO: mul_sld finished [took 32.9409s]
-30/10/23 14:34:54| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.5034s]
-30/10/23 14:34:54| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 14:35:04| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:35:06| INFO: ref finished [took 11.6742s]
-30/10/23 14:35:09| INFO: atc_mc finished [took 14.8324s]
-30/10/23 14:35:10| INFO: atc_ne finished [took 14.8661s]
-30/10/23 14:35:15| INFO: mul_sld finished [took 21.1356s]
-30/10/23 14:35:15| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.5814s]
-30/10/23 14:35:15| ERROR: Configuration imdb_1prevs failed. Exception: ('acc', None)
-30/10/23 14:35:15| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 14:37:47| INFO: dataset imdb
-30/10/23 14:37:54| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 14:38:07| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:38:09| INFO: ref finished [took 12.0443s]
-30/10/23 14:38:12| INFO: atc_mc finished [took 14.8929s]
-30/10/23 14:38:12| INFO: atc_ne finished [took 15.0431s]
-30/10/23 14:38:21| INFO: mul_sld finished [took 24.7987s]
-30/10/23 14:38:21| INFO: Dataset sample 0.90 of dataset imdb finished [took 27.0182s]
-30/10/23 14:38:21| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 14:38:35| INFO: ref finished [took 12.4504s]
-30/10/23 14:38:38| INFO: atc_mc finished [took 16.1560s]
-30/10/23 14:38:39| INFO: atc_ne finished [took 16.1785s]
-30/10/23 14:38:49| INFO: mul_sld finished [took 27.0617s]
-30/10/23 14:38:55| INFO: mul_sld_bcts finished [took 32.7384s]
-30/10/23 14:38:55| INFO: Dataset sample 0.80 of dataset imdb finished [took 33.5347s]
-30/10/23 14:38:55| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 14:39:08| INFO: ref finished [took 12.4381s]
-30/10/23 14:39:11| INFO: atc_mc finished [took 15.6709s]
-30/10/23 14:39:11| INFO: atc_ne finished [took 15.7319s]
-30/10/23 14:39:23| INFO: mul_sld finished [took 27.9301s]
-30/10/23 14:39:31| INFO: mul_sld_bcts finished [took 35.5094s]
-30/10/23 14:39:31| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.1333s]
-30/10/23 14:39:31| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 14:39:44| INFO: ref finished [took 12.0382s]
-30/10/23 14:39:47| INFO: atc_mc finished [took 15.0164s]
-30/10/23 14:39:47| INFO: atc_ne finished [took 15.1080s]
-30/10/23 14:40:02| INFO: mul_sld_bcts finished [took 30.9659s]
-30/10/23 14:40:04| INFO: mul_sld finished [took 32.9418s]
-30/10/23 14:40:04| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.4681s]
-30/10/23 14:40:04| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 14:40:14| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:40:17| INFO: ref finished [took 11.8501s]
-30/10/23 14:40:20| INFO: atc_mc finished [took 14.8473s]
-30/10/23 14:40:21| INFO: atc_ne finished [took 15.2000s]
-30/10/23 14:40:26| INFO: mul_sld finished [took 21.4799s]
-30/10/23 14:40:26| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.9220s]
-30/10/23 14:40:26| ERROR: Configuration imdb_1prevs failed. Exception: NDFrame.droplevel() got an unexpected keyword argument 'index'
-30/10/23 14:40:26| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 14:42:13| INFO: dataset imdb
-30/10/23 14:42:20| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 14:42:33| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:42:34| INFO: ref finished [took 12.1951s]
-30/10/23 14:42:38| INFO: atc_ne finished [took 15.3431s]
-30/10/23 14:42:38| INFO: atc_mc finished [took 15.4508s]
-30/10/23 14:42:47| INFO: mul_sld finished [took 25.0246s]
-30/10/23 14:42:47| INFO: Dataset sample 0.90 of dataset imdb finished [took 27.1381s]
-30/10/23 14:42:47| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 14:43:00| INFO: ref finished [took 12.3269s]
-30/10/23 14:43:04| INFO: atc_ne finished [took 15.9216s]
-30/10/23 14:43:04| INFO: atc_mc finished [took 16.1140s]
-30/10/23 14:43:16| INFO: mul_sld finished [took 28.0575s]
-30/10/23 14:43:22| INFO: mul_sld_bcts finished [took 33.9201s]
-30/10/23 14:43:22| INFO: Dataset sample 0.80 of dataset imdb finished [took 34.7703s]
-30/10/23 14:43:22| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 14:43:35| INFO: ref finished [took 12.6508s]
-30/10/23 14:43:39| INFO: atc_mc finished [took 16.0527s]
-30/10/23 14:43:39| INFO: atc_ne finished [took 16.0515s]
-30/10/23 14:43:50| INFO: mul_sld finished [took 28.1061s]
-30/10/23 14:43:57| INFO: mul_sld_bcts finished [took 34.9278s]
-30/10/23 14:43:57| INFO: Dataset sample 0.50 of dataset imdb finished [took 35.6587s]
-30/10/23 14:43:57| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 14:44:10| INFO: ref finished [took 12.0801s]
-30/10/23 14:44:14| INFO: atc_mc finished [took 15.4685s]
-30/10/23 14:44:14| INFO: atc_ne finished [took 15.4165s]
-30/10/23 14:44:29| INFO: mul_sld_bcts finished [took 31.5628s]
-30/10/23 14:44:31| INFO: mul_sld finished [took 33.3113s]
-30/10/23 14:44:31| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.8828s]
-30/10/23 14:44:31| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 14:44:41| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:44:44| INFO: ref finished [took 11.6822s]
-30/10/23 14:44:47| INFO: atc_mc finished [took 14.8091s]
-30/10/23 14:44:47| INFO: atc_ne finished [took 14.7900s]
-30/10/23 14:44:53| INFO: mul_sld finished [took 21.0390s]
-30/10/23 14:44:53| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.4515s]
-30/10/23 14:44:53| ERROR: Configuration imdb_1prevs failed. Exception: 'function' object has no attribute 'index'
-30/10/23 14:44:53| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 14:46:34| INFO: dataset imdb
-30/10/23 14:46:41| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 14:46:54| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:46:56| INFO: ref finished [took 12.5001s]
-30/10/23 14:46:59| INFO: atc_mc finished [took 15.5415s]
-30/10/23 14:46:59| INFO: atc_ne finished [took 15.6358s]
-30/10/23 14:47:08| INFO: mul_sld finished [took 24.5102s]
-30/10/23 14:47:08| INFO: Dataset sample 0.90 of dataset imdb finished [took 26.5553s]
-30/10/23 14:47:08| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 14:47:21| INFO: ref finished [took 12.0997s]
-30/10/23 14:47:24| INFO: atc_mc finished [took 15.4285s]
-30/10/23 14:47:24| INFO: atc_ne finished [took 15.5599s]
-30/10/23 14:47:36| INFO: mul_sld finished [took 27.6146s]
-30/10/23 14:47:43| INFO: mul_sld_bcts finished [took 34.2610s]
-30/10/23 14:47:43| INFO: Dataset sample 0.80 of dataset imdb finished [took 35.0096s]
-30/10/23 14:47:43| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 14:47:56| INFO: ref finished [took 12.1238s]
-30/10/23 14:48:00| INFO: atc_mc finished [took 15.6990s]
-30/10/23 14:48:00| INFO: atc_ne finished [took 15.8708s]
-30/10/23 14:48:11| INFO: mul_sld finished [took 28.0048s]
-30/10/23 14:48:20| INFO: mul_sld_bcts finished [took 36.1524s]
-30/10/23 14:48:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.8480s]
-30/10/23 14:48:20| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 14:48:32| INFO: ref finished [took 11.3690s]
-30/10/23 14:48:35| INFO: atc_mc finished [took 14.3092s]
-30/10/23 14:48:35| INFO: atc_ne finished [took 14.4043s]
-30/10/23 14:48:51| INFO: mul_sld_bcts finished [took 30.2595s]
-30/10/23 14:48:52| INFO: mul_sld finished [took 31.4270s]
-30/10/23 14:48:52| INFO: Dataset sample 0.20 of dataset imdb finished [took 31.9598s]
-30/10/23 14:48:52| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 14:49:02| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 14:49:04| INFO: ref finished [took 12.1449s]
-30/10/23 14:49:08| INFO: atc_mc finished [took 15.0332s]
-30/10/23 14:49:08| INFO: atc_ne finished [took 15.3463s]
-30/10/23 14:49:13| INFO: mul_sld finished [took 21.2802s]
-30/10/23 14:49:13| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.7079s]
-30/10/23 14:49:14| ERROR: Configuration imdb_1prevs failed. Exception: unsupported operand type(s) for -: 'list' and 'list'
-30/10/23 14:49:14| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 15:10:08| INFO: dataset imdb
-30/10/23 15:10:14| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 15:10:26| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 15:10:27| INFO: ref finished [took 10.8100s]
-30/10/23 15:10:30| INFO: atc_mc finished [took 13.5996s]
-30/10/23 15:10:30| INFO: atc_ne finished [took 13.6110s]
-30/10/23 15:10:39| INFO: mul_sld finished [took 22.7361s]
-30/10/23 15:10:39| INFO: Dataset sample 0.90 of dataset imdb finished [took 24.8056s]
-30/10/23 15:10:39| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 15:10:51| INFO: ref finished [took 10.9293s]
-30/10/23 15:10:54| INFO: atc_mc finished [took 13.8377s]
-30/10/23 15:10:54| INFO: atc_ne finished [took 13.9983s]
-30/10/23 15:11:05| INFO: mul_sld finished [took 25.1977s]
-30/10/23 15:11:11| INFO: mul_sld_bcts finished [took 31.1124s]
-30/10/23 15:11:11| INFO: Dataset sample 0.80 of dataset imdb finished [took 31.8294s]
-30/10/23 15:11:11| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 15:11:23| INFO: ref finished [took 11.0056s]
-30/10/23 15:11:26| INFO: atc_mc finished [took 14.3946s]
-30/10/23 15:11:27| INFO: atc_ne finished [took 14.6355s]
-30/10/23 15:11:38| INFO: mul_sld finished [took 26.2697s]
-30/10/23 15:11:45| INFO: mul_sld_bcts finished [took 33.8992s]
-30/10/23 15:11:45| INFO: Dataset sample 0.50 of dataset imdb finished [took 34.4963s]
-30/10/23 15:11:45| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 15:11:57| INFO: ref finished [took 10.9836s]
-30/10/23 15:12:00| INFO: atc_mc finished [took 13.8378s]
-30/10/23 15:12:00| INFO: atc_ne finished [took 13.8318s]
-30/10/23 15:12:16| INFO: mul_sld_bcts finished [took 29.9813s]
-30/10/23 15:12:17| INFO: mul_sld finished [took 30.7175s]
-30/10/23 15:12:17| INFO: Dataset sample 0.20 of dataset imdb finished [took 31.2508s]
-30/10/23 15:12:17| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 15:12:26| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 15:12:28| INFO: ref finished [took 10.4376s]
-30/10/23 15:12:31| INFO: atc_ne finished [took 13.3510s]
-30/10/23 15:12:31| INFO: atc_mc finished [took 13.5172s]
-30/10/23 15:12:37| INFO: mul_sld finished [took 19.7440s]
-30/10/23 15:12:37| INFO: Dataset sample 0.10 of dataset imdb finished [took 20.1519s]
-30/10/23 15:12:37| ERROR: Configuration imdb_1prevs failed. Exception: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
-30/10/23 15:12:37| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 17:12:41| INFO: dataset imdb
-30/10/23 17:12:48| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 17:13:01| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 17:13:03| INFO: ref finished [took 12.6699s]
-30/10/23 17:13:07| INFO: atc_ne finished [took 15.6073s]
-30/10/23 17:13:07| INFO: atc_mc finished [took 15.6695s]
-30/10/23 17:13:15| INFO: mul_sld finished [took 24.8617s]
-30/10/23 17:13:15| INFO: Dataset sample 0.90 of dataset imdb finished [took 27.6018s]
-30/10/23 17:13:15| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 17:13:29| INFO: ref finished [took 12.6205s]
-30/10/23 17:13:33| INFO: atc_mc finished [took 16.2005s]
-30/10/23 17:13:33| INFO: atc_ne finished [took 16.2091s]
-30/10/23 17:13:43| INFO: mul_sld finished [took 27.1113s]
-30/10/23 17:13:49| INFO: mul_sld_bcts finished [took 33.3939s]
-30/10/23 17:13:49| INFO: Dataset sample 0.80 of dataset imdb finished [took 34.1222s]
-30/10/23 17:13:49| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 17:14:04| INFO: ref finished [took 13.2345s]
-30/10/23 17:14:07| INFO: atc_mc finished [took 16.5475s]
-30/10/23 17:14:07| INFO: atc_ne finished [took 16.6557s]
-30/10/23 17:14:19| INFO: mul_sld finished [took 28.8817s]
-30/10/23 17:14:27| INFO: mul_sld_bcts finished [took 36.5726s]
-30/10/23 17:14:27| INFO: Dataset sample 0.50 of dataset imdb finished [took 37.2057s]
-30/10/23 17:14:27| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 17:14:39| INFO: ref finished [took 11.7051s]
-30/10/23 17:14:42| INFO: atc_mc finished [took 14.8335s]
-30/10/23 17:14:43| INFO: atc_ne finished [took 15.0826s]
-30/10/23 17:14:59| INFO: mul_sld_bcts finished [took 31.7685s]
-30/10/23 17:15:00| INFO: mul_sld finished [took 33.2861s]
-30/10/23 17:15:00| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.8225s]
-30/10/23 17:15:00| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 17:15:11| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 17:15:13| INFO: ref finished [took 12.0927s]
-30/10/23 17:15:17| INFO: atc_mc finished [took 15.4201s]
-30/10/23 17:15:17| INFO: atc_ne finished [took 15.5212s]
-30/10/23 17:15:23| INFO: mul_sld finished [took 21.7236s]
-30/10/23 17:15:23| INFO: Dataset sample 0.10 of dataset imdb finished [took 22.2065s]
-30/10/23 17:15:23| ERROR: Configuration imdb_1prevs failed. Exception: operands could not be broadcast together with shapes (0,) (0,21)
-30/10/23 17:15:23| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 17:16:39| INFO: dataset imdb
-30/10/23 17:16:46| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 17:16:58| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 17:17:00| INFO: ref finished [took 11.7575s]
-30/10/23 17:17:03| INFO: atc_ne finished [took 14.7709s]
-30/10/23 17:17:03| INFO: atc_mc finished [took 14.8925s]
-30/10/23 17:17:12| INFO: mul_sld finished [took 23.7037s]
-30/10/23 17:17:12| INFO: Dataset sample 0.90 of dataset imdb finished [took 25.8491s]
-30/10/23 17:17:12| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 17:17:25| INFO: ref finished [took 12.2081s]
-30/10/23 17:17:28| INFO: atc_ne finished [took 15.3145s]
-30/10/23 17:17:28| INFO: atc_mc finished [took 15.5166s]
-30/10/23 17:17:39| INFO: mul_sld finished [took 26.7520s]
-30/10/23 17:17:45| INFO: mul_sld_bcts finished [took 32.0850s]
-30/10/23 17:17:45| INFO: Dataset sample 0.80 of dataset imdb finished [took 32.8702s]
-30/10/23 17:17:45| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 17:17:57| INFO: ref finished [took 11.9494s]
-30/10/23 17:18:01| INFO: atc_mc finished [took 15.3034s]
-30/10/23 17:18:01| INFO: atc_ne finished [took 15.3254s]
-30/10/23 17:18:12| INFO: mul_sld finished [took 27.2902s]
-30/10/23 17:18:20| INFO: mul_sld_bcts finished [took 34.4237s]
-30/10/23 17:18:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 35.1216s]
-30/10/23 17:18:20| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 17:18:32| INFO: ref finished [took 11.7945s]
-30/10/23 17:18:35| INFO: atc_mc finished [took 14.9218s]
-30/10/23 17:18:36| INFO: atc_ne finished [took 14.9745s]
-30/10/23 17:18:51| INFO: mul_sld_bcts finished [took 30.7287s]
-30/10/23 17:18:53| INFO: mul_sld finished [took 32.5641s]
-30/10/23 17:18:53| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.0982s]
-30/10/23 17:18:53| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 17:19:02| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 17:19:05| INFO: ref finished [took 11.4568s]
-30/10/23 17:19:08| INFO: atc_mc finished [took 14.4778s]
-30/10/23 17:19:08| INFO: atc_ne finished [took 14.5099s]
-30/10/23 17:19:14| INFO: mul_sld finished [took 20.5183s]
-30/10/23 17:19:14| INFO: Dataset sample 0.10 of dataset imdb finished [took 20.9251s]
-30/10/23 17:19:14| ERROR: Configuration imdb_1prevs failed. Exception: operands could not be broadcast together with shapes (0,) (0,21)
-30/10/23 17:19:14| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-30/10/23 19:57:49| INFO: dataset imdb
-30/10/23 19:58:00| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 19:58:11| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 19:58:22| INFO: ref finished [took 20.9010s]
-30/10/23 19:58:29| INFO: atc_ne finished [took 27.8453s]
-30/10/23 19:58:29| INFO: atc_mc finished [took 28.1079s]
-30/10/23 19:58:37| INFO: mul_sld finished [took 36.1699s]
-30/10/23 19:58:37| INFO: Dataset sample 0.90 of dataset imdb finished [took 36.7140s]
-30/10/23 19:58:37| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 19:59:01| INFO: ref finished [took 23.2803s]
-30/10/23 19:59:09| INFO: atc_ne finished [took 31.1099s]
-30/10/23 19:59:09| INFO: atc_mc finished [took 31.5916s]
-30/10/23 19:59:19| INFO: mul_sld finished [took 41.5113s]
-30/10/23 19:59:24| INFO: mul_sld_bcts finished [took 46.6603s]
-30/10/23 19:59:24| INFO: Dataset sample 0.80 of dataset imdb finished [took 47.4989s]
-30/10/23 19:59:24| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 19:59:49| INFO: ref finished [took 23.6312s]
-30/10/23 19:59:57| INFO: atc_ne finished [took 31.5195s]
-30/10/23 19:59:57| INFO: atc_mc finished [took 31.8197s]
-30/10/23 20:00:08| INFO: mul_sld finished [took 42.8675s]
-30/10/23 20:00:15| INFO: mul_sld_bcts finished [took 50.5527s]
-30/10/23 20:00:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 51.3659s]
-30/10/23 20:00:16| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 20:00:41| INFO: ref finished [took 24.2178s]
-30/10/23 20:00:48| INFO: atc_mc finished [took 31.9886s]
-30/10/23 20:00:49| INFO: atc_ne finished [took 32.1537s]
-30/10/23 20:01:03| INFO: mul_sld_bcts finished [took 46.2477s]
-30/10/23 20:01:07| INFO: mul_sld finished [took 50.8912s]
-30/10/23 20:01:07| INFO: Dataset sample 0.20 of dataset imdb finished [took 51.4589s]
-30/10/23 20:01:07| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 20:01:18| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 20:01:30| INFO: ref finished [took 22.6404s]
-30/10/23 20:01:38| INFO: atc_mc finished [took 29.8371s]
-30/10/23 20:01:38| INFO: atc_ne finished [took 30.2098s]
-30/10/23 20:01:41| INFO: mul_sld finished [took 33.6271s]
-30/10/23 20:01:41| INFO: Dataset sample 0.10 of dataset imdb finished [took 34.1993s]
-30/10/23 20:01:42| ERROR: Configuration imdb_1prevs failed. Exception: operands could not be broadcast together with shapes (0,) (0,21)
-30/10/23 20:01:42| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 20:05:04| INFO: dataset imdb
-30/10/23 20:05:14| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 20:05:26| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 20:05:38| INFO: ref finished [took 22.7241s]
-30/10/23 20:05:45| INFO: atc_mc finished [took 29.9191s]
-30/10/23 20:05:45| INFO: atc_ne finished [took 29.8405s]
-30/10/23 20:05:52| INFO: mul_sld finished [took 37.4045s]
-30/10/23 20:05:52| INFO: Dataset sample 0.90 of dataset imdb finished [took 37.9554s]
-30/10/23 20:05:52| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 20:06:17| INFO: ref finished [took 23.2465s]
-30/10/23 20:06:25| INFO: atc_ne finished [took 31.0138s]
-30/10/23 20:06:25| INFO: atc_mc finished [took 31.1341s]
-30/10/23 20:06:34| INFO: mul_sld finished [took 40.8777s]
-30/10/23 20:06:40| INFO: mul_sld_bcts finished [took 46.7083s]
-30/10/23 20:06:40| INFO: Dataset sample 0.80 of dataset imdb finished [took 47.5062s]
-30/10/23 20:06:40| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:07:05| INFO: ref finished [took 24.3375s]
-30/10/23 20:07:15| INFO: atc_mc finished [took 33.8014s]
-30/10/23 20:07:15| INFO: atc_ne finished [took 33.7355s]
-30/10/23 20:07:25| INFO: mul_sld finished [took 44.2891s]
-30/10/23 20:07:32| INFO: mul_sld_bcts finished [took 51.2404s]
-30/10/23 20:07:32| INFO: Dataset sample 0.50 of dataset imdb finished [took 51.9917s]
-30/10/23 20:07:32| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 20:07:55| INFO: ref finished [took 21.6828s]
-30/10/23 20:08:01| INFO: atc_mc finished [took 28.2369s]
-30/10/23 20:08:01| INFO: atc_ne finished [took 28.4328s]
-30/10/23 20:08:15| INFO: mul_sld_bcts finished [took 41.9176s]
-30/10/23 20:08:18| INFO: mul_sld finished [took 45.4999s]
-30/10/23 20:08:18| INFO: Dataset sample 0.20 of dataset imdb finished [took 46.0301s]
-30/10/23 20:08:18| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 20:08:28| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 20:08:38| INFO: ref finished [took 19.4082s]
-30/10/23 20:08:45| INFO: atc_mc finished [took 26.2343s]
-30/10/23 20:08:45| INFO: atc_ne finished [took 26.2322s]
-30/10/23 20:08:48| INFO: mul_sld finished [took 29.8392s]
-30/10/23 20:08:48| INFO: Dataset sample 0.10 of dataset imdb finished [took 30.3563s]
-----------------------------------------------------------------------------------------------------
-30/10/23 20:29:28| INFO: dataset imdb
-30/10/23 20:29:38| INFO: Dataset sample 0.50 of dataset imdb started
- 30/10/23 20:29:59| INFO: ref finished [took 19.1581s]
- 30/10/23 20:30:06| INFO: atc_mc finished [took 26.3398s]
- 30/10/23 20:30:07| INFO: atc_ne finished [took 26.4359s]
-30/10/23 20:30:07| INFO: Dataset sample 0.50 of dataset imdb finished [took 28.7984s]
-----------------------------------------------------------------------------------------------------
-30/10/23 20:31:50| INFO: dataset imdb
-30/10/23 20:32:00| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:33:59|INFO: ref finished [took 118.1306s]
-----------------------------------------------------------------------------------------------------
-30/10/23 20:36:06| INFO: dataset imdb
-30/10/23 20:36:17| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:38:52|WARNING: Method ref failed. Exception: "['acc_score' 'f1_score' 'ref'] not in index"
-30/10/23 20:41:28|WARNING: Method atc_mc failed. Exception: "['acc' 'acc_score' 'atc_mc' 'f1' 'f1_score'] not in index"
-30/10/23 20:41:32|WARNING: Method atc_ne failed. Exception: "['acc' 'acc_score' 'atc_ne' 'f1' 'f1_score'] not in index"
-30/10/23 20:41:32| INFO: Dataset sample 0.50 of dataset imdb finished [took 315.4626s]
-30/10/23 20:41:32| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:41:32| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
-30/10/23 20:41:32| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 20:41:43| INFO: dataset imdb
-30/10/23 20:41:54| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:42:26| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
-30/10/23 20:43:01| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:43:08| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:43:08| INFO: Dataset sample 0.50 of dataset imdb finished [took 73.6011s]
-30/10/23 20:43:08| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:43:08| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
-30/10/23 20:43:08| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 20:44:25| INFO: dataset imdb
-30/10/23 20:44:35| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:44:37| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
-30/10/23 20:44:37| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:44:38| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:44:38| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.6758s]
-30/10/23 20:44:38| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:44:38| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
-30/10/23 20:44:38| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
-----------------------------------------------------------------------------------------------------
-30/10/23 20:47:08| INFO: dataset imdb
-30/10/23 20:47:18| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:47:20| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
-30/10/23 20:47:21| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:47:21| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:47:21| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.6147s]
-30/10/23 20:47:21| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:47:21| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
-----------------------------------------------------------------------------------------------------
-30/10/23 20:50:07| INFO: dataset imdb
-30/10/23 20:50:17| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:50:19| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
-30/10/23 20:50:20| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:50:20| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:50:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.5897s]
-30/10/23 20:50:20| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:50:20| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
-----------------------------------------------------------------------------------------------------
-30/10/23 20:51:29| INFO: dataset imdb
-30/10/23 20:51:39| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:51:42| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
-30/10/23 20:51:42| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:51:42| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
-30/10/23 20:51:42| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.5821s]
-30/10/23 20:51:42| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:51:42| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
-----------------------------------------------------------------------------------------------------
-30/10/23 20:56:28| INFO: dataset imdb
-30/10/23 20:56:38| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:56:40| WARNING: Method ref failed. Exception: cannot reshape array of size 1 into shape (1,2)
-30/10/23 20:56:40| WARNING: Method atc_mc failed. Exception: cannot reshape array of size 1 into shape (1,4)
-30/10/23 20:56:40| WARNING: Method atc_ne failed. Exception: cannot reshape array of size 1 into shape (1,4)
-30/10/23 20:56:40| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.6150s]
-30/10/23 20:56:40| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:56:40| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
-----------------------------------------------------------------------------------------------------
-30/10/23 20:57:13| INFO: dataset imdb
-30/10/23 20:57:23| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 20:59:40| WARNING: Method ref failed. Exception: cannot reshape array of size 1 into shape (1,2)
-30/10/23 20:59:51| WARNING: Method atc_mc failed. Exception: cannot reshape array of size 1 into shape (1,4)
-30/10/23 20:59:52| WARNING: Method atc_ne failed. Exception: cannot reshape array of size 1 into shape (1,4)
-30/10/23 20:59:52| INFO: Dataset sample 0.50 of dataset imdb finished [took 149.2395s]
-30/10/23 20:59:52| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 20:59:52| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
-----------------------------------------------------------------------------------------------------
-30/10/23 21:00:04| INFO: dataset imdb
-30/10/23 21:00:14| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:01:33| INFO: ref finished [took 78.2917s]
-30/10/23 21:01:42| INFO: atc_mc finished [took 86.9003s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:01:59| INFO: dataset imdb
-30/10/23 21:02:09| INFO: Dataset sample 0.50 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 21:04:09| INFO: dataset imdb
-30/10/23 21:04:19| INFO: Dataset sample 0.50 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 21:06:25| INFO: dataset imdb
-30/10/23 21:06:35| INFO: Dataset sample 0.50 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 21:07:33| INFO: dataset imdb
-30/10/23 21:07:43| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:07:45| WARNING: Method ref failed. Exception: setting an array element with a sequence.
-30/10/23 21:07:45| WARNING: Method atc_mc failed. Exception: setting an array element with a sequence.
-30/10/23 21:07:45| WARNING: Method atc_ne failed. Exception: setting an array element with a sequence.
-30/10/23 21:07:45| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.5382s]
-30/10/23 21:07:45| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
-30/10/23 21:07:45| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
-----------------------------------------------------------------------------------------------------
-30/10/23 21:09:07| INFO: dataset imdb
-30/10/23 21:09:16| INFO: Dataset sample 0.50 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 21:10:48| INFO: dataset imdb
-30/10/23 21:10:58| INFO: Dataset sample 0.50 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 21:18:53| INFO: dataset imdb
-30/10/23 21:19:03| INFO: Dataset sample 0.50 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 21:22:03| INFO: dataset imdb
-30/10/23 21:22:12| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:22:31| INFO: ref finished [took 17.0861s]
-30/10/23 21:22:37| INFO: atc_mc finished [took 23.6279s]
-30/10/23 21:22:38| INFO: atc_ne finished [took 23.7395s]
-30/10/23 21:22:38| INFO: Dataset sample 0.50 of dataset imdb finished [took 25.2007s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:29:55| INFO: dataset imdb
-30/10/23 21:30:05| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:30:23| INFO: ref finished [took 16.7801s]
-30/10/23 21:30:30| INFO: atc_mc finished [took 23.5645s]
-30/10/23 21:30:30| INFO: atc_ne finished [took 23.5639s]
-30/10/23 21:30:30| INFO: Dataset sample 0.50 of dataset imdb finished [took 25.0459s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:33:45| INFO: dataset imdb
-30/10/23 21:33:55| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:34:13| INFO: ref finished [took 17.0169s]
-30/10/23 21:34:20| INFO: atc_mc finished [took 23.4725s]
-30/10/23 21:34:20| INFO: atc_ne finished [took 23.5928s]
-30/10/23 21:34:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.9542s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:37:32| INFO: dataset imdb
-30/10/23 21:37:39| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:37:49| INFO: ref finished [took 8.9050s]
-30/10/23 21:37:52| INFO: atc_mc finished [took 11.7412s]
-30/10/23 21:37:52| INFO: atc_ne finished [took 11.7256s]
-30/10/23 21:37:52| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.9758s]
-30/10/23 21:37:53| ERROR: Configuration imdb_1prevs failed. Exception: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
-----------------------------------------------------------------------------------------------------
-30/10/23 21:39:14| INFO: dataset imdb
-30/10/23 21:39:21| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:39:31| INFO: ref finished [took 8.5615s]
-30/10/23 21:39:34| INFO: atc_mc finished [took 11.4156s]
-30/10/23 21:39:34| INFO: atc_ne finished [took 11.4156s]
-30/10/23 21:39:34| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.7024s]
-30/10/23 21:39:35| ERROR: Configuration imdb_1prevs failed. Exception: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
-----------------------------------------------------------------------------------------------------
-30/10/23 21:40:51| INFO: dataset imdb
-30/10/23 21:41:01| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:41:19| INFO: ref finished [took 16.7164s]
-30/10/23 21:41:26| INFO: atc_mc finished [took 23.3181s]
-30/10/23 21:41:26| INFO: atc_ne finished [took 23.4811s]
-30/10/23 21:41:26| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.9698s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:43:25| INFO: dataset imdb
-30/10/23 21:43:35| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:43:53| INFO: ref finished [took 16.9333s]
-30/10/23 21:44:00| INFO: atc_mc finished [took 23.4183s]
-30/10/23 21:44:00| INFO: atc_ne finished [took 23.4274s]
-30/10/23 21:44:00| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.9308s]
-30/10/23 21:44:19| ERROR: Configuration imdb_1prevs failed. Exception: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
-----------------------------------------------------------------------------------------------------
-30/10/23 21:45:16| INFO: dataset imdb
-30/10/23 21:45:26| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:45:44| INFO: ref finished [took 17.6768s]
-30/10/23 21:45:51| INFO: atc_mc finished [took 24.3756s]
-30/10/23 21:45:52| INFO: atc_ne finished [took 24.5307s]
-30/10/23 21:45:52| INFO: Dataset sample 0.50 of dataset imdb finished [took 25.8971s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:48:20| INFO: dataset imdb
-30/10/23 21:48:27| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:48:36| INFO: ref finished [took 8.6456s]
-30/10/23 21:48:39| INFO: atc_mc finished [took 11.2686s]
-30/10/23 21:48:39| INFO: atc_ne finished [took 11.3112s]
-30/10/23 21:48:39| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.5747s]
-30/10/23 21:48:40| ERROR: Configuration imdb_1prevs failed. Exception: NDFrame.droplevel() got an unexpected keyword argument 'index'
-----------------------------------------------------------------------------------------------------
-30/10/23 21:49:49| INFO: dataset imdb
-30/10/23 21:49:55| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:50:05| INFO: ref finished [took 8.6556s]
-30/10/23 21:50:08| INFO: atc_mc finished [took 11.6953s]
-30/10/23 21:50:08| INFO: atc_ne finished [took 11.6000s]
-30/10/23 21:50:08| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.8578s]
-30/10/23 21:50:09| ERROR: Configuration imdb_1prevs failed. Exception: 'NoneType' object has no attribute 'groupby'
-----------------------------------------------------------------------------------------------------
-30/10/23 21:50:57| INFO: dataset imdb
-30/10/23 21:51:07| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:51:25| INFO: ref finished [took 17.0426s]
-30/10/23 21:51:31| INFO: atc_mc finished [took 23.5734s]
-30/10/23 21:51:31| INFO: atc_ne finished [took 23.5276s]
-30/10/23 21:51:31| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.8200s]
-----------------------------------------------------------------------------------------------------
-30/10/23 21:55:21| INFO: dataset imdb
-30/10/23 21:55:27| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:55:37| INFO: ref finished [took 8.8453s]
-30/10/23 21:55:40| INFO: atc_mc finished [took 11.5585s]
-30/10/23 21:55:40| INFO: atc_ne finished [took 11.5871s]
-30/10/23 21:55:40| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.8416s]
-30/10/23 21:55:41| ERROR: Configuration imdb_1prevs failed. Exception: 'DatasetReport' object has no attribute 'fit_scores'
-----------------------------------------------------------------------------------------------------
-30/10/23 21:57:00| INFO: dataset imdb
-30/10/23 21:57:06| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:57:16| INFO: ref finished [took 8.5540s]
-30/10/23 21:57:19| INFO: atc_mc finished [took 11.4482s]
-30/10/23 21:57:19| INFO: atc_ne finished [took 11.5399s]
-30/10/23 21:57:19| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.7681s]
-30/10/23 21:57:20| ERROR: Configuration imdb_1prevs failed. Exception: 'DatasetReport' object has no attribute 'fit_scores'
-----------------------------------------------------------------------------------------------------
-30/10/23 21:57:38| INFO: dataset imdb
-30/10/23 21:57:45| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 21:57:55| INFO: ref finished [took 8.7982s]
-30/10/23 21:57:58| INFO: atc_mc finished [took 11.4787s]
-30/10/23 21:57:58| INFO: atc_ne finished [took 11.5419s]
-30/10/23 21:57:58| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.8803s]
-----------------------------------------------------------------------------------------------------
-30/10/23 22:00:05| INFO: dataset imdb
-30/10/23 22:00:12| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 22:00:21| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 22:00:22| INFO: ref finished [took 10.0983s]
-30/10/23 22:00:25| INFO: atc_mc finished [took 13.0928s]
-30/10/23 22:00:26| INFO: atc_ne finished [took 13.1088s]
-30/10/23 22:00:34| INFO: mul_sld finished [took 22.3228s]
-30/10/23 22:00:34| INFO: Dataset sample 0.90 of dataset imdb finished [took 22.7020s]
-30/10/23 22:00:34| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 22:00:46| INFO: ref finished [took 10.5937s]
-30/10/23 22:00:49| INFO: atc_mc finished [took 13.5008s]
-30/10/23 22:00:49| INFO: atc_ne finished [took 13.7521s]
-30/10/23 22:01:00| INFO: mul_sld finished [took 25.0319s]
-30/10/23 22:01:06| INFO: mul_sld_bcts finished [took 31.0525s]
-30/10/23 22:01:06| INFO: Dataset sample 0.80 of dataset imdb finished [took 31.7700s]
-30/10/23 22:01:06| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 22:01:17| INFO: ref finished [took 10.6316s]
-30/10/23 22:01:21| INFO: atc_ne finished [took 14.1054s]
-30/10/23 22:01:21| INFO: atc_mc finished [took 14.4357s]
-30/10/23 22:01:33| INFO: mul_sld finished [took 26.6800s]
-30/10/23 22:01:41| INFO: mul_sld_bcts finished [took 34.4745s]
-30/10/23 22:01:41| INFO: Dataset sample 0.50 of dataset imdb finished [took 35.1450s]
-30/10/23 22:01:41| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 22:01:53| INFO: ref finished [took 10.7413s]
-30/10/23 22:01:56| INFO: atc_ne finished [took 13.5169s]
-30/10/23 22:01:56| INFO: atc_mc finished [took 13.5849s]
-30/10/23 22:02:11| INFO: mul_sld_bcts finished [took 29.3981s]
-30/10/23 22:02:12| INFO: mul_sld finished [took 30.6705s]
-30/10/23 22:02:12| INFO: Dataset sample 0.20 of dataset imdb finished [took 31.2089s]
-30/10/23 22:02:12| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 22:02:22| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 22:02:24| INFO: ref finished [took 10.3435s]
-30/10/23 22:02:26| INFO: atc_mc finished [took 13.0763s]
-30/10/23 22:02:27| INFO: atc_ne finished [took 13.2013s]
-30/10/23 22:02:32| INFO: mul_sld finished [took 19.2237s]
-30/10/23 22:02:32| INFO: Dataset sample 0.10 of dataset imdb finished [took 19.7097s]
-----------------------------------------------------------------------------------------------------
-30/10/23 22:07:59| INFO: dataset imdb
-30/10/23 22:08:07| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 22:08:10| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:08:11| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:08:11| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:08:11| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-30/10/23 22:08:18| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 22:08:20| INFO: ref finished [took 11.3765s]
-30/10/23 22:08:23| INFO: atc_mc finished [took 14.2141s]
-30/10/23 22:08:23| INFO: atc_ne finished [took 14.0568s]
-30/10/23 22:08:31| INFO: mul_sld finished [took 23.9496s]
-30/10/23 22:08:31| INFO: Dataset sample 0.90 of dataset imdb finished [took 24.5121s]
-30/10/23 22:08:31| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 22:08:48| INFO: ref finished [took 14.8939s]
-30/10/23 22:08:52| INFO: atc_mc finished [took 18.5014s]
-30/10/23 22:08:52| INFO: atc_ne finished [took 18.4609s]
-30/10/23 22:09:05| INFO: mul_sld finished [took 32.9898s]
-30/10/23 22:09:12| INFO: mul_sld_bcts finished [took 39.3492s]
-30/10/23 22:11:48| INFO: bin_sld_bcts finished [took 195.8293s]
-30/10/23 22:11:49| INFO: bin_sld finished [took 196.6861s]
-30/10/23 22:12:44| INFO: mul_sld_gs finished [took 250.9835s]
-30/10/23 22:16:16| INFO: bin_sld_gs finished [took 462.9748s]
-30/10/23 22:16:16| INFO: Dataset sample 0.80 of dataset imdb finished [took 464.4318s]
-30/10/23 22:16:16| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 22:16:33| INFO: ref finished [took 15.2921s]
-30/10/23 22:16:37| INFO: atc_mc finished [took 18.9592s]
-30/10/23 22:16:37| INFO: atc_ne finished [took 19.1317s]
-30/10/23 22:16:50| INFO: mul_sld finished [took 33.4304s]
-30/10/23 22:16:59| INFO: mul_sld_bcts finished [took 42.3496s]
-30/10/23 22:19:33| INFO: bin_sld finished [took 196.1571s]
-30/10/23 22:19:36| INFO: bin_sld_bcts finished [took 199.7857s]
-30/10/23 22:20:39| INFO: mul_sld_gs finished [took 261.6674s]
-30/10/23 22:23:46| INFO: bin_sld_gs finished [took 449.3788s]
-30/10/23 22:23:46| INFO: Dataset sample 0.50 of dataset imdb finished [took 450.7045s]
-30/10/23 22:23:46| INFO: Dataset sample 0.20 of dataset imdb started
-30/10/23 22:24:05| INFO: ref finished [took 16.4122s]
-30/10/23 22:24:09| INFO: atc_mc finished [took 20.4920s]
-30/10/23 22:24:09| INFO: atc_ne finished [took 20.3723s]
-30/10/23 22:24:28| INFO: mul_sld_bcts finished [took 40.3400s]
-30/10/23 22:24:30| INFO: mul_sld finished [took 43.2311s]
-30/10/23 22:27:16| INFO: bin_sld_bcts finished [took 208.6113s]
-30/10/23 22:27:21| INFO: bin_sld finished [took 214.1596s]
-30/10/23 22:28:17| INFO: mul_sld_gs finished [took 269.1075s]
-30/10/23 22:34:19| INFO: bin_sld_gs finished [took 630.9727s]
-30/10/23 22:34:19| INFO: Dataset sample 0.20 of dataset imdb finished [took 632.2728s]
-30/10/23 22:34:19| INFO: Dataset sample 0.10 of dataset imdb started
-30/10/23 22:34:23| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-30/10/23 22:34:23| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-30/10/23 22:34:26| WARNING: Method bin_sld_bcts failed. Exception: Cannot have number of splits n_splits=5 greater than the number of samples: n_samples=4.
-30/10/23 22:34:31| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 22:34:34| INFO: ref finished [took 13.7988s]
-30/10/23 22:34:37| INFO: atc_mc finished [took 16.7490s]
-30/10/23 22:34:38| INFO: atc_ne finished [took 16.7307s]
-30/10/23 22:34:43| INFO: mul_sld finished [took 23.6079s]
-30/10/23 22:36:42| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-30/10/23 22:36:42| INFO: Dataset sample 0.10 of dataset imdb finished [took 143.1097s]
-----------------------------------------------------------------------------------------------------
-30/10/23 22:49:25| INFO: dataset imdb
-30/10/23 22:49:37| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 22:49:42| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-30/10/23 22:49:43| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:49:43| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:49:43| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:49:51| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 22:50:02| INFO: ref finished [took 22.5398s]
-30/10/23 22:50:09| INFO: atc_mc finished [took 29.3095s]
-30/10/23 22:50:09| INFO: atc_ne finished [took 29.2984s]
-30/10/23 22:50:16| INFO: mul_sld finished [took 37.6287s]
-30/10/23 22:50:16| INFO: Dataset sample 0.90 of dataset imdb finished [took 38.3452s]
-----------------------------------------------------------------------------------------------------
-30/10/23 22:53:57| INFO: dataset imdb
-30/10/23 22:54:09| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 22:54:13| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-30/10/23 22:54:14| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:54:15| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:54:15| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 22:54:22| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 22:54:33| INFO: ref finished [took 22.4225s]
-30/10/23 22:54:40| INFO: atc_ne finished [took 29.0085s]
-30/10/23 22:54:41| INFO: atc_mc finished [took 29.6620s]
-30/10/23 22:54:48| INFO: mul_sld finished [took 37.9580s]
-30/10/23 22:54:48| INFO: Dataset sample 0.90 of dataset imdb finished [took 38.6632s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:02:33| INFO: dataset imdb
-30/10/23 23:02:45| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 23:02:50| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-30/10/23 23:02:51| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 23:02:52| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 23:02:52| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 23:02:59| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 23:03:10| INFO: ref finished [took 23.4021s]
-30/10/23 23:03:17| INFO: atc_mc finished [took 30.1849s]
-30/10/23 23:03:18| INFO: atc_ne finished [took 30.4116s]
-30/10/23 23:03:25| INFO: mul_sld finished [took 38.6513s]
-30/10/23 23:03:25| INFO: Dataset sample 0.90 of dataset imdb finished [took 39.3497s]
-30/10/23 23:07:32| INFO: Dataset sample 0.80 of dataset imdb started
-----------------------------------------------------------------------------------------------------
-30/10/23 23:08:15| INFO: dataset imdb
-30/10/23 23:08:26| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:08:51| INFO: ref finished [took 23.6855s]
-30/10/23 23:08:59| INFO: atc_mc finished [took 31.1520s]
-30/10/23 23:08:59| INFO: atc_ne finished [took 31.1659s]
-30/10/23 23:09:10| INFO: mul_sld finished [took 42.2066s]
-30/10/23 23:09:21| INFO: mul_sld_bcts finished [took 52.9631s]
-30/10/23 23:09:21| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.5286s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:14:11| INFO: dataset imdb
-30/10/23 23:14:22| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:14:47| INFO: ref finished [took 22.8152s]
-30/10/23 23:14:55| INFO: atc_mc finished [took 31.2100s]
-30/10/23 23:14:55| INFO: atc_ne finished [took 31.2325s]
-30/10/23 23:15:06| INFO: mul_sld finished [took 42.5389s]
-30/10/23 23:15:16| INFO: mul_sld_bcts finished [took 52.7119s]
-30/10/23 23:15:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.2106s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:16:16| INFO: dataset imdb
-30/10/23 23:16:27| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:16:51| INFO: ref finished [took 22.6482s]
-30/10/23 23:17:00| INFO: atc_ne finished [took 30.5701s]
-30/10/23 23:17:00| INFO: atc_mc finished [took 30.9988s]
-30/10/23 23:17:10| INFO: mul_sld finished [took 41.9572s]
-30/10/23 23:17:21| INFO: mul_sld_bcts finished [took 52.6091s]
-30/10/23 23:17:21| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.1182s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:20:27| INFO: dataset imdb
-30/10/23 23:20:38| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:21:02| INFO: ref finished [took 22.7779s]
-30/10/23 23:21:10| INFO: atc_mc finished [took 30.4191s]
-30/10/23 23:21:10| INFO: atc_ne finished [took 30.8097s]
-30/10/23 23:21:20| INFO: mul_sld finished [took 41.5927s]
-30/10/23 23:21:32| INFO: mul_sld_bcts finished [took 52.6374s]
-30/10/23 23:21:32| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.1125s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:24:11| INFO: dataset imdb
-30/10/23 23:24:22| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:24:46| INFO: ref finished [took 23.2007s]
-30/10/23 23:24:54| INFO: atc_ne finished [took 30.9437s]
-30/10/23 23:24:55| INFO: atc_mc finished [took 31.6008s]
-30/10/23 23:25:05| INFO: mul_sld finished [took 42.0673s]
-30/10/23 23:25:16| INFO: mul_sld_bcts finished [took 52.6228s]
-30/10/23 23:25:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.0611s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:33:01| INFO: dataset imdb
-30/10/23 23:33:11| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:33:36| INFO: ref finished [took 22.9215s]
-30/10/23 23:33:44| INFO: atc_mc finished [took 30.5897s]
-30/10/23 23:33:44| INFO: atc_ne finished [took 30.4788s]
-30/10/23 23:33:55| INFO: mul_sld finished [took 42.0598s]
-30/10/23 23:34:05| INFO: mul_sld_bcts finished [took 52.1772s]
-30/10/23 23:34:05| INFO: Dataset sample 0.50 of dataset imdb finished [took 53.6878s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:38:11| INFO: dataset imdb
-30/10/23 23:38:22| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:38:47| INFO: ref finished [took 22.8046s]
-30/10/23 23:38:56| INFO: atc_mc finished [took 31.5660s]
-30/10/23 23:38:56| INFO: atc_ne finished [took 31.5269s]
-30/10/23 23:39:06| INFO: mul_sld finished [took 42.2553s]
-30/10/23 23:39:16| INFO: mul_sld_bcts finished [took 52.2602s]
-30/10/23 23:39:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 53.7890s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:46:40| INFO: dataset imdb
-30/10/23 23:46:51| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:47:16| INFO: ref finished [took 22.8069s]
-30/10/23 23:47:24| INFO: atc_mc finished [took 30.7916s]
-30/10/23 23:47:24| INFO: atc_ne finished [took 30.8668s]
-30/10/23 23:47:35| INFO: mul_sld finished [took 42.2809s]
-30/10/23 23:47:45| INFO: mul_sld_bcts finished [took 52.5498s]
-30/10/23 23:47:45| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.0424s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:50:43| INFO: dataset imdb
-30/10/23 23:50:50| INFO: Dataset sample 0.50 of dataset imdb started
-30/10/23 23:51:04| INFO: ref finished [took 12.0863s]
-30/10/23 23:51:07| INFO: atc_ne finished [took 15.0218s]
-30/10/23 23:51:08| INFO: atc_mc finished [took 15.7900s]
-30/10/23 23:51:20| INFO: mul_sld finished [took 28.7221s]
-30/10/23 23:51:31| INFO: mul_sld_bcts finished [took 39.4698s]
-30/10/23 23:51:31| INFO: Dataset sample 0.50 of dataset imdb finished [took 40.8506s]
-----------------------------------------------------------------------------------------------------
-30/10/23 23:52:29| INFO: dataset imdb
-30/10/23 23:52:37| INFO: Dataset sample 0.90 of dataset imdb started
-30/10/23 23:52:40| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 23:52:41| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 23:52:41| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-30/10/23 23:52:41| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-30/10/23 23:52:48| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-30/10/23 23:52:50| INFO: ref finished [took 12.4800s]
-30/10/23 23:52:53| INFO: atc_mc finished [took 15.1770s]
-30/10/23 23:52:54| INFO: atc_ne finished [took 15.2184s]
-30/10/23 23:53:02| INFO: mul_sld finished [took 24.9402s]
-30/10/23 23:53:02| INFO: Dataset sample 0.90 of dataset imdb finished [took 25.4588s]
-30/10/23 23:53:02| INFO: Dataset sample 0.80 of dataset imdb started
-30/10/23 23:53:20| INFO: ref finished [took 16.3699s]
-30/10/23 23:53:25| INFO: atc_ne finished [took 20.5069s]
-30/10/23 23:53:25| INFO: atc_mc finished [took 20.7398s]
-30/10/23 23:53:38| INFO: mul_sld finished [took 35.3572s]
-30/10/23 23:53:45| INFO: mul_sld_bcts finished [took 41.8712s]
-30/10/23 23:56:35| INFO: bin_sld finished [took 212.1758s]
-30/10/23 23:56:36| INFO: bin_sld_bcts finished [took 213.3641s]
-30/10/23 23:57:38| INFO: mul_sld_gs finished [took 274.6360s]
-31/10/23 00:01:13| INFO: bin_sld_gs finished [took 490.0221s]
-31/10/23 00:01:13| INFO: Dataset sample 0.80 of dataset imdb finished [took 491.4099s]
-31/10/23 00:01:13| INFO: Dataset sample 0.50 of dataset imdb started
-31/10/23 00:01:32| INFO: ref finished [took 17.1003s]
-31/10/23 00:01:37| INFO: atc_ne finished [took 21.2159s]
-31/10/23 00:01:37| INFO: atc_mc finished [took 21.6794s]
-31/10/23 00:01:51| INFO: mul_sld finished [took 37.3507s]
-31/10/23 00:02:01| INFO: mul_sld_bcts finished [took 46.7227s]
-31/10/23 00:04:46| INFO: bin_sld finished [took 211.9902s]
-31/10/23 00:04:48| INFO: bin_sld_bcts finished [took 213.3398s]
-31/10/23 00:05:55| INFO: mul_sld_gs finished [took 279.4401s]
-31/10/23 00:08:56| INFO: bin_sld_gs finished [took 461.6571s]
-31/10/23 00:08:56| INFO: Dataset sample 0.50 of dataset imdb finished [took 462.8616s]
-31/10/23 00:08:56| INFO: Dataset sample 0.20 of dataset imdb started
-31/10/23 00:09:15| INFO: ref finished [took 17.3643s]
-31/10/23 00:09:20| INFO: atc_mc finished [took 21.0373s]
-31/10/23 00:09:20| INFO: atc_ne finished [took 21.2599s]
-31/10/23 00:09:38| INFO: mul_sld_bcts finished [took 41.0473s]
-31/10/23 00:09:41| INFO: mul_sld finished [took 43.7800s]
-31/10/23 00:12:30| INFO: bin_sld_bcts finished [took 212.8639s]
-31/10/23 00:12:32| INFO: bin_sld finished [took 215.5704s]
-31/10/23 00:13:29| INFO: mul_sld_gs finished [took 270.7454s]
-31/10/23 00:19:19| INFO: bin_sld_gs finished [took 621.7089s]
-31/10/23 00:19:19| INFO: Dataset sample 0.20 of dataset imdb finished [took 623.1501s]
-31/10/23 00:19:19| INFO: Dataset sample 0.10 of dataset imdb started
-31/10/23 00:19:24| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
-31/10/23 00:19:24| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-31/10/23 00:19:26| WARNING: Method bin_sld_bcts failed. Exception: Cannot have number of splits n_splits=5 greater than the number of samples: n_samples=4.
-31/10/23 00:19:31| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
-31/10/23 00:19:35| INFO: ref finished [took 13.7926s]
-31/10/23 00:19:38| INFO: atc_mc finished [took 16.8128s]
-31/10/23 00:19:39| INFO: atc_ne finished [took 16.9032s]
-31/10/23 00:19:44| INFO: mul_sld finished [took 23.7188s]
-31/10/23 00:21:43| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-31/10/23 00:21:43| INFO: Dataset sample 0.10 of dataset imdb finished [took 143.1001s]
-----------------------------------------------------------------------------------------------------
-31/10/23 01:36:56| INFO: dataset imdb
-31/10/23 01:37:04| INFO: Dataset sample 0.90 of dataset imdb started
-31/10/23 01:37:13| WARNING: Method bin_sld_bcts failed. Exception: fun: nan
- hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
- jac: array([ 1.06687127, -0.00373246, 0.00373246])
- message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
- nfev: 53
- nit: 34
- njev: 53
- status: 2
- success: False
- x: array([ 0.11536329, -12.93833991, 12.93833991])
-31/10/23 01:37:24| INFO: ref finished [took 15.9844s]
-31/10/23 01:37:28| INFO: atc_mc finished [took 19.7000s]
-31/10/23 01:37:28| INFO: atc_ne finished [took 19.4612s]
-31/10/23 01:37:39| INFO: mul_sld finished [took 33.2999s]
-31/10/23 01:37:49| INFO: mul_sld_bcts finished [took 43.1402s]
-31/10/23 01:40:23| INFO: bin_sld finished [took 197.7518s]
-31/10/23 01:41:23| INFO: mul_sld_gs finished [took 256.4496s]
-31/10/23 01:42:49| INFO: bin_sld_gs finished [took 342.7515s]
-31/10/23 01:42:49| INFO: Dataset sample 0.90 of dataset imdb finished [took 344.8637s]
-31/10/23 01:42:49| INFO: Dataset sample 0.50 of dataset imdb started
-31/10/23 01:43:10| INFO: ref finished [took 17.6503s]
-31/10/23 01:43:15| INFO: atc_mc finished [took 21.9510s]
-31/10/23 01:43:15| INFO: atc_ne finished [took 21.5680s]
-31/10/23 01:43:29| INFO: mul_sld finished [took 38.2515s]
-31/10/23 01:43:41| INFO: mul_sld_bcts finished [took 48.9560s]
-31/10/23 01:46:29| INFO: bin_sld_bcts finished [took 217.8464s]
-31/10/23 01:46:29| INFO: bin_sld finished [took 218.6211s]
-31/10/23 01:47:51| INFO: mul_sld_gs finished [took 298.6694s]
-31/10/23 01:50:25| INFO: bin_sld_gs finished [took 452.8300s]
-31/10/23 01:50:25| INFO: Dataset sample 0.50 of dataset imdb finished [took 455.3596s]
-31/10/23 01:50:28| ERROR: Configuration imdb_2prevs failed. Exception: could not broadcast input array from shape (2100,7) into shape (2100,)
-----------------------------------------------------------------------------------------------------
-31/10/23 02:13:21| INFO: dataset imdb
-31/10/23 02:13:29| INFO: Dataset sample 0.90 of dataset imdb started
-31/10/23 02:13:37| WARNING: Method bin_sld_bcts failed. Exception: fun: nan
- hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
- jac: array([ 1.06687127, -0.00373246, 0.00373246])
- message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
- nfev: 53
- nit: 34
- njev: 53
- status: 2
- success: False
- x: array([ 0.11536329, -12.93833991, 12.93833991])
-31/10/23 02:13:48| INFO: ref finished [took 16.5509s]
-31/10/23 02:13:52| INFO: atc_mc finished [took 20.3138s]
-31/10/23 02:13:52| INFO: atc_ne finished [took 20.1191s]
-31/10/23 02:14:02| INFO: mul_sld finished [took 32.5158s]
-31/10/23 02:14:12| INFO: mul_sld_bcts finished [took 42.0654s]
-31/10/23 02:16:44| INFO: bin_sld finished [took 193.9189s]
-31/10/23 02:17:44| INFO: mul_sld_gs finished [took 252.9066s]
-31/10/23 02:19:11| INFO: bin_sld_gs finished [took 339.9813s]
-31/10/23 02:19:11| INFO: Dataset sample 0.90 of dataset imdb finished [took 341.6967s]
-31/10/23 02:19:11| INFO: Dataset sample 0.50 of dataset imdb started
-31/10/23 02:19:30| INFO: ref finished [took 16.1334s]
-31/10/23 02:19:35| INFO: atc_mc finished [took 20.5691s]
-31/10/23 02:19:35| INFO: atc_ne finished [took 20.0126s]
-31/10/23 02:19:49| INFO: mul_sld finished [took 36.4597s]
-31/10/23 02:20:02| INFO: mul_sld_bcts finished [took 48.7131s]
-31/10/23 02:22:38| INFO: bin_sld finished [took 205.8577s]
-31/10/23 02:22:41| INFO: bin_sld_bcts finished [took 208.1999s]
-31/10/23 02:23:58| INFO: mul_sld_gs finished [took 284.9247s]
-31/10/23 02:26:26| INFO: bin_sld_gs finished [took 432.5665s]
-31/10/23 02:26:26| INFO: Dataset sample 0.50 of dataset imdb finished [took 435.0679s]
-----------------------------------------------------------------------------------------------------
-31/10/23 03:05:44| INFO: dataset rcv1_CCAT
-31/10/23 03:05:49| INFO: Dataset sample 0.90 of dataset rcv1_CCAT started
-31/10/23 03:06:59| INFO: kfcv finished [took 59.0143s]
-31/10/23 03:06:59| INFO: ref finished [took 56.9074s]
-31/10/23 03:07:03| INFO: doc_feat finished [took 49.0683s]
-31/10/23 03:07:05| INFO: atc_mc finished [took 59.3988s]
-31/10/23 03:07:07| INFO: atc_ne finished [took 58.0283s]
-31/10/23 03:07:09| INFO: mul_sld finished [took 76.8284s]
-31/10/23 03:07:19| INFO: mul_sld_bcts finished [took 84.0129s]
-31/10/23 03:09:51| INFO: bin_sld_bcts finished [took 237.9395s]
-31/10/23 03:09:53| INFO: bin_sld finished [took 242.1415s]
-31/10/23 03:10:13| INFO: mul_sld_gs finished [took 255.3743s]
-31/10/23 03:13:59| INFO: bin_sld_gs finished [took 483.0217s]
-31/10/23 03:13:59| INFO: Dataset sample 0.90 of dataset rcv1_CCAT finished [took 489.9328s]
-31/10/23 03:13:59| INFO: Dataset sample 0.80 of dataset rcv1_CCAT started
-31/10/23 03:15:04| INFO: ref finished [took 53.0703s]
-31/10/23 03:15:05| INFO: kfcv finished [took 55.9779s]
-31/10/23 03:15:05| INFO: doc_feat finished [took 48.1315s]
-31/10/23 03:15:10| INFO: atc_mc finished [took 56.8062s]
-31/10/23 03:15:11| INFO: atc_ne finished [took 55.9933s]
-31/10/23 03:15:20| INFO: mul_sld finished [took 77.2840s]
-31/10/23 03:15:25| INFO: mul_sld_bcts finished [took 80.0502s]
-31/10/23 03:17:55| INFO: bin_sld finished [took 233.0173s]
-31/10/23 03:17:55| INFO: bin_sld_bcts finished [took 231.2358s]
-31/10/23 03:18:59| INFO: mul_sld_gs finished [took 291.7573s]
-31/10/23 03:21:50| INFO: bin_sld_gs finished [took 463.8743s]
-31/10/23 03:21:50| INFO: Dataset sample 0.80 of dataset rcv1_CCAT finished [took 470.4706s]
-31/10/23 03:21:50| INFO: Dataset sample 0.70 of dataset rcv1_CCAT started
-31/10/23 03:22:52| INFO: doc_feat finished [took 46.9563s]
-31/10/23 03:22:53| INFO: ref finished [took 52.8185s]
-31/10/23 03:22:54| INFO: kfcv finished [took 55.3202s]
-31/10/23 03:22:57| INFO: atc_mc finished [took 55.1482s]
-31/10/23 03:22:58| INFO: atc_ne finished [took 54.7420s]
-31/10/23 03:23:09| INFO: mul_sld finished [took 76.8111s]
-31/10/23 03:23:14| INFO: mul_sld_bcts finished [took 80.0460s]
-31/10/23 03:25:43| INFO: bin_sld finished [took 231.7146s]
-31/10/23 03:25:44| INFO: bin_sld_bcts finished [took 230.9954s]
-31/10/23 03:26:53| INFO: mul_sld_gs finished [took 296.5824s]
-31/10/23 03:29:12| INFO: bin_sld_gs finished [took 437.2666s]
-31/10/23 03:29:12| INFO: Dataset sample 0.70 of dataset rcv1_CCAT finished [took 442.6584s]
-31/10/23 03:29:12| INFO: Dataset sample 0.60 of dataset rcv1_CCAT started
-31/10/23 03:30:14| INFO: doc_feat finished [took 47.2841s]
-31/10/23 03:30:15| INFO: ref finished [took 52.5819s]
-31/10/23 03:30:16| INFO: kfcv finished [took 54.9735s]
-31/10/23 03:30:19| INFO: atc_mc finished [took 55.5994s]
-31/10/23 03:30:20| INFO: atc_ne finished [took 55.0062s]
-31/10/23 03:30:30| INFO: mul_sld finished [took 75.3263s]
-31/10/23 03:30:37| INFO: mul_sld_bcts finished [took 80.4052s]
-31/10/23 03:33:04| INFO: bin_sld finished [took 229.9416s]
-31/10/23 03:33:05| INFO: bin_sld_bcts finished [took 229.0971s]
-31/10/23 03:34:12| INFO: mul_sld_gs finished [took 292.9916s]
-31/10/23 03:37:15| INFO: bin_sld_gs finished [took 477.2157s]
-31/10/23 03:37:15| INFO: Dataset sample 0.60 of dataset rcv1_CCAT finished [took 482.5150s]
-31/10/23 03:37:15| INFO: Dataset sample 0.50 of dataset rcv1_CCAT started
-31/10/23 03:38:17| INFO: doc_feat finished [took 47.6798s]
-31/10/23 03:38:17| INFO: ref finished [took 52.2283s]
-31/10/23 03:38:18| INFO: kfcv finished [took 54.3535s]
-31/10/23 03:38:22| INFO: atc_mc finished [took 55.4316s]
-31/10/23 03:38:23| INFO: atc_ne finished [took 55.3697s]
-31/10/23 03:38:32| INFO: mul_sld finished [took 74.3762s]
-31/10/23 03:38:39| INFO: mul_sld_bcts finished [took 79.7216s]
-31/10/23 03:41:05| INFO: bin_sld finished [took 228.4963s]
-31/10/23 03:41:08| INFO: bin_sld_bcts finished [took 230.0901s]
-31/10/23 03:42:09| INFO: mul_sld_gs finished [took 287.8477s]
-31/10/23 03:45:08| INFO: bin_sld_gs finished [took 467.2633s]
-31/10/23 03:45:08| INFO: Dataset sample 0.50 of dataset rcv1_CCAT finished [took 472.6090s]
-31/10/23 03:45:08| INFO: Dataset sample 0.40 of dataset rcv1_CCAT started
-31/10/23 03:46:08| INFO: doc_feat finished [took 47.0674s]
-31/10/23 03:46:09| INFO: ref finished [took 51.5844s]
-31/10/23 03:46:09| INFO: kfcv finished [took 53.6481s]
-31/10/23 03:46:14| INFO: atc_mc finished [took 55.3679s]
-31/10/23 03:46:14| INFO: atc_ne finished [took 54.6174s]
-31/10/23 03:46:21| INFO: mul_sld finished [took 71.5925s]
-31/10/23 03:46:29| INFO: mul_sld_bcts finished [took 77.5938s]
-31/10/23 03:48:55| INFO: bin_sld finished [took 226.3217s]
-31/10/23 03:48:57| INFO: bin_sld_bcts finished [took 226.5561s]
-31/10/23 03:50:04| INFO: mul_sld_gs finished [took 289.8958s]
-31/10/23 03:53:13| INFO: bin_sld_gs finished [took 479.9650s]
-31/10/23 03:53:13| INFO: Dataset sample 0.40 of dataset rcv1_CCAT finished [took 485.0438s]
-31/10/23 03:53:13| INFO: Dataset sample 0.30 of dataset rcv1_CCAT started
-31/10/23 03:54:15| INFO: doc_feat finished [took 47.1959s]
-31/10/23 03:54:16| INFO: ref finished [took 52.7452s]
-31/10/23 03:54:17| INFO: kfcv finished [took 55.3715s]
-31/10/23 03:54:20| INFO: atc_mc finished [took 55.5749s]
-31/10/23 03:54:21| INFO: atc_ne finished [took 54.8719s]
-31/10/23 03:54:29| INFO: mul_sld finished [took 74.1932s]
-31/10/23 03:54:37| INFO: mul_sld_bcts finished [took 80.1150s]
-31/10/23 03:57:01| INFO: bin_sld finished [took 227.2338s]
-31/10/23 03:57:06| INFO: bin_sld_bcts finished [took 229.7342s]
-31/10/23 03:58:13| INFO: mul_sld_gs finished [took 293.4750s]
-31/10/23 04:00:50| INFO: bin_sld_gs finished [took 451.3322s]
-31/10/23 04:00:50| INFO: Dataset sample 0.30 of dataset rcv1_CCAT finished [took 456.9583s]
-31/10/23 04:00:50| INFO: Dataset sample 0.20 of dataset rcv1_CCAT started
-31/10/23 04:01:54| INFO: doc_feat finished [took 48.9670s]
-31/10/23 04:01:54| INFO: ref finished [took 54.3281s]
-31/10/23 04:01:55| INFO: kfcv finished [took 57.0798s]
-31/10/23 04:01:59| INFO: atc_mc finished [took 57.5663s]
-31/10/23 04:02:00| INFO: atc_ne finished [took 57.1756s]
-31/10/23 04:02:07| INFO: mul_sld finished [took 74.8552s]
-31/10/23 04:02:14| INFO: mul_sld_bcts finished [took 79.8097s]
-31/10/23 04:04:43| INFO: bin_sld finished [took 231.6926s]
-31/10/23 04:04:43| INFO: bin_sld_bcts finished [took 229.9267s]
-31/10/23 04:05:23| INFO: mul_sld_gs finished [took 266.8226s]
-31/10/23 04:08:36| INFO: bin_sld_gs finished [took 460.9384s]
-31/10/23 04:08:36| INFO: Dataset sample 0.20 of dataset rcv1_CCAT finished [took 466.5653s]
-31/10/23 04:08:36| INFO: Dataset sample 0.10 of dataset rcv1_CCAT started
-31/10/23 04:08:46| WARNING: Method mul_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-31/10/23 04:08:46| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-31/10/23 04:08:55| WARNING: Method mul_sld_bcts failed. Exception: fun: nan
- hess_inv: <5x5 LbfgsInvHessProduct with dtype=float64>
- jac: array([nan, nan, nan, nan, nan])
- message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
- nfev: 21
- nit: 0
- njev: 21
- status: 2
- success: False
- x: array([1., 0., 0., 0., 0.])
-31/10/23 04:09:33| INFO: doc_feat finished [took 42.6167s]
-31/10/23 04:09:33| INFO: ref finished [took 46.6961s]
-31/10/23 04:09:33| INFO: kfcv finished [took 48.7570s]
-31/10/23 04:09:37| INFO: atc_mc finished [took 49.6198s]
-31/10/23 04:09:38| INFO: atc_ne finished [took 49.1195s]
-31/10/23 04:09:42| INFO: mul_sld finished [took 63.1364s]
-31/10/23 04:11:02| WARNING: Method bin_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-31/10/23 04:12:05| INFO: bin_sld finished [took 207.4063s]
-31/10/23 04:12:05| INFO: Dataset sample 0.10 of dataset rcv1_CCAT finished [took 208.7423s]
-31/10/23 04:12:16| ERROR: Configuration rcv1_CCAT_9prevs failed. Exception: 'DatasetReport' object has no attribute 'fit_scores'
-----------------------------------------------------------------------------------------------------
-31/10/23 11:30:20| INFO: dataset rcv1_CCAT
-31/10/23 11:30:26| INFO: Dataset sample 0.90 of dataset rcv1_CCAT started
-31/10/23 11:31:32| INFO: doc_feat finished [took 48.1486s]
-31/10/23 11:31:32| INFO: ref finished [took 53.9235s]
-31/10/23 11:31:33| INFO: kfcv finished [took 56.4175s]
-31/10/23 11:31:37| INFO: atc_mc finished [took 57.2963s]
-31/10/23 11:31:39| INFO: atc_ne finished [took 56.1470s]
-31/10/23 11:31:43| INFO: mul_sld finished [took 74.0703s]
-31/10/23 11:31:50| INFO: mul_sld_bcts finished [took 78.8253s]
-31/10/23 11:34:16| INFO: bin_sld_bcts finished [took 225.7409s]
-31/10/23 11:34:18| INFO: bin_sld finished [took 229.9705s]
-31/10/23 11:34:42| INFO: mul_sld_gs finished [took 247.4756s]
-31/10/23 11:38:30| INFO: bin_sld_gs finished [took 477.2173s]
-31/10/23 11:38:30| INFO: Dataset sample 0.90 of dataset rcv1_CCAT finished [took 483.7632s]
-31/10/23 11:38:30| INFO: Dataset sample 0.80 of dataset rcv1_CCAT started
-31/10/23 11:39:32| INFO: doc_feat finished [took 47.0343s]
-31/10/23 11:39:33| INFO: ref finished [took 52.5674s]
-31/10/23 11:39:33| INFO: kfcv finished [took 54.5521s]
-31/10/23 11:39:38| INFO: atc_mc finished [took 55.5394s]
-31/10/23 11:39:38| INFO: atc_ne finished [took 54.9616s]
-31/10/23 11:39:48| INFO: mul_sld finished [took 75.9068s]
-31/10/23 11:39:53| INFO: mul_sld_bcts finished [took 78.1581s]
-31/10/23 11:42:22| INFO: bin_sld finished [took 230.5536s]
-31/10/23 11:42:23| INFO: bin_sld_bcts finished [took 229.2262s]
-31/10/23 11:43:29| INFO: mul_sld_gs finished [took 291.7013s]
-31/10/23 11:46:14| INFO: bin_sld_gs finished [took 457.9059s]
-31/10/23 11:46:14| INFO: Dataset sample 0.80 of dataset rcv1_CCAT finished [took 463.5174s]
-31/10/23 11:46:14| INFO: Dataset sample 0.70 of dataset rcv1_CCAT started
-31/10/23 11:47:17| INFO: doc_feat finished [took 46.4490s]
-31/10/23 11:47:17| INFO: ref finished [took 52.6852s]
-31/10/23 11:47:17| INFO: kfcv finished [took 55.0158s]
-31/10/23 11:47:21| INFO: atc_mc finished [took 55.4861s]
-31/10/23 11:47:22| INFO: atc_ne finished [took 54.9236s]
-31/10/23 11:47:32| INFO: mul_sld finished [took 75.5717s]
-31/10/23 11:47:38| INFO: mul_sld_bcts finished [took 80.0893s]
-31/10/23 11:50:02| INFO: bin_sld finished [took 226.8402s]
-31/10/23 11:50:05| INFO: bin_sld_bcts finished [took 227.7311s]
-31/10/23 11:51:15| INFO: mul_sld_gs finished [took 294.0087s]
-31/10/23 11:53:36| INFO: bin_sld_gs finished [took 436.3031s]
-31/10/23 11:53:36| INFO: Dataset sample 0.70 of dataset rcv1_CCAT finished [took 441.8200s]
-31/10/23 11:53:36| INFO: Dataset sample 0.60 of dataset rcv1_CCAT started
-31/10/23 11:54:37| INFO: doc_feat finished [took 47.1550s]
-31/10/23 11:54:38| INFO: ref finished [took 52.2980s]
-31/10/23 11:54:39| INFO: kfcv finished [took 54.5489s]
-31/10/23 11:54:42| INFO: atc_mc finished [took 55.2076s]
-31/10/23 11:54:43| INFO: atc_ne finished [took 54.6137s]
-31/10/23 11:54:53| INFO: mul_sld finished [took 74.8407s]
-31/10/23 11:54:59| INFO: mul_sld_bcts finished [took 79.4977s]
-31/10/23 11:57:24| INFO: bin_sld finished [took 226.9209s]
-31/10/23 11:57:26| INFO: bin_sld_bcts finished [took 227.3112s]
-31/10/23 11:58:29| INFO: mul_sld_gs finished [took 286.1947s]
-31/10/23 12:01:41| INFO: bin_sld_gs finished [took 479.8610s]
-31/10/23 12:01:41| INFO: Dataset sample 0.60 of dataset rcv1_CCAT finished [took 485.3472s]
-31/10/23 12:01:41| INFO: Dataset sample 0.50 of dataset rcv1_CCAT started
-31/10/23 12:02:42| INFO: doc_feat finished [took 46.7340s]
-31/10/23 12:02:42| INFO: ref finished [took 51.5482s]
-31/10/23 12:02:43| INFO: kfcv finished [took 53.9559s]
-31/10/23 12:02:47| INFO: atc_mc finished [took 54.7558s]
-31/10/23 12:02:48| INFO: atc_ne finished [took 54.5216s]
-31/10/23 12:02:57| INFO: mul_sld finished [took 73.4013s]
-31/10/23 12:03:04| INFO: mul_sld_bcts finished [took 78.9197s]
-31/10/23 12:05:30| INFO: bin_sld finished [took 227.3887s]
-31/10/23 12:05:31| INFO: bin_sld_bcts finished [took 226.6540s]
-31/10/23 12:06:37| INFO: mul_sld_gs finished [took 289.2631s]
-31/10/23 12:09:30| INFO: bin_sld_gs finished [took 463.2754s]
-31/10/23 12:09:30| INFO: Dataset sample 0.50 of dataset rcv1_CCAT finished [took 468.6356s]
-31/10/23 12:09:30| INFO: Dataset sample 0.40 of dataset rcv1_CCAT started
-31/10/23 12:10:30| INFO: doc_feat finished [took 47.0178s]
-31/10/23 12:10:31| INFO: ref finished [took 51.8808s]
-31/10/23 12:10:31| INFO: kfcv finished [took 53.6165s]
-31/10/23 12:10:36| INFO: atc_mc finished [took 55.8052s]
-31/10/23 12:10:36| INFO: atc_ne finished [took 55.0541s]
-31/10/23 12:10:44| INFO: mul_sld finished [took 72.1431s]
-31/10/23 12:10:52| INFO: mul_sld_bcts finished [took 78.0435s]
-31/10/23 12:13:18| INFO: bin_sld finished [took 227.6364s]
-31/10/23 12:13:20| INFO: bin_sld_bcts finished [took 227.4485s]
-31/10/23 12:14:23| INFO: mul_sld_gs finished [took 287.2824s]
-31/10/23 12:17:20| INFO: bin_sld_gs finished [took 465.4084s]
-31/10/23 12:17:20| INFO: Dataset sample 0.40 of dataset rcv1_CCAT finished [took 470.5362s]
-31/10/23 12:17:20| INFO: Dataset sample 0.30 of dataset rcv1_CCAT started
-31/10/23 12:18:22| INFO: doc_feat finished [took 46.7203s]
-31/10/23 12:18:24| INFO: ref finished [took 52.8941s]
-31/10/23 12:18:24| INFO: kfcv finished [took 55.1602s]
-31/10/23 12:18:27| INFO: atc_mc finished [took 55.1296s]
-31/10/23 12:18:29| INFO: atc_ne finished [took 54.8176s]
-31/10/23 12:18:36| INFO: mul_sld finished [took 73.6368s]
-31/10/23 12:18:44| INFO: mul_sld_bcts finished [took 79.2444s]
-31/10/23 12:21:09| INFO: bin_sld finished [took 227.4633s]
-31/10/23 12:21:11| INFO: bin_sld_bcts finished [took 227.8848s]
-31/10/23 12:22:18| INFO: mul_sld_gs finished [took 290.8750s]
-31/10/23 12:25:01| INFO: bin_sld_gs finished [took 455.0492s]
-31/10/23 12:25:01| INFO: Dataset sample 0.30 of dataset rcv1_CCAT finished [took 460.7077s]
-31/10/23 12:25:01| INFO: Dataset sample 0.20 of dataset rcv1_CCAT started
-31/10/23 12:26:04| INFO: doc_feat finished [took 48.7419s]
-31/10/23 12:26:05| INFO: ref finished [took 53.9956s]
-31/10/23 12:26:06| INFO: kfcv finished [took 56.7159s]
-31/10/23 12:26:10| INFO: atc_mc finished [took 57.0141s]
-31/10/23 12:26:11| INFO: atc_ne finished [took 56.6235s]
-31/10/23 12:26:18| INFO: mul_sld finished [took 74.9361s]
-31/10/23 12:26:24| INFO: mul_sld_bcts finished [took 78.6411s]
-31/10/23 12:28:51| INFO: bin_sld finished [took 228.5964s]
-31/10/23 12:28:51| INFO: bin_sld_bcts finished [took 226.9077s]
-31/10/23 12:29:34| INFO: mul_sld_gs finished [took 265.9319s]
-31/10/23 12:32:39| INFO: bin_sld_gs finished [took 452.9439s]
-31/10/23 12:32:39| INFO: Dataset sample 0.20 of dataset rcv1_CCAT finished [took 458.4924s]
-31/10/23 12:32:39| INFO: Dataset sample 0.10 of dataset rcv1_CCAT started
-31/10/23 12:32:49| WARNING: Method mul_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-31/10/23 12:32:49| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-31/10/23 12:32:57| WARNING: Method mul_sld_bcts failed. Exception: fun: nan
- hess_inv: <5x5 LbfgsInvHessProduct with dtype=float64>
- jac: array([nan, nan, nan, nan, nan])
- message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
- nfev: 21
- nit: 0
- njev: 21
- status: 2
- success: False
- x: array([1., 0., 0., 0., 0.])
-31/10/23 12:33:33| INFO: doc_feat finished [took 40.8855s]
-31/10/23 12:33:34| INFO: ref finished [took 44.7933s]
-31/10/23 12:33:34| INFO: kfcv finished [took 47.0146s]
-31/10/23 12:33:38| INFO: atc_mc finished [took 47.7008s]
-31/10/23 12:33:39| INFO: atc_ne finished [took 47.4664s]
-31/10/23 12:33:42| INFO: mul_sld finished [took 60.5341s]
-31/10/23 12:35:06| WARNING: Method bin_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-31/10/23 12:36:11| INFO: bin_sld finished [took 210.5128s]
-31/10/23 12:36:11| INFO: Dataset sample 0.10 of dataset rcv1_CCAT finished [took 211.7476s]
-----------------------------------------------------------------------------------------------------
-31/10/23 13:07:34| INFO: dataset imdb_2prevs
-31/10/23 13:07:41| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 13:07:55| INFO: ref finished [took 12.2932s]
-31/10/23 13:07:58| INFO: atc_mc finished [took 15.8781s]
-31/10/23 13:07:58| INFO: atc_ne finished [took 15.8256s]
-31/10/23 13:08:08| INFO: mul_sld finished [took 25.6841s]
-31/10/23 13:08:18| INFO: mul_sld_bcts finished [took 35.3498s]
-31/10/23 13:08:18| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 36.3540s]
-31/10/23 13:08:18| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 13:08:32| INFO: ref finished [took 12.8011s]
-31/10/23 13:08:36| INFO: atc_mc finished [took 16.7266s]
-31/10/23 13:08:36| INFO: atc_ne finished [took 16.9577s]
-31/10/23 13:08:49| INFO: mul_sld finished [took 30.1948s]
-31/10/23 13:09:00| INFO: mul_sld_bcts finished [took 41.0998s]
-31/10/23 13:09:00| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 42.6008s]
-31/10/23 13:09:00| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
-----------------------------------------------------------------------------------------------------
-31/10/23 13:10:27| INFO: dataset imdb_2prevs
-31/10/23 13:10:34| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 13:10:47| INFO: ref finished [took 11.6569s]
-31/10/23 13:10:51| INFO: atc_mc finished [took 15.6380s]
-31/10/23 13:10:51| INFO: atc_ne finished [took 15.5430s]
-31/10/23 13:11:00| INFO: mul_sld finished [took 24.9236s]
-31/10/23 13:11:10| INFO: mul_sld_bcts finished [took 34.5252s]
-31/10/23 13:11:10| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 35.4874s]
-31/10/23 13:11:10| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 13:11:23| INFO: ref finished [took 11.5602s]
-31/10/23 13:11:26| INFO: atc_ne finished [took 14.3888s]
-31/10/23 13:11:26| INFO: atc_mc finished [took 14.5643s]
-31/10/23 13:11:39| INFO: mul_sld finished [took 27.8023s]
-31/10/23 13:11:51| INFO: mul_sld_bcts finished [took 39.2892s]
-31/10/23 13:11:51| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.6914s]
-31/10/23 13:11:51| DEBUG: ['COMP_ESTIMATORS', 'DATASET_DIR_UPDATE', 'DATASET_NAME', 'DATASET_N_PREVS', 'DATASET_PREVS', 'DATASET_TARGET', 'METRICS', 'OUT_DIR', 'OUT_DIR_NAME', 'PLOT_DIR_NAME', 'PLOT_ESTIMATORS', 'PLOT_OUT_DIR', 'PLOT_STDEV', 'PROTOCOL_N_PREVS', 'PROTOCOL_REPEATS', 'SAMPLE_SIZE', '__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__slotnames__', '__str__', '__subclasshook__', '__weakref__', '_current_conf', '_default', '_environ__getdict', '_environ__setdict', '_instance', '_keys', 'confs', 'exec', 'get_confs', 'get_plot_confs', 'load_conf', 'plot_confs']
-31/10/23 13:11:51| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
-----------------------------------------------------------------------------------------------------
-31/10/23 13:12:56| INFO: dataset imdb_2prevs
-31/10/23 13:13:03| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 13:13:15| INFO: ref finished [took 11.2578s]
-31/10/23 13:13:19| INFO: atc_mc finished [took 14.7895s]
-31/10/23 13:13:19| INFO: atc_ne finished [took 14.8637s]
-31/10/23 13:13:28| INFO: mul_sld finished [took 24.2622s]
-31/10/23 13:13:38| INFO: mul_sld_bcts finished [took 34.0592s]
-31/10/23 13:13:38| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.9907s]
-31/10/23 13:13:38| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 13:13:52| INFO: ref finished [took 12.2334s]
-31/10/23 13:13:56| INFO: atc_ne finished [took 16.1148s]
-31/10/23 13:13:56| INFO: atc_mc finished [took 16.4135s]
-31/10/23 13:14:10| INFO: mul_sld finished [took 30.7003s]
-31/10/23 13:14:21| INFO: mul_sld_bcts finished [took 41.5915s]
-31/10/23 13:14:21| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 43.0339s]
-31/10/23 13:14:21| ERROR: estimate comparison failed. Exceprion: 'environ' object has no attribute '__getdict'
-----------------------------------------------------------------------------------------------------
-31/10/23 14:05:25| ERROR: estimate comparison failed. Exceprion: 'environ' object has no attribute '_current_conf'
-----------------------------------------------------------------------------------------------------
-31/10/23 14:06:00| INFO: dataset imdb_2prevs
-31/10/23 14:06:07| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:06:19| INFO: ref finished [took 10.8776s]
-31/10/23 14:06:23| INFO: atc_ne finished [took 14.0744s]
-31/10/23 14:06:23| INFO: atc_mc finished [took 14.4000s]
-31/10/23 14:06:33| INFO: mul_sld finished [took 24.5149s]
-31/10/23 14:06:42| INFO: mul_sld_bcts finished [took 33.9116s]
-31/10/23 14:06:42| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.8416s]
-31/10/23 14:06:42| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:06:55| INFO: ref finished [took 11.2125s]
-31/10/23 14:06:59| INFO: atc_ne finished [took 14.9235s]
-31/10/23 14:06:59| INFO: atc_mc finished [took 15.1623s]
-31/10/23 14:07:12| INFO: mul_sld finished [took 28.3463s]
-31/10/23 14:07:23| INFO: mul_sld_bcts finished [took 39.0377s]
-31/10/23 14:07:23| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.4312s]
-31/10/23 14:07:23| ERROR: estimate comparison failed. Exceprion: 'environ' object has no attribute '__getdict'
-----------------------------------------------------------------------------------------------------
-31/10/23 14:09:14| INFO: dataset imdb_2prevs
-31/10/23 14:09:22| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:09:33| INFO: ref finished [took 10.6213s]
-31/10/23 14:09:37| INFO: atc_mc finished [took 14.2004s]
-31/10/23 14:09:37| INFO: atc_ne finished [took 14.2574s]
-31/10/23 14:09:46| INFO: mul_sld finished [took 23.8084s]
-31/10/23 14:09:56| INFO: mul_sld_bcts finished [took 33.4634s]
-31/10/23 14:09:56| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.4023s]
-31/10/23 14:09:56| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:10:09| INFO: ref finished [took 11.0452s]
-31/10/23 14:10:12| INFO: atc_mc finished [took 14.0363s]
-31/10/23 14:10:12| INFO: atc_ne finished [took 14.2492s]
-31/10/23 14:10:25| INFO: mul_sld finished [took 27.1464s]
-31/10/23 14:10:35| INFO: mul_sld_bcts finished [took 37.7957s]
-31/10/23 14:10:35| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 39.1750s]
-31/10/23 14:10:35| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
-----------------------------------------------------------------------------------------------------
-31/10/23 14:14:00| INFO: dataset imdb_2prevs
-31/10/23 14:14:07| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:14:19| INFO: ref finished [took 11.0176s]
-31/10/23 14:14:22| INFO: atc_mc finished [took 14.0422s]
-31/10/23 14:14:23| INFO: atc_ne finished [took 14.2169s]
-31/10/23 14:14:31| INFO: mul_sld finished [took 23.7014s]
-31/10/23 14:14:42| INFO: mul_sld_bcts finished [took 33.7536s]
-31/10/23 14:14:42| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.7003s]
-31/10/23 14:14:42| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:14:54| INFO: ref finished [took 11.0187s]
-31/10/23 14:14:57| INFO: atc_mc finished [took 14.0175s]
-31/10/23 14:14:58| INFO: atc_ne finished [took 14.4154s]
-31/10/23 14:15:10| INFO: mul_sld finished [took 27.5946s]
-31/10/23 14:15:21| INFO: mul_sld_bcts finished [took 38.0464s]
-31/10/23 14:15:21| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 39.4594s]
-31/10/23 14:15:21| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_mc', 'mul_sld', 'atc_ne', 'mul_sld_bcts', 'ref'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': None, 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': None, 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
-31/10/23 14:15:21| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
-----------------------------------------------------------------------------------------------------
-31/10/23 14:30:59| INFO: dataset imdb_2prevs
-31/10/23 14:31:10| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:31:33| INFO: ref finished [took 22.2885s]
-31/10/23 14:31:41| INFO: atc_mc finished [took 29.8328s]
-31/10/23 14:31:41| INFO: atc_ne finished [took 30.1421s]
-31/10/23 14:31:46| INFO: mul_sld finished [took 35.8373s]
-31/10/23 14:31:57| INFO: mul_sld_bcts finished [took 46.5130s]
-31/10/23 14:31:57| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 47.5379s]
-31/10/23 14:31:57| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:32:24| INFO: ref finished [took 24.3912s]
-31/10/23 14:32:31| INFO: atc_mc finished [took 31.2488s]
-31/10/23 14:32:31| INFO: atc_ne finished [took 31.5120s]
-31/10/23 14:32:43| INFO: mul_sld finished [took 44.6372s]
-31/10/23 14:32:54| INFO: mul_sld_bcts finished [took 54.5749s]
-31/10/23 14:32:54| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 56.2358s]
-31/10/23 14:32:54| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_ne', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
-31/10/23 14:32:58| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_ne', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
-----------------------------------------------------------------------------------------------------
-31/10/23 14:37:38| INFO: dataset imdb_2prevs
-31/10/23 14:37:45| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:37:58| INFO: ref finished [took 11.4397s]
-31/10/23 14:38:01| INFO: atc_mc finished [took 14.6411s]
-31/10/23 14:38:01| INFO: atc_ne finished [took 14.8218s]
-31/10/23 14:38:11| INFO: mul_sld finished [took 24.4862s]
-31/10/23 14:38:20| INFO: mul_sld_bcts finished [took 33.9900s]
-31/10/23 14:38:20| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.9816s]
-31/10/23 14:38:20| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:38:33| INFO: ref finished [took 11.3787s]
-31/10/23 14:38:36| INFO: atc_mc finished [took 14.4366s]
-31/10/23 14:38:36| INFO: atc_ne finished [took 14.3365s]
-31/10/23 14:38:50| INFO: mul_sld finished [took 28.1585s]
-31/10/23 14:39:00| INFO: mul_sld_bcts finished [took 38.5508s]
-31/10/23 14:39:00| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.0193s]
-31/10/23 14:39:00| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld', 'ref', 'mul_sld_bcts', 'atc_mc'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
-31/10/23 14:39:03| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld', 'ref', 'mul_sld_bcts', 'atc_mc'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
-----------------------------------------------------------------------------------------------------
-31/10/23 14:44:15| INFO: dataset imdb_2prevs
-31/10/23 14:44:22| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:44:35| INFO: ref finished [took 11.5902s]
-31/10/23 14:44:38| INFO: atc_mc finished [took 14.7915s]
-31/10/23 14:44:39| INFO: atc_ne finished [took 14.8611s]
-31/10/23 14:44:48| INFO: mul_sld finished [took 24.7670s]
-31/10/23 14:44:58| INFO: mul_sld_bcts finished [took 34.3171s]
-31/10/23 14:44:58| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 35.3088s]
-31/10/23 14:44:58| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:45:11| INFO: ref finished [took 11.8887s]
-31/10/23 14:45:15| INFO: atc_mc finished [took 15.2624s]
-31/10/23 14:45:15| INFO: atc_ne finished [took 15.2085s]
-31/10/23 14:45:28| INFO: mul_sld finished [took 28.5408s]
-31/10/23 14:45:38| INFO: mul_sld_bcts finished [took 38.9976s]
-31/10/23 14:45:38| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.5854s]
-31/10/23 14:45:38| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
-31/10/23 14:45:41| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
-----------------------------------------------------------------------------------------------------
-31/10/23 14:55:18| INFO dataset imdb_2prevs
-31/10/23 14:55:26| INFO Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 14:55:37| INFO ref finished [took 10.1990s]
-31/10/23 14:55:40| INFO atc_mc finished [took 13.4778s]
-31/10/23 14:55:41| INFO atc_ne finished [took 13.5559s]
-31/10/23 14:55:50| INFO mul_sld finished [took 23.0450s]
-31/10/23 14:55:59| INFO mul_sld_bcts finished [took 32.4582s]
-31/10/23 14:55:59| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 33.3679s]
-31/10/23 14:55:59| INFO Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 14:56:11| INFO ref finished [took 10.3415s]
-31/10/23 14:56:14| INFO atc_mc finished [took 13.4638s]
-31/10/23 14:56:14| INFO atc_ne finished [took 13.4791s]
-31/10/23 14:56:27| INFO mul_sld finished [took 26.3298s]
-31/10/23 14:56:38| INFO mul_sld_bcts finished [took 37.2449s]
-31/10/23 14:56:38| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 38.6430s]
-31/10/23 14:56:38| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld', 'atc_ne'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
-31/10/23 14:56:41| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld', 'atc_ne'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
-----------------------------------------------------------------------------------------------------
-31/10/23 15:00:19| INFO dataset imdb_2prevs
-31/10/23 15:00:26| INFO Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 15:00:38| INFO ref finished [took 10.7099s]
-31/10/23 15:00:41| INFO atc_ne finished [took 13.7392s]
-31/10/23 15:00:41| INFO atc_mc finished [took 13.9108s]
-31/10/23 15:00:50| INFO mul_sld finished [took 23.3628s]
-31/10/23 15:01:00| INFO mul_sld_bcts finished [took 33.0440s]
-31/10/23 15:01:00| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 33.9805s]
-31/10/23 15:01:00| INFO Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 15:01:12| INFO ref finished [took 10.7020s]
-31/10/23 15:01:15| INFO atc_mc finished [took 13.9521s]
-31/10/23 15:01:15| INFO atc_ne finished [took 13.8623s]
-31/10/23 15:01:28| INFO mul_sld finished [took 26.8476s]
-31/10/23 15:01:39| INFO mul_sld_bcts finished [took 37.4291s]
-31/10/23 15:01:39| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 38.8721s]
-31/10/23 15:01:39| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['ref', 'atc_mc', 'mul_sld', 'atc_ne', 'mul_sld_bcts'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
-31/10/23 15:01:42| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['ref', 'atc_mc', 'mul_sld', 'atc_ne', 'mul_sld_bcts'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
-----------------------------------------------------------------------------------------------------
-31/10/23 15:02:43| INFO dataset imdb_2prevs
-31/10/23 15:02:50| INFO Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 15:03:02| INFO ref finished [took 10.5528s]
-31/10/23 15:03:05| INFO atc_mc finished [took 13.7838s]
-31/10/23 15:03:05| INFO atc_ne finished [took 13.6736s]
-31/10/23 15:03:14| INFO mul_sld finished [took 23.2705s]
-31/10/23 15:03:24| INFO mul_sld_bcts finished [took 32.8493s]
-31/10/23 15:03:24| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 33.7917s]
-31/10/23 15:03:24| INFO Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 15:03:36| INFO ref finished [took 10.4338s]
-31/10/23 15:03:39| INFO atc_mc finished [took 13.5140s]
-31/10/23 15:03:39| INFO atc_ne finished [took 13.5920s]
-31/10/23 15:03:52| INFO mul_sld finished [took 26.7677s]
-31/10/23 15:04:03| INFO mul_sld_bcts finished [took 37.2882s]
-31/10/23 15:04:03| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 38.7014s]
-----------------------------------------------------------------------------------------------------
-31/10/23 17:01:56| INFO dataset imdb_2prevs
-31/10/23 17:02:03| INFO Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 17:02:16| INFO ref finished [took 11.7260s]
-31/10/23 17:02:19| INFO atc_mc finished [took 14.9332s]
-31/10/23 17:02:20| INFO atc_ne finished [took 14.9267s]
-31/10/23 17:02:29| INFO mul_sld finished [took 25.0825s]
-31/10/23 17:02:39| INFO mul_sld_bcts finished [took 35.1456s]
-31/10/23 17:02:39| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 36.1167s]
-31/10/23 17:02:39| INFO Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 17:02:53| INFO ref finished [took 12.1990s]
-31/10/23 17:02:57| INFO atc_mc finished [took 15.9130s]
-31/10/23 17:02:57| INFO atc_ne finished [took 15.8122s]
-31/10/23 17:03:10| INFO mul_sld finished [took 29.0681s]
-31/10/23 17:03:21| INFO mul_sld_bcts finished [took 40.0346s]
-31/10/23 17:03:21| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 41.6137s]
-----------------------------------------------------------------------------------------------------
-31/10/23 17:04:35| INFO dataset imdb_2prevs
-31/10/23 17:04:42| INFO Dataset sample 0.10 of dataset imdb_2prevs started
-31/10/23 17:04:56| INFO ref finished [took 11.5027s]
-31/10/23 17:05:00| INFO atc_mc finished [took 15.1600s]
-31/10/23 17:05:00| INFO atc_ne finished [took 15.0072s]
-31/10/23 17:05:09| INFO mul_sld finished [took 24.7931s]
-31/10/23 17:05:19| INFO mul_sld_bcts finished [took 34.6305s]
-31/10/23 17:05:19| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 37.1778s]
-31/10/23 17:05:19| INFO Dataset sample 0.50 of dataset imdb_2prevs started
-31/10/23 17:05:33| INFO ref finished [took 12.2649s]
-31/10/23 17:05:36| INFO atc_mc finished [took 15.5987s]
-31/10/23 17:05:37| INFO atc_ne finished [took 15.8214s]
-31/10/23 17:05:50| INFO mul_sld finished [took 29.3523s]
-31/10/23 17:06:00| INFO mul_sld_bcts finished [took 39.8376s]
-31/10/23 17:06:00| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 41.2888s]
-----------------------------------------------------------------------------------------------------
-31/10/23 20:19:37| INFO dataset imdb_1prevs
-31/10/23 20:19:48| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-31/10/23 20:20:07| INFO ref finished [took 17.4125s]
-----------------------------------------------------------------------------------------------------
-31/10/23 20:20:50| INFO dataset imdb_1prevs
-31/10/23 20:21:01| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-31/10/23 20:21:19| INFO ref finished [took 17.0717s]
-----------------------------------------------------------------------------------------------------
-31/10/23 20:22:05| INFO dataset imdb_1prevs
-31/10/23 20:22:15| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-31/10/23 20:22:35| INFO ref finished [took 18.4752s]
-----------------------------------------------------------------------------------------------------
-31/10/23 20:23:38| INFO dataset imdb_1prevs
-31/10/23 20:23:48| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-31/10/23 20:24:08| INFO ref finished [took 18.3216s]
-----------------------------------------------------------------------------------------------------
-01/11/23 13:07:19| INFO dataset imdb_1prevs
-01/11/23 13:07:27| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-01/11/23 13:07:27| ERROR Evaluation over imdb_1prevs failed. Exception: 'Invalid estimator: estimator mul_sld_gs does not exist'
-01/11/23 13:07:27| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
-----------------------------------------------------------------------------------------------------
-03/11/23 20:54:19| INFO dataset rcv1_CCAT_9prevs
-03/11/23 20:54:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-03/11/23 20:54:28| WARNING Method mul_sld_gs failed. Exception: Invalid parameter 'quantifier' for estimator EMQ(classifier=LogisticRegression()). Valid parameters are: ['classifier', 'exact_train_prev', 'recalib'].
-03/11/23 20:54:29| WARNING Method mul_sld failed. Exception: evaluation_report() got an unexpected keyword argument 'protocor'
-03/11/23 20:54:30| WARNING Method bin_sld_gs failed. Exception: Invalid parameter 'quantifier' for estimator EMQ(classifier=LogisticRegression()). Valid parameters are: ['classifier', 'exact_train_prev', 'recalib'].
-03/11/23 20:55:09| INFO ref finished [took 38.5179s]
-----------------------------------------------------------------------------------------------------
-03/11/23 21:28:36| INFO dataset rcv1_CCAT_9prevs
-03/11/23 21:28:41| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-03/11/23 21:28:45| WARNING Method mul_sld failed. Exception: evaluation_report() got an unexpected keyword argument 'protocor'
-----------------------------------------------------------------------------------------------------
-03/11/23 21:31:03| INFO dataset rcv1_CCAT_9prevs
-03/11/23 21:31:08| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-03/11/23 21:31:59| INFO ref finished [took 45.6616s]
-03/11/23 21:32:03| INFO atc_mc finished [took 48.4360s]
-03/11/23 21:32:07| INFO atc_ne finished [took 51.0515s]
-03/11/23 21:32:23| INFO mul_sld finished [took 72.9229s]
-03/11/23 21:34:43| INFO bin_sld finished [took 213.9538s]
-03/11/23 21:36:27| INFO mul_sld_gs finished [took 314.9357s]
-03/11/23 21:40:50| INFO bin_sld_gs finished [took 579.2530s]
-03/11/23 21:40:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 582.5876s]
-03/11/23 21:40:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-03/11/23 21:41:39| INFO ref finished [took 43.7409s]
-03/11/23 21:41:43| INFO atc_mc finished [took 46.4580s]
-03/11/23 21:41:44| INFO atc_ne finished [took 46.4267s]
-03/11/23 21:41:54| INFO mul_sld finished [took 61.3005s]
-03/11/23 21:44:18| INFO bin_sld finished [took 206.3680s]
-03/11/23 21:45:59| INFO mul_sld_gs finished [took 304.4726s]
-03/11/23 21:50:33| INFO bin_sld_gs finished [took 579.3455s]
-03/11/23 21:50:33| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 582.4808s]
-03/11/23 21:50:33| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-03/11/23 21:51:22| INFO ref finished [took 43.6853s]
-03/11/23 21:51:26| INFO atc_mc finished [took 47.1366s]
-03/11/23 21:51:30| INFO atc_ne finished [took 49.4868s]
-03/11/23 21:51:34| INFO mul_sld finished [took 59.0964s]
-03/11/23 21:53:59| INFO bin_sld finished [took 205.0248s]
-03/11/23 21:55:50| INFO mul_sld_gs finished [took 312.5630s]
-03/11/23 22:00:27| INFO bin_sld_gs finished [took 591.1460s]
-03/11/23 22:00:27| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 594.3163s]
-03/11/23 22:00:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-03/11/23 22:01:15| INFO ref finished [took 43.3806s]
-03/11/23 22:01:19| INFO atc_mc finished [took 46.6674s]
-03/11/23 22:01:21| INFO atc_ne finished [took 47.1220s]
-03/11/23 22:01:28| INFO mul_sld finished [took 58.6799s]
-03/11/23 22:03:53| INFO bin_sld finished [took 204.7659s]
-03/11/23 22:05:39| INFO mul_sld_gs finished [took 307.8811s]
-03/11/23 22:10:32| INFO bin_sld_gs finished [took 601.9995s]
-03/11/23 22:10:32| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 604.8406s]
-03/11/23 22:10:32| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-03/11/23 22:11:20| INFO ref finished [took 42.8256s]
-03/11/23 22:11:25| INFO atc_mc finished [took 46.9203s]
-03/11/23 22:11:28| INFO atc_ne finished [took 49.3042s]
-03/11/23 22:11:34| INFO mul_sld finished [took 60.2744s]
-03/11/23 22:13:59| INFO bin_sld finished [took 205.7078s]
-03/11/23 22:15:45| INFO mul_sld_gs finished [took 309.0888s]
-03/11/23 22:20:32| INFO bin_sld_gs finished [took 596.5102s]
-03/11/23 22:20:32| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 599.5067s]
-03/11/23 22:20:32| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-03/11/23 22:21:20| INFO ref finished [took 43.1698s]
-03/11/23 22:21:24| INFO atc_mc finished [took 46.5768s]
-03/11/23 22:21:25| INFO atc_ne finished [took 46.3408s]
-03/11/23 22:21:34| INFO mul_sld finished [took 60.8070s]
-03/11/23 22:23:58| INFO bin_sld finished [took 205.3362s]
-03/11/23 22:25:44| INFO mul_sld_gs finished [took 308.1859s]
-03/11/23 22:30:44| INFO bin_sld_gs finished [took 609.5468s]
-03/11/23 22:30:44| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 612.5803s]
-03/11/23 22:30:44| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-03/11/23 22:31:32| INFO ref finished [took 43.2949s]
-03/11/23 22:31:37| INFO atc_mc finished [took 46.3686s]
-03/11/23 22:31:40| INFO atc_ne finished [took 49.2242s]
-03/11/23 22:31:47| INFO mul_sld finished [took 60.9437s]
-03/11/23 22:34:11| INFO bin_sld finished [took 205.9299s]
-03/11/23 22:35:56| INFO mul_sld_gs finished [took 308.2738s]
-03/11/23 22:40:36| INFO bin_sld_gs finished [took 588.7918s]
-03/11/23 22:40:36| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 591.8830s]
-03/11/23 22:40:36| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-03/11/23 22:41:24| INFO ref finished [took 43.3321s]
-03/11/23 22:41:29| INFO atc_mc finished [took 46.8041s]
-03/11/23 22:41:29| INFO atc_ne finished [took 46.5810s]
-03/11/23 22:41:38| INFO mul_sld finished [took 60.2962s]
-03/11/23 22:44:07| INFO bin_sld finished [took 209.6435s]
-03/11/23 22:45:44| INFO mul_sld_gs finished [took 304.4809s]
-03/11/23 22:50:39| INFO bin_sld_gs finished [took 599.5588s]
-03/11/23 22:50:39| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 602.5720s]
-03/11/23 22:50:39| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-03/11/23 22:51:26| INFO ref finished [took 42.4313s]
-03/11/23 22:51:30| INFO atc_mc finished [took 45.5261s]
-03/11/23 22:51:34| INFO atc_ne finished [took 48.4488s]
-03/11/23 22:51:47| INFO mul_sld finished [took 66.4801s]
-03/11/23 22:54:08| INFO bin_sld finished [took 208.4272s]
-03/11/23 22:55:49| INFO mul_sld_gs finished [took 306.4505s]
-03/11/23 23:00:15| INFO bin_sld_gs finished [took 573.7761s]
-03/11/23 23:00:15| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 576.7586s]
-----------------------------------------------------------------------------------------------------
-03/11/23 23:33:15| INFO dataset imdb_1prevs
-03/11/23 23:33:22| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-03/11/23 23:33:22| ERROR Evaluation over imdb_1prevs failed. Exception: 'function' object is not iterable
-03/11/23 23:33:22| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
-----------------------------------------------------------------------------------------------------
-03/11/23 23:34:15| INFO dataset imdb_1prevs
-03/11/23 23:34:23| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-03/11/23 23:34:35| INFO atc_mc finished [took 11.5081s]
-03/11/23 23:34:45| INFO ref finished [took 8.7754s]
-03/11/23 23:34:47| INFO mul_sld finished [took 22.9651s]
-03/11/23 23:34:47| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 23.9721s]
-03/11/23 23:34:47| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: 'ref'
-----------------------------------------------------------------------------------------------------
-03/11/23 23:36:10| INFO dataset imdb_1prevs
-03/11/23 23:36:30| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-03/11/23 23:38:02| INFO atc_mc finished [took 56.2957s]
-03/11/23 23:38:03| INFO mul_sld finished [took 57.6237s]
-03/11/23 23:38:40| INFO ref finished [took 37.7811s]
-03/11/23 23:38:40| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 130.9031s]
-03/11/23 23:38:42| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: 'ref'
-----------------------------------------------------------------------------------------------------
-03/11/23 23:39:32| INFO dataset imdb_1prevs
-03/11/23 23:39:42| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-03/11/23 23:40:08| INFO atc_mc finished [took 24.7110s]
-03/11/23 23:40:23| INFO mul_sld finished [took 40.2345s]
-03/11/23 23:40:26| INFO ref finished [took 17.8417s]
-03/11/23 23:40:26| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 44.8087s]
-----------------------------------------------------------------------------------------------------
-03/11/23 23:41:18| INFO dataset imdb_1prevs
-03/11/23 23:41:28| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-03/11/23 23:41:54| INFO atc_mc finished [took 24.0569s]
-03/11/23 23:42:03| INFO mul_sld finished [took 33.3390s]
-03/11/23 23:42:12| INFO ref finished [took 16.9551s]
-03/11/23 23:42:12| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 43.2484s]
-----------------------------------------------------------------------------------------------------
-04/11/23 00:03:17| ERROR Evaluation over imdb_1prevs failed. Exception: CompEstimatorName_.__init__() missing 1 required positional argument: 'ce'
-04/11/23 00:03:17| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
-----------------------------------------------------------------------------------------------------
-04/11/23 00:03:50| ERROR Evaluation over imdb_1prevs failed. Exception: 'CompEstimator' object has no attribute '_CompEstimatorName___get'
-04/11/23 00:03:50| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
-----------------------------------------------------------------------------------------------------
-04/11/23 00:04:42| INFO dataset imdb_1prevs
-04/11/23 00:04:53| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-04/11/23 00:05:13| INFO ref finished [took 19.2363s]
-04/11/23 00:05:20| INFO atc_mc finished [took 26.4278s]
-04/11/23 00:05:29| INFO mul_sld finished [took 35.3110s]
-04/11/23 00:05:29| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 36.4422s]
-----------------------------------------------------------------------------------------------------
-04/11/23 00:19:43| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:19:49| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:19:53| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-04/11/23 00:19:55| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-04/11/23 00:19:57| WARNING Method bin_pacc failed. Exception: PACC.__init__() got an unexpected keyword argument 'recalib'
-04/11/23 00:19:59| WARNING Method mul_pacc failed. Exception: PACC.__init__() got an unexpected keyword argument 'recalib'
-04/11/23 00:20:00| WARNING Method bin_pacc_gs failed. Exception: Invalid parameter 'recalib' for estimator PACC(classifier=LogisticRegression(), n_jobs=1). Valid parameters are: ['classifier', 'n_jobs', 'val_split'].
-04/11/23 00:20:01| WARNING Method mul_pacc_gs failed. Exception: Invalid parameter 'recalib' for estimator PACC(classifier=LogisticRegression(), n_jobs=1). Valid parameters are: ['classifier', 'n_jobs', 'val_split'].
-----------------------------------------------------------------------------------------------------
-04/11/23 00:22:45| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:22:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:22:54| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-04/11/23 00:22:55| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-----------------------------------------------------------------------------------------------------
-04/11/23 00:28:11| INFO dataset rcv1_CCAT_9prevs
-----------------------------------------------------------------------------------------------------
-04/11/23 00:29:39| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:29:45| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:29:49| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-04/11/23 00:29:51| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-04/11/23 00:30:39| WARNING Method mul_pacc_gs failed. Exception: evaluation_report() got an unexpected keyword argument 'method_name'
-04/11/23 00:31:00| INFO ref finished [took 60.5788s]
-04/11/23 00:31:09| INFO atc_mc finished [took 64.6156s]
-04/11/23 00:31:09| INFO mul_pacc finished [took 75.1821s]
-04/11/23 00:31:12| INFO atc_ne finished [took 62.8665s]
-04/11/23 00:31:24| INFO mul_sld finished [took 96.8624s]
-----------------------------------------------------------------------------------------------------
-04/11/23 00:33:26| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:33:31| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:33:35| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-04/11/23 00:33:37| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
-----------------------------------------------------------------------------------------------------
-04/11/23 00:38:42| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:38:48| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:38:51| WARNING Method bin_sld_qgs failed. Exception: ExtendedCollection.extend_collection() missing 1 required positional argument: 'pred_proba'
-04/11/23 00:38:52| WARNING Method mul_sld_qgs failed. Exception: ExtendedCollection.extend_collection() missing 1 required positional argument: 'pred_proba'
-04/11/23 00:39:41| WARNING Method mul_pacc_gs failed. Exception: evaluation_report() got an unexpected keyword argument 'method_name'
-----------------------------------------------------------------------------------------------------
-04/11/23 00:46:33| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:46:39| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:46:40| WARNING Method bin_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:41| WARNING Method mul_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:42| WARNING Method bin_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
-04/11/23 00:46:43| WARNING Method mul_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
-04/11/23 00:46:44| WARNING Method bin_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:45| WARNING Method mul_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:46| WARNING Method bin_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:47| WARNING Method mul_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:47| WARNING Method bin_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:46:48| WARNING Method mul_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:27| INFO ref finished [took 37.5294s]
-04/11/23 00:47:31| INFO atc_mc finished [took 40.5777s]
-04/11/23 00:47:32| INFO atc_ne finished [took 40.7565s]
-04/11/23 00:47:32| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 52.8106s]
-04/11/23 00:47:32| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:47:33| WARNING Method bin_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:34| WARNING Method mul_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:35| WARNING Method bin_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
-04/11/23 00:47:36| WARNING Method mul_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
-04/11/23 00:47:37| WARNING Method bin_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:38| WARNING Method mul_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:39| WARNING Method bin_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:39| WARNING Method mul_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:40| WARNING Method bin_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-04/11/23 00:47:41| WARNING Method mul_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
-----------------------------------------------------------------------------------------------------
-04/11/23 00:48:05| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:48:10| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:48:13| WARNING Method bin_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
-04/11/23 00:48:14| WARNING Method mul_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
-----------------------------------------------------------------------------------------------------
-04/11/23 00:49:18| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:49:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:49:27| WARNING Method bin_sld_qgs failed. Exception: GridSearchQ.__init__() missing 1 required positional argument: 'model'
-04/11/23 00:49:28| WARNING Method mul_sld_qgs failed. Exception: X has 47238 features, but LogisticRegression is expecting 47236 features as input.
-----------------------------------------------------------------------------------------------------
-04/11/23 00:51:27| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:51:32| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:51:36| WARNING Method bin_sld_qgs failed. Exception: X has 47238 features, but LogisticRegression is expecting 47236 features as input.
-04/11/23 00:51:37| WARNING Method mul_sld_qgs failed. Exception: X has 47238 features, but LogisticRegression is expecting 47236 features as input.
-----------------------------------------------------------------------------------------------------
-04/11/23 00:54:47| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:54:53| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 00:54:57| WARNING Method bin_sld_qgs failed. Exception: a must be greater than 0 unless no samples are taken
-04/11/23 00:54:58| WARNING Method mul_sld_qgs failed. Exception: a must be greater than 0 unless no samples are taken
-----------------------------------------------------------------------------------------------------
-04/11/23 00:58:47| INFO dataset rcv1_CCAT_9prevs
-04/11/23 00:58:52| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 01:00:04| INFO ref finished [took 61.6328s]
-04/11/23 01:00:11| INFO atc_mc finished [took 65.4916s]
-04/11/23 01:00:13| INFO atc_ne finished [took 63.2288s]
-04/11/23 01:00:14| INFO mul_pacc finished [took 75.5101s]
-04/11/23 01:00:30| INFO mul_sld finished [took 96.6656s]
-04/11/23 01:00:41| INFO mul_pacc_gs finished [took 99.7211s]
-04/11/23 01:03:02| INFO bin_pacc finished [took 244.6260s]
-04/11/23 01:03:07| INFO bin_sld finished [took 254.3478s]
-04/11/23 01:04:51| INFO mul_sld_gs finished [took 354.7477s]
-04/11/23 01:05:02| INFO bin_pacc_gs finished [took 362.1808s]
-04/11/23 01:09:24| INFO bin_sld_gs finished [took 628.6714s]
-04/11/23 01:09:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 631.8421s]
-04/11/23 01:09:24| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-04/11/23 01:10:39| INFO ref finished [took 63.5158s]
-04/11/23 01:10:44| INFO atc_mc finished [took 66.4279s]
-04/11/23 01:10:46| INFO mul_pacc finished [took 75.3281s]
-04/11/23 01:10:47| INFO atc_ne finished [took 67.5374s]
-04/11/23 01:10:52| INFO mul_sld finished [took 86.6592s]
-04/11/23 01:11:19| INFO mul_pacc_gs finished [took 104.6374s]
-04/11/23 01:13:58| INFO bin_sld finished [took 273.4932s]
-04/11/23 01:14:01| INFO bin_pacc finished [took 271.3481s]
-04/11/23 01:15:42| INFO mul_sld_gs finished [took 374.2416s]
-04/11/23 01:16:01| INFO bin_pacc_gs finished [took 388.0839s]
-04/11/23 01:20:29| INFO bin_sld_gs finished [took 661.9729s]
-04/11/23 01:20:29| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 665.2874s]
-04/11/23 01:20:29| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-04/11/23 01:21:46| INFO ref finished [took 63.8544s]
-04/11/23 01:21:50| INFO atc_mc finished [took 66.6917s]
-04/11/23 01:21:52| INFO atc_ne finished [took 65.0860s]
-04/11/23 01:21:53| INFO mul_pacc finished [took 77.2630s]
-04/11/23 01:21:55| INFO mul_sld finished [took 83.3146s]
-04/11/23 01:22:23| INFO mul_pacc_gs finished [took 102.3761s]
-04/11/23 01:24:47| INFO bin_pacc finished [took 252.0964s]
-04/11/23 01:24:49| INFO bin_sld finished [took 258.6998s]
-04/11/23 01:26:37| INFO mul_sld_gs finished [took 363.7500s]
-04/11/23 01:26:49| INFO bin_pacc_gs finished [took 370.5817s]
-04/11/23 01:31:27| INFO bin_sld_gs finished [took 654.3921s]
-04/11/23 01:31:27| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 658.0041s]
-04/11/23 01:31:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-04/11/23 01:32:33| INFO ref finished [took 55.7749s]
-04/11/23 01:32:38| INFO atc_mc finished [took 59.4190s]
-04/11/23 01:32:40| INFO atc_ne finished [took 59.5155s]
-04/11/23 01:32:42| INFO mul_pacc finished [took 68.8994s]
-04/11/23 01:32:44| INFO mul_sld finished [took 74.6470s]
-04/11/23 01:33:09| INFO mul_pacc_gs finished [took 92.6473s]
-04/11/23 01:35:32| INFO bin_pacc finished [took 239.7541s]
-04/11/23 01:35:34| INFO bin_sld finished [took 245.7504s]
-04/11/23 01:37:19| INFO mul_sld_gs finished [took 348.1188s]
-04/11/23 01:37:30| INFO bin_pacc_gs finished [took 355.4729s]
-04/11/23 01:42:07| INFO bin_sld_gs finished [took 636.8598s]
-04/11/23 01:42:07| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 639.9201s]
-04/11/23 01:42:07| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-04/11/23 01:43:14| INFO ref finished [took 56.1531s]
-04/11/23 01:43:19| INFO atc_mc finished [took 59.7473s]
-04/11/23 01:43:20| INFO atc_ne finished [took 59.0606s]
-04/11/23 01:43:23| INFO mul_pacc finished [took 69.4266s]
-04/11/23 01:43:25| INFO mul_sld finished [took 76.3328s]
-04/11/23 01:43:49| INFO mul_pacc_gs finished [took 92.3926s]
-04/11/23 01:46:05| INFO bin_pacc finished [took 233.1877s]
-04/11/23 01:46:08| INFO bin_sld finished [took 239.8757s]
-04/11/23 01:47:51| INFO mul_sld_gs finished [took 339.5911s]
-04/11/23 01:48:00| INFO bin_pacc_gs finished [took 345.7788s]
-04/11/23 01:52:44| INFO bin_sld_gs finished [took 633.8407s]
-04/11/23 01:52:44| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 637.0648s]
-04/11/23 01:52:44| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-04/11/23 01:53:52| INFO ref finished [took 57.4958s]
-04/11/23 01:53:57| INFO atc_mc finished [took 60.9998s]
-04/11/23 01:53:58| INFO atc_ne finished [took 60.4847s]
-04/11/23 01:54:01| INFO mul_pacc finished [took 70.5216s]
-04/11/23 01:54:04| INFO mul_sld finished [took 78.2910s]
-04/11/23 01:54:27| INFO mul_pacc_gs finished [took 94.4726s]
-04/11/23 01:56:48| INFO bin_pacc finished [took 238.5969s]
-04/11/23 01:56:50| INFO bin_sld finished [took 244.5679s]
-04/11/23 01:58:31| INFO mul_sld_gs finished [took 342.4843s]
-04/11/23 01:58:44| INFO bin_pacc_gs finished [took 352.8264s]
-04/11/23 02:03:32| INFO bin_sld_gs finished [took 644.7046s]
-04/11/23 02:03:32| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 647.8055s]
-04/11/23 02:03:32| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-04/11/23 02:04:37| INFO ref finished [took 55.4488s]
-04/11/23 02:04:42| INFO atc_mc finished [took 59.2634s]
-04/11/23 02:04:44| INFO atc_ne finished [took 59.1371s]
-04/11/23 02:04:46| INFO mul_pacc finished [took 68.0960s]
-04/11/23 02:04:50| INFO mul_sld finished [took 76.4282s]
-04/11/23 02:05:12| INFO mul_pacc_gs finished [took 91.7735s]
-04/11/23 02:07:30| INFO bin_pacc finished [took 232.7650s]
-04/11/23 02:07:36| INFO bin_sld finished [took 242.4077s]
-04/11/23 02:09:14| INFO mul_sld_gs finished [took 338.1418s]
-04/11/23 02:09:26| INFO bin_pacc_gs finished [took 347.2033s]
-04/11/23 02:13:59| INFO bin_sld_gs finished [took 624.6098s]
-04/11/23 02:13:59| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 627.7979s]
-04/11/23 02:13:59| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-04/11/23 02:15:05| INFO ref finished [took 55.1962s]
-04/11/23 02:15:10| INFO atc_mc finished [took 59.0907s]
-04/11/23 02:15:11| INFO atc_ne finished [took 59.1531s]
-04/11/23 02:15:13| INFO mul_pacc finished [took 67.6705s]
-04/11/23 02:15:17| INFO mul_sld finished [took 75.4559s]
-04/11/23 02:15:41| INFO mul_pacc_gs finished [took 92.4901s]
-04/11/23 02:17:59| INFO bin_pacc finished [took 233.8600s]
-04/11/23 02:18:04| INFO bin_sld finished [took 243.2382s]
-04/11/23 02:19:40| INFO mul_sld_gs finished [took 336.0961s]
-04/11/23 02:19:51| INFO bin_pacc_gs finished [took 344.4075s]
-04/11/23 02:24:30| INFO bin_sld_gs finished [took 627.6209s]
-04/11/23 02:24:30| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 630.8251s]
-04/11/23 02:24:30| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-04/11/23 02:25:35| INFO ref finished [took 54.8513s]
-04/11/23 02:25:40| INFO atc_mc finished [took 58.8528s]
-04/11/23 02:25:41| INFO atc_ne finished [took 58.6035s]
-04/11/23 02:25:43| INFO mul_pacc finished [took 66.9030s]
-04/11/23 02:25:57| INFO mul_sld finished [took 84.2072s]
-04/11/23 02:26:10| INFO mul_pacc_gs finished [took 91.0973s]
-04/11/23 02:28:31| INFO bin_pacc finished [took 235.7331s]
-04/11/23 02:28:35| INFO bin_sld finished [took 243.6260s]
-04/11/23 02:30:09| INFO mul_sld_gs finished [took 334.4842s]
-04/11/23 02:30:22| INFO bin_pacc_gs finished [took 344.6874s]
-04/11/23 02:34:46| INFO bin_sld_gs finished [took 612.1219s]
-04/11/23 02:34:46| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 615.2004s]
-----------------------------------------------------------------------------------------------------
-04/11/23 02:57:35| INFO dataset rcv1_CCAT_9prevs
-04/11/23 02:57:39| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 02:57:47| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 02:58:59| INFO ref finished [took 64.5948s]
-04/11/23 02:59:06| INFO atc_mc finished [took 69.5808s]
-04/11/23 02:59:12| INFO mul_pacc finished [took 82.8518s]
-04/11/23 02:59:13| INFO atc_ne finished [took 72.1303s]
-04/11/23 02:59:26| INFO mul_sld finished [took 103.4201s]
-04/11/23 02:59:30| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-04/11/23 02:59:41| INFO mul_pacc_gs finished [took 109.4672s]
-04/11/23 03:01:59| INFO bin_pacc finished [took 251.3945s]
-04/11/23 03:02:02| INFO bin_sld finished [took 260.0226s]
-04/11/23 03:03:35| INFO mul_sld_gs finished [took 350.1705s]
-04/11/23 03:03:48| INFO bin_pacc_gs finished [took 357.9668s]
-04/11/23 03:07:59| INFO bin_sld_gs finished [took 615.8087s]
-04/11/23 03:07:59| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 620.4985s]
-04/11/23 03:07:59| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-04/11/23 03:08:06| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 03:09:17| INFO ref finished [took 64.4692s]
-04/11/23 03:09:25| INFO atc_mc finished [took 71.3766s]
-04/11/23 03:09:27| INFO atc_ne finished [took 71.0947s]
-04/11/23 03:09:28| INFO mul_pacc finished [took 80.0201s]
-04/11/23 03:09:31| INFO mul_sld finished [took 89.4295s]
-04/11/23 03:09:55| INFO mul_pacc_gs finished [took 104.7292s]
-04/11/23 03:12:25| INFO bin_sld finished [took 263.6824s]
-04/11/23 03:12:25| INFO bin_pacc finished [took 258.6502s]
-04/11/23 03:14:01| INFO mul_sld_gs finished [took 357.3344s]
-04/11/23 03:14:14| INFO bin_sld_gsq finished [took 369.1636s]
-04/11/23 03:14:22| INFO bin_pacc_gs finished [took 372.8646s]
-04/11/23 03:18:40| INFO bin_sld_gs finished [took 636.9190s]
-04/11/23 03:18:40| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 640.2322s]
-04/11/23 03:18:40| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-04/11/23 03:18:46| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 03:19:58| INFO ref finished [took 65.9462s]
-04/11/23 03:20:02| INFO atc_mc finished [took 68.5710s]
-04/11/23 03:20:04| INFO atc_ne finished [took 68.9466s]
-04/11/23 03:20:06| INFO mul_pacc finished [took 77.9039s]
-04/11/23 03:20:06| INFO mul_sld finished [took 84.0917s]
-04/11/23 03:20:37| INFO mul_pacc_gs finished [took 106.2536s]
-04/11/23 03:23:04| INFO bin_pacc finished [took 257.4211s]
-04/11/23 03:23:05| INFO bin_sld finished [took 264.3442s]
-04/11/23 03:24:49| INFO mul_sld_gs finished [took 365.1691s]
-04/11/23 03:25:01| INFO bin_pacc_gs finished [took 371.9184s]
-04/11/23 03:25:02| INFO bin_sld_gsq finished [took 377.0442s]
-04/11/23 03:29:37| INFO bin_sld_gs finished [took 654.0366s]
-04/11/23 03:29:37| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 657.0840s]
-04/11/23 03:29:37| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-04/11/23 03:29:42| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 03:30:51| INFO ref finished [took 62.7217s]
-04/11/23 03:30:58| INFO atc_mc finished [took 67.8613s]
-04/11/23 03:31:00| INFO atc_ne finished [took 68.5026s]
-04/11/23 03:31:03| INFO mul_sld finished [took 83.8857s]
-04/11/23 03:31:03| INFO mul_pacc finished [took 78.6340s]
-04/11/23 03:31:30| INFO mul_pacc_gs finished [took 103.4683s]
-04/11/23 03:34:00| INFO bin_sld finished [took 262.4457s]
-04/11/23 03:34:02| INFO bin_pacc finished [took 258.2247s]
-04/11/23 03:35:44| INFO mul_sld_gs finished [took 363.8135s]
-04/11/23 03:35:58| INFO bin_pacc_gs finished [took 372.0485s]
-04/11/23 03:36:05| INFO bin_sld_gsq finished [took 382.9585s]
-04/11/23 03:40:39| INFO bin_sld_gs finished [took 659.6222s]
-04/11/23 03:40:39| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 662.5763s]
-04/11/23 03:40:39| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-04/11/23 03:40:45| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 03:41:56| INFO ref finished [took 64.5923s]
-04/11/23 03:42:01| INFO atc_mc finished [took 68.0148s]
-04/11/23 03:42:03| INFO atc_ne finished [took 68.3119s]
-04/11/23 03:42:04| INFO mul_pacc finished [took 76.9397s]
-04/11/23 03:42:07| INFO mul_sld finished [took 85.5363s]
-04/11/23 03:42:34| INFO mul_pacc_gs finished [took 103.4448s]
-04/11/23 03:45:01| INFO bin_sld finished [took 260.0814s]
-04/11/23 03:45:03| INFO bin_pacc finished [took 256.9386s]
-04/11/23 03:46:45| INFO mul_sld_gs finished [took 361.5910s]
-04/11/23 03:47:01| INFO bin_pacc_gs finished [took 371.9657s]
-04/11/23 03:47:13| INFO bin_sld_gsq finished [took 388.2498s]
-04/11/23 03:51:40| INFO bin_sld_gs finished [took 657.4008s]
-04/11/23 03:51:40| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 660.5115s]
-04/11/23 03:51:40| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-04/11/23 03:51:46| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 03:52:54| INFO ref finished [took 61.9225s]
-04/11/23 03:53:00| INFO atc_mc finished [took 66.3156s]
-04/11/23 03:53:02| INFO atc_ne finished [took 66.5025s]
-04/11/23 03:53:04| INFO mul_pacc finished [took 75.8808s]
-04/11/23 03:53:06| INFO mul_sld finished [took 84.3204s]
-04/11/23 03:53:33| INFO mul_pacc_gs finished [took 102.5763s]
-04/11/23 03:56:04| INFO bin_sld finished [took 263.2781s]
-04/11/23 03:56:04| INFO bin_pacc finished [took 257.7298s]
-04/11/23 03:57:44| INFO mul_sld_gs finished [took 359.7910s]
-04/11/23 03:58:00| INFO bin_pacc_gs finished [took 371.3848s]
-04/11/23 03:58:11| INFO bin_sld_gsq finished [took 386.0904s]
-04/11/23 04:02:50| INFO bin_sld_gs finished [took 667.6623s]
-04/11/23 04:02:50| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 670.7255s]
-04/11/23 04:02:50| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-04/11/23 04:02:57| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 04:04:05| INFO ref finished [took 62.3256s]
-04/11/23 04:04:13| INFO atc_mc finished [took 68.9525s]
-04/11/23 04:04:15| INFO atc_ne finished [took 68.8750s]
-04/11/23 04:04:16| INFO mul_pacc finished [took 77.5049s]
-04/11/23 04:04:19| INFO mul_sld finished [took 86.0694s]
-04/11/23 04:04:45| INFO mul_pacc_gs finished [took 103.3513s]
-04/11/23 04:07:15| INFO bin_pacc finished [took 257.6456s]
-04/11/23 04:07:16| INFO bin_sld finished [took 263.9914s]
-04/11/23 04:08:55| INFO mul_sld_gs finished [took 360.5634s]
-04/11/23 04:09:12| INFO bin_pacc_gs finished [took 372.2665s]
-04/11/23 04:09:18| INFO bin_sld_gsq finished [took 381.8311s]
-04/11/23 04:13:39| INFO bin_sld_gs finished [took 645.3599s]
-04/11/23 04:13:39| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 648.5328s]
-04/11/23 04:13:39| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-04/11/23 04:13:45| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 04:14:51| INFO ref finished [took 59.8110s]
-04/11/23 04:14:58| INFO atc_mc finished [took 65.2666s]
-04/11/23 04:14:59| INFO atc_ne finished [took 64.5173s]
-04/11/23 04:15:01| INFO mul_pacc finished [took 73.8332s]
-04/11/23 04:15:04| INFO mul_sld finished [took 82.3509s]
-04/11/23 04:15:29| INFO mul_pacc_gs finished [took 99.3541s]
-04/11/23 04:18:00| INFO bin_pacc finished [took 254.3308s]
-04/11/23 04:18:03| INFO bin_sld finished [took 262.3008s]
-04/11/23 04:19:40| INFO mul_sld_gs finished [took 357.1229s]
-04/11/23 04:19:57| INFO bin_pacc_gs finished [took 368.4516s]
-04/11/23 04:20:03| INFO bin_sld_gsq finished [took 378.7658s]
-04/11/23 04:24:37| INFO bin_sld_gs finished [took 655.1931s]
-04/11/23 04:24:37| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 658.3505s]
-04/11/23 04:24:37| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-04/11/23 04:24:43| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
-04/11/23 04:25:49| INFO ref finished [took 59.4546s]
-04/11/23 04:25:55| INFO atc_mc finished [took 63.5805s]
-04/11/23 04:25:58| INFO atc_ne finished [took 63.2985s]
-04/11/23 04:25:58| INFO mul_pacc finished [took 72.5198s]
-04/11/23 04:26:11| INFO mul_sld finished [took 91.7136s]
-04/11/23 04:26:27| INFO mul_pacc_gs finished [took 98.8722s]
-04/11/23 04:28:57| INFO bin_pacc finished [took 252.8144s]
-04/11/23 04:29:02| INFO bin_sld finished [took 263.8013s]
-04/11/23 04:30:35| INFO mul_sld_gs finished [took 353.3693s]
-04/11/23 04:30:51| INFO bin_sld_gsq finished [took 368.8564s]
-04/11/23 04:30:54| INFO bin_pacc_gs finished [took 367.5592s]
-04/11/23 04:35:11| INFO bin_sld_gs finished [took 630.6700s]
-04/11/23 04:35:11| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 633.7494s]
-----------------------------------------------------------------------------------------------------
-04/11/23 19:09:42| INFO dataset rcv1_CCAT_9prevs
-04/11/23 19:09:47| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:10:28| INFO ref finished [took 36.0351s]
-04/11/23 19:10:32| INFO atc_mc finished [took 38.9507s]
-04/11/23 19:10:35| INFO mulmc_sld finished [took 43.7869s]
-04/11/23 19:10:50| INFO mul_sld finished [took 60.8007s]
-04/11/23 19:10:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 62.9600s]
-04/11/23 19:10:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:11:29| INFO ref finished [took 36.3632s]
-04/11/23 19:11:34| INFO atc_mc finished [took 39.5928s]
-04/11/23 19:11:36| INFO mulmc_sld finished [took 44.2915s]
-04/11/23 19:11:44| INFO mul_sld finished [took 52.6727s]
-04/11/23 19:11:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 54.0362s]
-04/11/23 19:11:44| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:12:24| INFO ref finished [took 36.4303s]
-04/11/23 19:12:27| INFO atc_mc finished [took 39.2329s]
-04/11/23 19:12:30| INFO mulmc_sld finished [took 43.6247s]
-04/11/23 19:12:36| INFO mul_sld finished [took 50.2041s]
-04/11/23 19:12:36| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 51.6412s]
-04/11/23 19:12:36| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:13:16| INFO ref finished [took 36.7551s]
-04/11/23 19:13:19| INFO atc_mc finished [took 39.2806s]
-04/11/23 19:13:21| INFO mulmc_sld finished [took 43.6120s]
-04/11/23 19:13:27| INFO mul_sld finished [took 50.4446s]
-04/11/23 19:13:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 51.6672s]
-04/11/23 19:13:27| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:14:07| INFO ref finished [took 35.8789s]
-04/11/23 19:14:11| INFO atc_mc finished [took 39.2168s]
-04/11/23 19:14:13| INFO mulmc_sld finished [took 43.4580s]
-04/11/23 19:14:20| INFO mul_sld finished [took 51.2902s]
-04/11/23 19:14:20| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 52.6303s]
-04/11/23 19:14:20| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:15:00| INFO ref finished [took 36.3735s]
-04/11/23 19:15:04| INFO atc_mc finished [took 39.7035s]
-04/11/23 19:15:06| INFO mulmc_sld finished [took 43.6364s]
-04/11/23 19:15:13| INFO mul_sld finished [took 52.0138s]
-04/11/23 19:15:13| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 53.3303s]
-04/11/23 19:15:13| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:15:54| INFO ref finished [took 37.3366s]
-04/11/23 19:15:57| INFO atc_mc finished [took 39.8921s]
-04/11/23 19:16:00| INFO mulmc_sld finished [took 44.5159s]
-04/11/23 19:16:08| INFO mul_sld finished [took 53.0806s]
-04/11/23 19:16:08| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 54.4117s]
-04/11/23 19:16:08| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:16:47| INFO ref finished [took 35.7800s]
-04/11/23 19:16:50| INFO atc_mc finished [took 38.4484s]
-04/11/23 19:16:53| INFO mulmc_sld finished [took 42.7405s]
-04/11/23 19:17:01| INFO mul_sld finished [took 51.5556s]
-04/11/23 19:17:01| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 52.9684s]
-04/11/23 19:17:01| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:17:39| INFO ref finished [took 35.0919s]
-04/11/23 19:17:43| INFO atc_mc finished [took 38.1718s]
-04/11/23 19:17:45| INFO mulmc_sld finished [took 42.4413s]
-04/11/23 19:17:59| INFO mul_sld finished [took 57.0766s]
-04/11/23 19:17:59| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 58.3668s]
-----------------------------------------------------------------------------------------------------
-04/11/23 19:42:38| INFO dataset rcv1_CCAT_9prevs
-04/11/23 19:42:43| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:43:27| INFO ref finished [took 38.7664s]
-04/11/23 19:43:31| INFO atc_mc finished [took 42.4000s]
-04/11/23 19:43:33| INFO mulmc_sld finished [took 47.0913s]
-04/11/23 19:43:34| INFO binmc_sld finished [took 47.1675s]
-04/11/23 19:43:49| INFO mul_sld finished [took 64.1382s]
-04/11/23 19:46:00| INFO bin_sld finished [took 195.9822s]
-04/11/23 19:46:00| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 197.2916s]
-04/11/23 19:46:00| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:46:44| INFO ref finished [took 38.5976s]
-04/11/23 19:46:48| INFO atc_mc finished [took 41.9465s]
-04/11/23 19:46:49| INFO mulmc_sld finished [took 46.2205s]
-04/11/23 19:46:51| INFO binmc_sld finished [took 46.7475s]
-04/11/23 19:46:58| INFO mul_sld finished [took 56.3552s]
-04/11/23 19:49:14| INFO bin_sld finished [took 193.2923s]
-04/11/23 19:49:14| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 194.6251s]
-04/11/23 19:49:14| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:49:58| INFO ref finished [took 38.3754s]
-04/11/23 19:50:02| INFO atc_mc finished [took 41.0091s]
-04/11/23 19:50:03| INFO mulmc_sld finished [took 45.6205s]
-04/11/23 19:50:05| INFO binmc_sld finished [took 46.1852s]
-04/11/23 19:50:10| INFO mul_sld finished [took 52.9704s]
-04/11/23 19:52:27| INFO bin_sld finished [took 190.6101s]
-04/11/23 19:52:27| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 192.0378s]
-04/11/23 19:52:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:53:10| INFO ref finished [took 38.4467s]
-04/11/23 19:53:13| INFO atc_mc finished [took 41.2602s]
-04/11/23 19:53:15| INFO mulmc_sld finished [took 45.7496s]
-04/11/23 19:53:16| INFO binmc_sld finished [took 45.5531s]
-04/11/23 19:53:21| INFO mul_sld finished [took 52.5067s]
-04/11/23 19:55:38| INFO bin_sld finished [took 190.7744s]
-04/11/23 19:55:38| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 191.9715s]
-04/11/23 19:55:39| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:56:21| INFO ref finished [took 37.9420s]
-04/11/23 19:56:26| INFO atc_mc finished [took 41.2056s]
-04/11/23 19:56:27| INFO mulmc_sld finished [took 45.7577s]
-04/11/23 19:56:28| INFO binmc_sld finished [took 45.6411s]
-04/11/23 19:56:34| INFO mul_sld finished [took 53.5219s]
-04/11/23 19:58:51| INFO bin_sld finished [took 191.1772s]
-04/11/23 19:58:51| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 192.4566s]
-04/11/23 19:58:51| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-04/11/23 19:59:34| INFO ref finished [took 37.8604s]
-04/11/23 19:59:38| INFO atc_mc finished [took 41.0334s]
-04/11/23 19:59:39| INFO mulmc_sld finished [took 45.1999s]
-04/11/23 19:59:40| INFO binmc_sld finished [took 45.4846s]
-04/11/23 19:59:47| INFO mul_sld finished [took 54.3166s]
-04/11/23 20:02:04| INFO bin_sld finished [took 191.4002s]
-04/11/23 20:02:04| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 192.6275s]
-04/11/23 20:02:04| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-04/11/23 20:02:48| INFO ref finished [took 38.8313s]
-04/11/23 20:02:52| INFO atc_mc finished [took 42.1162s]
-04/11/23 20:02:54| INFO mulmc_sld finished [took 47.0413s]
-04/11/23 20:02:55| INFO binmc_sld finished [took 46.8891s]
-04/11/23 20:03:02| INFO mul_sld finished [took 55.8821s]
-04/11/23 20:05:19| INFO bin_sld finished [took 193.7571s]
-04/11/23 20:05:19| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 195.2404s]
-04/11/23 20:05:19| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-04/11/23 20:06:03| INFO ref finished [took 38.7982s]
-04/11/23 20:06:06| INFO atc_mc finished [took 41.6213s]
-04/11/23 20:06:08| INFO mulmc_sld finished [took 46.2646s]
-04/11/23 20:06:09| INFO binmc_sld finished [took 46.2453s]
-04/11/23 20:06:16| INFO mul_sld finished [took 54.8621s]
-04/11/23 20:08:35| INFO bin_sld finished [took 194.5226s]
-04/11/23 20:08:35| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 195.9251s]
-04/11/23 20:08:35| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-04/11/23 20:09:18| INFO ref finished [took 38.3873s]
-04/11/23 20:09:22| INFO atc_mc finished [took 41.2537s]
-04/11/23 20:09:24| INFO mulmc_sld finished [took 46.2211s]
-04/11/23 20:09:25| INFO binmc_sld finished [took 46.6421s]
-04/11/23 20:09:38| INFO mul_sld finished [took 60.9539s]
-04/11/23 20:11:51| INFO bin_sld finished [took 195.1888s]
-04/11/23 20:11:51| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 196.4776s]
-----------------------------------------------------------------------------------------------------
-04/11/23 20:56:32| INFO dataset rcv1_CCAT_9prevs
-04/11/23 20:56:37| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-04/11/23 20:57:33| INFO ref finished [took 49.2697s]
-04/11/23 20:57:38| INFO atc_mc finished [took 53.2068s]
-04/11/23 20:57:39| INFO mulmc_sld finished [took 58.6224s]
-04/11/23 20:58:59| INFO mulmc_sld_gs finished [took 136.0930s]
-04/11/23 21:00:30| INFO binmc_sld finished [took 230.3290s]
-04/11/23 21:02:12| INFO mul_sld_gs finished [took 333.4899s]
-04/11/23 21:06:49| INFO bin_sld_gs finished [took 610.5751s]
-04/11/23 21:06:54| INFO binmc_sld_gs finished [took 612.8900s]
-04/11/23 21:06:55| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 617.6873s]
-04/11/23 21:06:55| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-04/11/23 21:07:52| INFO ref finished [took 49.8077s]
-04/11/23 21:07:56| INFO atc_mc finished [took 53.3303s]
-04/11/23 21:07:57| INFO mulmc_sld finished [took 58.9345s]
-04/11/23 21:09:17| INFO mulmc_sld_gs finished [took 136.5258s]
-04/11/23 21:10:51| INFO binmc_sld finished [took 233.4049s]
-04/11/23 21:12:35| INFO mul_sld_gs finished [took 338.2751s]
-04/11/23 21:17:38| INFO bin_sld_gs finished [took 641.8524s]
-04/11/23 21:18:19| INFO binmc_sld_gs finished [took 679.9471s]
-04/11/23 21:18:19| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 684.7098s]
-04/11/23 21:18:19| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-04/11/23 21:19:24| INFO ref finished [took 55.3767s]
-04/11/23 21:19:28| INFO mulmc_sld finished [took 64.2789s]
-04/11/23 21:19:29| INFO atc_mc finished [took 59.5610s]
-04/11/23 21:20:57| INFO mulmc_sld_gs finished [took 150.1392s]
-04/11/23 21:22:36| INFO binmc_sld finished [took 253.0960s]
-04/11/23 21:24:16| INFO mul_sld_gs finished [took 354.6283s]
-04/11/23 21:29:15| INFO bin_sld_gs finished [took 654.3325s]
-04/11/23 21:29:50| INFO binmc_sld_gs finished [took 684.5074s]
-04/11/23 21:29:50| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 690.4897s]
-04/11/23 21:29:50| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-04/11/23 21:30:45| INFO ref finished [took 48.2647s]
-04/11/23 21:30:51| INFO atc_mc finished [took 52.2724s]
-04/11/23 21:30:51| INFO mulmc_sld finished [took 57.5142s]
-04/11/23 21:32:07| INFO mulmc_sld_gs finished [took 131.4908s]
-04/11/23 21:33:38| INFO binmc_sld finished [took 224.9620s]
-04/11/23 21:35:22| INFO mul_sld_gs finished [took 329.9053s]
-04/11/23 21:40:25| INFO bin_sld_gs finished [took 634.4342s]
-04/11/23 21:41:08| INFO binmc_sld_gs finished [took 673.6071s]
-04/11/23 21:41:08| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 678.4725s]
-04/11/23 21:41:08| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-04/11/23 21:42:03| INFO ref finished [took 47.4381s]
-04/11/23 21:42:08| INFO atc_mc finished [took 51.3566s]
-04/11/23 21:42:09| INFO mulmc_sld finished [took 56.6180s]
-04/11/23 21:43:23| INFO mulmc_sld_gs finished [took 128.6413s]
-04/11/23 21:44:54| INFO binmc_sld finished [took 222.7951s]
-04/11/23 21:46:39| INFO mul_sld_gs finished [took 328.8118s]
-04/11/23 21:51:37| INFO bin_sld_gs finished [took 627.4937s]
-04/11/23 21:52:17| INFO binmc_sld_gs finished [took 663.8116s]
-04/11/23 21:52:17| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 668.8948s]
-04/11/23 21:52:17| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-04/11/23 21:53:12| INFO ref finished [took 47.6269s]
-04/11/23 21:53:16| INFO atc_mc finished [took 51.1109s]
-04/11/23 21:53:17| INFO mulmc_sld finished [took 56.5728s]
-04/11/23 21:54:31| INFO mulmc_sld_gs finished [took 128.0358s]
-04/11/23 21:56:00| INFO binmc_sld finished [took 220.0811s]
-04/11/23 21:57:46| INFO mul_sld_gs finished [took 327.0856s]
-04/11/23 22:02:58| INFO bin_sld_gs finished [took 639.3432s]
-04/11/23 22:03:48| INFO binmc_sld_gs finished [took 686.2326s]
-04/11/23 22:03:48| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 690.9677s]
-04/11/23 22:03:48| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-04/11/23 22:04:42| INFO ref finished [took 47.2804s]
-04/11/23 22:04:48| INFO atc_mc finished [took 51.6888s]
-04/11/23 22:04:48| INFO mulmc_sld finished [took 56.1465s]
-04/11/23 22:06:06| INFO mulmc_sld_gs finished [took 132.4278s]
-04/11/23 22:07:33| INFO binmc_sld finished [took 221.9299s]
-04/11/23 22:09:19| INFO mul_sld_gs finished [took 329.1446s]
-04/11/23 22:14:09| INFO bin_sld_gs finished [took 619.3584s]
-04/11/23 22:14:32| INFO binmc_sld_gs finished [took 638.7326s]
-04/11/23 22:14:32| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 643.6278s]
-04/11/23 22:14:32| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-04/11/23 22:15:26| INFO ref finished [took 47.3139s]
-04/11/23 22:15:30| INFO atc_mc finished [took 50.8602s]
-04/11/23 22:15:32| INFO mulmc_sld finished [took 56.5107s]
-04/11/23 22:16:47| INFO mulmc_sld_gs finished [took 129.5292s]
-04/11/23 22:18:22| INFO binmc_sld finished [took 226.9238s]
-04/11/23 22:20:02| INFO mul_sld_gs finished [took 327.7014s]
-04/11/23 22:24:57| INFO bin_sld_gs finished [took 624.4254s]
-04/11/23 22:25:13| INFO binmc_sld_gs finished [took 636.2675s]
-04/11/23 22:25:13| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 641.0382s]
-04/11/23 22:25:13| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-04/11/23 22:26:07| INFO ref finished [took 47.3224s]
-04/11/23 22:26:12| INFO atc_mc finished [took 51.1828s]
-04/11/23 22:26:13| INFO mulmc_sld finished [took 56.6133s]
-04/11/23 22:27:30| INFO mulmc_sld_gs finished [took 131.3662s]
-04/11/23 22:29:05| INFO binmc_sld finished [took 229.3002s]
-04/11/23 22:30:38| INFO mul_sld_gs finished [took 323.5271s]
-04/11/23 22:35:21| INFO bin_sld_gs finished [took 606.6430s]
-04/11/23 22:35:30| INFO binmc_sld_gs finished [took 612.5966s]
-04/11/23 22:35:30| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 617.3109s]
-----------------------------------------------------------------------------------------------------
-04/11/23 22:49:37| ERROR Evaluation over rcv1_CCAT_3prevs failed. Exception: 'Invalid estimator: estimator binmc_sld_gs does not exist'
-04/11/23 22:49:37| ERROR Failed while saving configuration rcv1_CCAT_debug of rcv1_CCAT_3prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
-----------------------------------------------------------------------------------------------------
-04/11/23 22:50:07| INFO dataset rcv1_CCAT_3prevs
-04/11/23 22:50:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-----------------------------------------------------------------------------------------------------
-04/11/23 22:55:55| INFO dataset rcv1_CCAT_3prevs
-04/11/23 22:55:59| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 22:56:48| INFO ref finished [took 44.4275s]
-----------------------------------------------------------------------------------------------------
-04/11/23 22:56:59| INFO dataset rcv1_CCAT_3prevs
-04/11/23 22:57:03| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 22:57:09| WARNING Method mul_sld_gs failed. Exception: '>=' not supported between instances of 'TypeError' and 'int'
-04/11/23 22:57:17| WARNING Method bin_sld_gs failed. Exception: '>=' not supported between instances of 'TypeError' and 'int'
-----------------------------------------------------------------------------------------------------
-04/11/23 22:58:04| INFO dataset rcv1_CCAT_3prevs
-04/11/23 22:58:09| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 22:58:58| INFO ref finished [took 43.7541s]
-04/11/23 22:59:05| INFO atc_mc finished [took 50.0628s]
-----------------------------------------------------------------------------------------------------
-04/11/23 23:01:22| INFO dataset rcv1_CCAT_3prevs
-04/11/23 23:01:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 23:02:16| INFO ref finished [took 43.9765s]
-04/11/23 23:02:23| INFO atc_mc finished [took 50.5568s]
-----------------------------------------------------------------------------------------------------
-04/11/23 23:09:33| INFO dataset rcv1_CCAT_3prevs
-04/11/23 23:09:37| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 23:09:38| WARNING Method binmc_sld failed. Exception: classifier and pred_proba cannot be both None
-04/11/23 23:09:39| WARNING Method mulmc_sld failed. Exception: classifier and pred_proba cannot be both None
-04/11/23 23:09:40| WARNING Method bin_sld_gs failed. Exception: no combination of hyperparameters seem to work
-04/11/23 23:09:41| WARNING Method mul_sld_gs failed. Exception: no combination of hyperparameters seem to work
-----------------------------------------------------------------------------------------------------
-04/11/23 23:10:23| INFO dataset rcv1_CCAT_3prevs
-04/11/23 23:10:28| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 23:11:15| INFO ref finished [took 42.4887s]
-04/11/23 23:11:20| INFO atc_mc finished [took 45.6262s]
-04/11/23 23:11:21| INFO mulmc_sld finished [took 50.9790s]
-04/11/23 23:13:57| INFO binmc_sld finished [took 208.3159s]
-----------------------------------------------------------------------------------------------------
-04/11/23 23:16:22| INFO dataset rcv1_CCAT_3prevs
-04/11/23 23:16:26| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-04/11/23 23:17:12| INFO ref finished [took 40.5978s]
-04/11/23 23:17:16| INFO atc_mc finished [took 43.6933s]
-04/11/23 23:17:17| INFO mulmc_sld finished [took 49.0808s]
-04/11/23 23:19:53| INFO binmc_sld finished [took 205.5731s]
-04/11/23 23:22:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00672) [took 354.1411s]
-04/11/23 23:23:05| INFO mul_sld_gs finished [took 394.8240s]
-04/11/23 23:30:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00891) [took 852.1465s]
-04/11/23 23:33:44| INFO bin_sld_gs finished [took 1035.2071s]
-04/11/23 23:33:44| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs finished [took 1038.1845s]
-04/11/23 23:33:44| INFO Dataset sample 0.50 of dataset rcv1_CCAT_3prevs started
-04/11/23 23:34:33| INFO ref finished [took 43.6409s]
-04/11/23 23:34:37| INFO atc_mc finished [took 46.7818s]
-04/11/23 23:34:38| INFO mulmc_sld finished [took 51.3459s]
-04/11/23 23:37:15| INFO binmc_sld finished [took 209.5746s]
-04/11/23 23:39:48| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00553) [took 359.3210s]
-04/11/23 23:40:28| INFO mul_sld_gs finished [took 399.5320s]
-04/11/23 23:48:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': None} (score=0.01058) [took 855.1289s]
-04/11/23 23:51:06| INFO bin_sld_gs finished [took 1038.6344s]
-04/11/23 23:51:06| INFO Dataset sample 0.50 of dataset rcv1_CCAT_3prevs finished [took 1041.6478s]
-04/11/23 23:51:06| INFO Dataset sample 0.60 of dataset rcv1_CCAT_3prevs started
-04/11/23 23:51:51| INFO ref finished [took 40.0694s]
-04/11/23 23:51:55| INFO atc_mc finished [took 42.4882s]
-04/11/23 23:51:56| INFO mulmc_sld finished [took 47.7936s]
-04/11/23 23:54:29| INFO binmc_sld finished [took 201.3777s]
-04/11/23 23:57:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00429) [took 352.7820s]
-04/11/23 23:57:43| INFO mul_sld_gs finished [took 392.5201s]
-05/11/23 00:05:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.00552) [took 851.9361s]
-05/11/23 00:08:24| INFO bin_sld_gs finished [took 1034.7353s]
-05/11/23 00:08:24| INFO Dataset sample 0.60 of dataset rcv1_CCAT_3prevs finished [took 1037.8033s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:11:07| INFO dataset rcv1_CCAT_3prevs
-05/11/23 00:11:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
-----------------------------------------------------------------------------------------------------
-05/11/23 00:28:39| INFO dataset imdb_3prevs
-05/11/23 00:28:46| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 00:28:55| INFO ref finished [took 8.7347s]
-05/11/23 00:28:58| INFO atc_mc finished [took 11.6376s]
-05/11/23 00:28:59| INFO mulmc_sld finished [took 13.5476s]
-05/11/23 00:28:59| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 13.9513s]
-05/11/23 00:28:59| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 00:29:09| INFO ref finished [took 8.7049s]
-05/11/23 00:29:12| INFO atc_mc finished [took 11.6170s]
-05/11/23 00:29:14| INFO mulmc_sld finished [took 13.7416s]
-05/11/23 00:29:14| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.2842s]
-05/11/23 00:29:14| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 00:29:23| INFO ref finished [took 8.6894s]
-05/11/23 00:29:26| INFO atc_mc finished [took 11.5275s]
-05/11/23 00:29:28| INFO mulmc_sld finished [took 13.6977s]
-05/11/23 00:29:28| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.2742s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:34:12| INFO dataset imdb_3prevs
-05/11/23 00:34:22| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 00:34:41| INFO ref finished [took 17.6558s]
-05/11/23 00:34:46| INFO mulmc_sld finished [took 22.9646s]
-05/11/23 00:34:48| INFO atc_mc finished [took 24.5871s]
-05/11/23 00:34:48| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 25.3179s]
-05/11/23 00:34:48| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 00:35:05| INFO ref finished [took 17.2188s]
-05/11/23 00:35:10| INFO mulmc_sld finished [took 22.2420s]
-05/11/23 00:35:12| INFO atc_mc finished [took 23.9752s]
-05/11/23 00:35:12| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 24.7688s]
-05/11/23 00:35:12| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 00:35:33| INFO ref finished [took 20.0731s]
-05/11/23 00:35:38| INFO mulmc_sld finished [took 24.8736s]
-05/11/23 00:35:40| INFO atc_mc finished [took 27.0318s]
-05/11/23 00:35:40| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 27.8108s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:39:57| INFO dataset imdb_1prevs
-05/11/23 00:40:07| INFO Dataset sample 0.50 of dataset imdb_1prevs started
-05/11/23 00:40:26| INFO ref finished [took 17.4863s]
-05/11/23 00:40:31| INFO mulmc_sld finished [took 22.5384s]
-05/11/23 00:40:33| INFO atc_mc finished [took 24.2747s]
-05/11/23 00:40:33| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 25.6430s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:41:36| INFO dataset imdb_2prevs
-05/11/23 00:41:46| INFO Dataset sample 0.20 of dataset imdb_2prevs started
-05/11/23 00:42:05| INFO ref finished [took 17.6637s]
-05/11/23 00:42:10| INFO mulmc_sld finished [took 22.6956s]
-05/11/23 00:42:11| INFO atc_mc finished [took 24.3529s]
-05/11/23 00:42:11| INFO Dataset sample 0.20 of dataset imdb_2prevs finished [took 25.0708s]
-05/11/23 00:42:11| INFO Dataset sample 0.80 of dataset imdb_2prevs started
-05/11/23 00:42:29| INFO ref finished [took 17.2818s]
-05/11/23 00:42:34| INFO mulmc_sld finished [took 22.4054s]
-05/11/23 00:42:36| INFO atc_mc finished [took 23.9392s]
-05/11/23 00:42:36| INFO Dataset sample 0.80 of dataset imdb_2prevs finished [took 24.7193s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:45:54| INFO dataset imdb_2prevs
-05/11/23 00:46:04| INFO Dataset sample 0.20 of dataset imdb_2prevs started
-05/11/23 00:46:22| INFO ref finished [took 17.2217s]
-05/11/23 00:46:27| INFO mulmc_sld finished [took 22.2712s]
-05/11/23 00:46:28| INFO atc_mc finished [took 23.7770s]
-05/11/23 00:46:28| INFO Dataset sample 0.20 of dataset imdb_2prevs finished [took 24.5092s]
-05/11/23 00:46:28| INFO Dataset sample 0.80 of dataset imdb_2prevs started
-05/11/23 00:46:46| INFO ref finished [took 17.1303s]
-05/11/23 00:46:51| INFO mulmc_sld finished [took 22.5084s]
-05/11/23 00:46:53| INFO atc_mc finished [took 23.9160s]
-05/11/23 00:46:53| INFO Dataset sample 0.80 of dataset imdb_2prevs finished [took 24.6992s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:51:06| INFO dataset imdb_2prevs
-05/11/23 00:51:16| INFO Dataset sample 0.20 of dataset imdb_2prevs started
-05/11/23 00:51:33| INFO ref finished [took 17.0670s]
-05/11/23 00:51:38| INFO mulmc_sld finished [took 22.3141s]
-05/11/23 00:51:40| INFO atc_mc finished [took 23.7219s]
-05/11/23 00:51:40| INFO Dataset sample 0.20 of dataset imdb_2prevs finished [took 24.4385s]
-05/11/23 00:51:40| INFO Dataset sample 0.80 of dataset imdb_2prevs started
-05/11/23 00:51:58| INFO ref finished [took 17.1894s]
-05/11/23 00:52:03| INFO mulmc_sld finished [took 22.4247s]
-05/11/23 00:52:04| INFO atc_mc finished [took 23.6032s]
-05/11/23 00:52:04| INFO Dataset sample 0.80 of dataset imdb_2prevs finished [took 24.3674s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:53:32| INFO dataset imdb_3prevs
-05/11/23 00:53:39| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 00:53:48| INFO ref finished [took 8.8062s]
-05/11/23 00:53:51| INFO atc_mc finished [took 11.7173s]
-05/11/23 00:53:53| INFO mulmc_sld finished [took 13.8761s]
-05/11/23 00:53:53| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 14.3147s]
-05/11/23 00:53:53| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 00:54:03| INFO ref finished [took 8.9071s]
-05/11/23 00:54:06| INFO atc_mc finished [took 11.7005s]
-05/11/23 00:54:08| INFO mulmc_sld finished [took 13.6266s]
-05/11/23 00:54:08| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.1625s]
-05/11/23 00:54:08| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 00:54:17| INFO ref finished [took 8.7680s]
-05/11/23 00:54:20| INFO atc_mc finished [took 11.4957s]
-05/11/23 00:54:22| INFO mulmc_sld finished [took 13.5719s]
-05/11/23 00:54:22| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.1564s]
-----------------------------------------------------------------------------------------------------
-05/11/23 00:57:53| INFO dataset imdb_3prevs
-05/11/23 00:57:59| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 00:58:08| INFO ref finished [took 8.7497s]
-05/11/23 00:58:12| INFO atc_mc finished [took 11.6903s]
-05/11/23 00:58:13| INFO mulmc_sld finished [took 13.6731s]
-05/11/23 00:58:13| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 14.1073s]
-05/11/23 00:58:13| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 00:58:23| INFO ref finished [took 8.7718s]
-05/11/23 00:58:26| INFO atc_mc finished [took 11.7653s]
-05/11/23 00:58:28| INFO mulmc_sld finished [took 13.9184s]
-05/11/23 00:58:28| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.4270s]
-05/11/23 00:58:28| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 00:58:37| INFO ref finished [took 8.8129s]
-05/11/23 00:58:40| INFO atc_mc finished [took 11.7267s]
-05/11/23 00:58:42| INFO mulmc_sld finished [took 13.6726s]
-05/11/23 00:58:42| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.2387s]
-----------------------------------------------------------------------------------------------------
-05/11/23 01:04:04| INFO dataset imdb_3prevs
-05/11/23 01:04:10| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 01:04:20| INFO ref finished [took 8.7879s]
-05/11/23 01:04:23| INFO atc_mc finished [took 11.8757s]
-05/11/23 01:04:25| INFO mulmc_sld finished [took 13.8698s]
-05/11/23 01:04:25| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 14.2927s]
-05/11/23 01:04:25| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 01:04:34| INFO ref finished [took 8.9200s]
-05/11/23 01:04:37| INFO atc_mc finished [took 11.9555s]
-05/11/23 01:04:39| INFO mulmc_sld finished [took 13.9860s]
-05/11/23 01:04:39| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.5339s]
-05/11/23 01:04:39| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 01:04:49| INFO ref finished [took 8.8757s]
-05/11/23 01:04:52| INFO atc_mc finished [took 11.8222s]
-05/11/23 01:04:53| INFO mulmc_sld finished [took 13.7034s]
-05/11/23 01:04:53| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.2710s]
-----------------------------------------------------------------------------------------------------
-05/11/23 01:08:05| INFO dataset rcv1_CCAT_9prevs
-05/11/23 01:08:09| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 01:08:55| INFO ref finished [took 40.9427s]
-05/11/23 01:09:00| INFO atc_mc finished [took 44.2152s]
-05/11/23 01:09:01| INFO mulmc_sld finished [took 49.6089s]
-05/11/23 01:11:38| INFO bin_sld finished [took 207.5917s]
-05/11/23 01:13:47| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00663) [took 333.7044s]
-05/11/23 01:14:30| INFO mul_sld_gs finished [took 376.3503s]
-05/11/23 01:20:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00619) [took 751.2730s]
-05/11/23 01:23:45| INFO bin_sld_gs finished [took 932.2941s]
-05/11/23 01:23:45| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 935.3228s]
-05/11/23 01:23:45| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 01:24:30| INFO ref finished [took 39.9821s]
-05/11/23 01:24:34| INFO atc_mc finished [took 43.3585s]
-05/11/23 01:24:36| INFO mulmc_sld finished [took 48.6404s]
-05/11/23 01:27:08| INFO bin_sld finished [took 202.3970s]
-05/11/23 01:29:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00699) [took 328.6883s]
-05/11/23 01:30:00| INFO mul_sld_gs finished [took 371.2150s]
-05/11/23 01:36:40| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00780) [took 771.8150s]
-05/11/23 01:39:44| INFO bin_sld_gs finished [took 956.5831s]
-05/11/23 01:39:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 959.5214s]
-05/11/23 01:39:44| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 01:40:38| INFO ref finished [took 46.9727s]
-05/11/23 01:40:42| INFO atc_mc finished [took 49.6456s]
-05/11/23 01:40:43| INFO mulmc_sld finished [took 55.1784s]
-05/11/23 01:43:16| INFO bin_sld finished [took 209.5653s]
-05/11/23 01:45:30| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00720) [took 340.0613s]
-05/11/23 01:46:09| INFO mul_sld_gs finished [took 379.3695s]
-05/11/23 01:53:22| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00810) [took 813.3118s]
-05/11/23 01:56:25| INFO bin_sld_gs finished [took 996.4380s]
-05/11/23 01:56:25| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1000.8297s]
-05/11/23 01:56:25| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 01:57:11| INFO ref finished [took 40.2515s]
-05/11/23 01:57:15| INFO atc_mc finished [took 43.5348s]
-05/11/23 01:57:15| INFO mulmc_sld finished [took 48.1622s]
-05/11/23 01:59:46| INFO bin_sld finished [took 200.0955s]
-05/11/23 02:02:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00644) [took 331.2368s]
-05/11/23 02:02:40| INFO mul_sld_gs finished [took 370.8879s]
-05/11/23 02:10:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.01269) [took 813.7272s]
-05/11/23 02:13:04| INFO bin_sld_gs finished [took 995.6098s]
-05/11/23 02:13:04| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 998.5647s]
-05/11/23 02:13:04| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-05/11/23 02:13:50| INFO ref finished [took 41.4181s]
-05/11/23 02:13:55| INFO atc_mc finished [took 44.8414s]
-05/11/23 02:13:55| INFO mulmc_sld finished [took 49.5767s]
-05/11/23 02:16:27| INFO bin_sld finished [took 201.8696s]
-05/11/23 02:18:33| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00636) [took 325.5401s]
-05/11/23 02:19:17| INFO mul_sld_gs finished [took 368.9682s]
-05/11/23 02:26:26| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00670) [took 799.7618s]
-05/11/23 02:29:29| INFO bin_sld_gs finished [took 982.2921s]
-05/11/23 02:29:29| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 985.2925s]
-05/11/23 02:29:29| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-05/11/23 02:30:14| INFO ref finished [took 40.3341s]
-05/11/23 02:30:18| INFO atc_mc finished [took 43.3032s]
-05/11/23 02:30:19| INFO mulmc_sld finished [took 47.8507s]
-05/11/23 02:32:51| INFO bin_sld finished [took 200.9647s]
-05/11/23 02:34:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00596) [took 321.5172s]
-05/11/23 02:35:33| INFO mul_sld_gs finished [took 360.5222s]
-05/11/23 02:43:22| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.00544) [took 829.7314s]
-05/11/23 02:46:23| INFO bin_sld_gs finished [took 1011.3917s]
-05/11/23 02:46:23| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1014.2514s]
-05/11/23 02:46:23| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-05/11/23 02:47:09| INFO ref finished [took 40.4272s]
-05/11/23 02:47:13| INFO atc_mc finished [took 43.8966s]
-05/11/23 02:47:14| INFO mulmc_sld finished [took 48.4437s]
-05/11/23 02:49:47| INFO bin_sld finished [took 202.6013s]
-05/11/23 02:51:57| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00653) [took 329.4236s]
-05/11/23 02:52:36| INFO mul_sld_gs finished [took 368.7426s]
-05/11/23 02:59:51| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01370) [took 804.3215s]
-05/11/23 03:02:54| INFO bin_sld_gs finished [took 987.5377s]
-05/11/23 03:02:54| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 990.4607s]
-05/11/23 03:02:54| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-05/11/23 03:03:40| INFO ref finished [took 41.5104s]
-05/11/23 03:03:44| INFO atc_mc finished [took 44.1770s]
-05/11/23 03:03:46| INFO mulmc_sld finished [took 49.7176s]
-05/11/23 03:06:27| INFO bin_sld finished [took 211.4985s]
-05/11/23 03:08:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00822) [took 334.7029s]
-05/11/23 03:09:16| INFO mul_sld_gs finished [took 377.8219s]
-05/11/23 03:16:22| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00984) [took 805.4146s]
-05/11/23 03:19:28| INFO bin_sld_gs finished [took 991.0520s]
-05/11/23 03:19:28| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 994.1016s]
-05/11/23 03:19:28| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-05/11/23 03:20:18| INFO ref finished [took 44.1663s]
-05/11/23 03:20:22| INFO atc_mc finished [took 47.3231s]
-05/11/23 03:20:23| INFO mulmc_sld finished [took 53.1243s]
-05/11/23 03:23:10| INFO bin_sld finished [took 220.4921s]
-05/11/23 03:25:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00811) [took 338.9143s]
-05/11/23 03:25:56| INFO mul_sld_gs finished [took 383.9350s]
-05/11/23 03:32:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': None} (score=0.00954) [took 792.6190s]
-05/11/23 03:35:44| INFO bin_sld_gs finished [took 973.2397s]
-05/11/23 03:35:44| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 976.4502s]
-05/11/23 03:35:57| INFO dataset imbd_9prevs
-05/11/23 03:35:57| ERROR Evaluation over imbd_9prevs failed. Exception: 'imbd'
-----------------------------------------------------------------------------------------------------
-05/11/23 09:42:24| INFO dataset imdb_9prevs
-05/11/23 09:42:30| INFO Dataset sample 0.10 of dataset imdb_9prevs started
-05/11/23 09:42:44| INFO ref finished [took 10.6450s]
-05/11/23 09:42:47| INFO atc_mc finished [took 13.9369s]
-05/11/23 09:42:49| INFO mulmc_sld finished [took 16.6526s]
-05/11/23 09:42:56| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-05/11/23 09:45:26| INFO bin_sld finished [took 173.8798s]
-05/11/23 09:47:18| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.03792) [took 285.1339s]
-05/11/23 09:47:33| INFO mul_sld_gs finished [took 300.3243s]
-05/11/23 09:47:33| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 302.7180s]
-05/11/23 09:47:33| INFO Dataset sample 0.20 of dataset imdb_9prevs started
-05/11/23 09:47:46| INFO ref finished [took 12.0501s]
-05/11/23 09:47:50| INFO atc_mc finished [took 15.0907s]
-05/11/23 09:47:52| INFO mulmc_sld finished [took 17.8502s]
-05/11/23 09:50:42| INFO bin_sld finished [took 188.2533s]
-05/11/23 09:53:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.01067) [took 328.6088s]
-05/11/23 09:53:19| INFO mul_sld_gs finished [took 345.1926s]
-05/11/23 10:00:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00923) [took 798.1316s]
-05/11/23 10:03:34| INFO bin_sld_gs finished [took 960.1696s]
-05/11/23 10:03:34| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 960.9823s]
-05/11/23 10:03:34| INFO Dataset sample 0.30 of dataset imdb_9prevs started
-05/11/23 10:03:46| INFO ref finished [took 10.8585s]
-05/11/23 10:03:49| INFO atc_mc finished [took 13.6836s]
-05/11/23 10:03:51| INFO mulmc_sld finished [took 15.8085s]
-05/11/23 10:06:39| INFO bin_sld finished [took 183.7435s]
-05/11/23 10:09:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00707) [took 326.5308s]
-05/11/23 10:09:15| INFO mul_sld_gs finished [took 339.3412s]
-05/11/23 10:16:51| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01094) [took 796.0895s]
-05/11/23 10:19:27| INFO bin_sld_gs finished [took 952.0793s]
-05/11/23 10:19:27| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 953.0580s]
-05/11/23 10:19:27| INFO Dataset sample 0.40 of dataset imdb_9prevs started
-05/11/23 10:19:39| INFO ref finished [took 10.8707s]
-05/11/23 10:19:42| INFO atc_mc finished [took 13.9089s]
-05/11/23 10:19:44| INFO mulmc_sld finished [took 15.9994s]
-05/11/23 10:22:17| INFO bin_sld finished [took 168.9998s]
-05/11/23 10:24:35| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00999) [took 306.5297s]
-05/11/23 10:24:47| INFO mul_sld_gs finished [took 318.6584s]
-05/11/23 10:32:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.01176) [took 782.7189s]
-05/11/23 10:35:07| INFO bin_sld_gs finished [took 939.3830s]
-05/11/23 10:35:07| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 940.2365s]
-05/11/23 10:35:07| INFO Dataset sample 0.50 of dataset imdb_9prevs started
-05/11/23 10:35:19| INFO ref finished [took 10.1160s]
-05/11/23 10:35:22| INFO atc_mc finished [took 13.6292s]
-05/11/23 10:35:24| INFO mulmc_sld finished [took 15.7949s]
-05/11/23 10:38:04| INFO bin_sld finished [took 176.0746s]
-05/11/23 10:40:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01008) [took 319.8045s]
-05/11/23 10:40:45| INFO mul_sld_gs finished [took 336.8792s]
-05/11/23 10:48:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00942) [took 802.9266s]
-05/11/23 10:51:09| INFO bin_sld_gs finished [took 961.0002s]
-05/11/23 10:51:09| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 961.8311s]
-05/11/23 10:51:09| INFO Dataset sample 0.60 of dataset imdb_9prevs started
-05/11/23 10:51:21| INFO ref finished [took 10.7059s]
-05/11/23 10:51:24| INFO atc_mc finished [took 13.8934s]
-05/11/23 10:51:26| INFO mulmc_sld finished [took 16.0295s]
-05/11/23 10:54:09| INFO bin_sld finished [took 179.1806s]
-05/11/23 10:56:31| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00906) [took 320.5350s]
-05/11/23 10:56:45| INFO mul_sld_gs finished [took 334.5485s]
-05/11/23 11:04:55| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01228) [took 824.5702s]
-05/11/23 11:07:33| INFO bin_sld_gs finished [took 983.3806s]
-05/11/23 11:07:33| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 984.1981s]
-05/11/23 11:07:34| INFO Dataset sample 0.70 of dataset imdb_9prevs started
-05/11/23 11:07:45| INFO ref finished [took 10.7034s]
-05/11/23 11:07:49| INFO atc_mc finished [took 14.0668s]
-05/11/23 11:07:51| INFO mulmc_sld finished [took 16.2499s]
-----------------------------------------------------------------------------------------------------
-05/11/23 11:09:19| INFO dataset rcv1_CCAT_9prevs
-05/11/23 11:09:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-----------------------------------------------------------------------------------------------------
-05/11/23 11:10:40| INFO dataset rcv1_CCAT_9prevs
-05/11/23 11:10:44| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:11:21| INFO ref finished [took 34.7944s]
-05/11/23 11:11:25| INFO atc_mc finished [took 37.6168s]
-05/11/23 11:11:36| INFO mulmc_sld finished [took 51.0883s]
-05/11/23 11:11:36| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 52.3442s]
-05/11/23 11:11:36| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:12:14| INFO ref finished [took 35.0033s]
-05/11/23 11:12:17| INFO atc_mc finished [took 37.7761s]
-05/11/23 11:12:24| INFO mulmc_sld finished [took 46.2195s]
-05/11/23 11:12:24| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 47.5446s]
-05/11/23 11:12:24| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:13:01| INFO ref finished [took 35.1077s]
-05/11/23 11:13:05| INFO atc_mc finished [took 37.7889s]
-05/11/23 11:13:12| INFO mulmc_sld finished [took 46.6515s]
-05/11/23 11:13:12| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 48.0359s]
-05/11/23 11:13:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:13:49| INFO ref finished [took 35.0214s]
-05/11/23 11:13:53| INFO atc_mc finished [took 37.9480s]
-05/11/23 11:14:00| INFO mulmc_sld finished [took 46.4140s]
-05/11/23 11:14:00| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 47.5164s]
-05/11/23 11:14:00| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:14:37| INFO ref finished [took 35.2699s]
-05/11/23 11:14:41| INFO atc_mc finished [took 37.9490s]
-05/11/23 11:14:49| INFO mulmc_sld finished [took 47.7005s]
-05/11/23 11:14:49| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 49.0189s]
-05/11/23 11:14:49| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:15:26| INFO ref finished [took 35.2350s]
-05/11/23 11:15:30| INFO atc_mc finished [took 38.6364s]
-05/11/23 11:15:39| INFO mulmc_sld finished [took 48.8860s]
-05/11/23 11:15:39| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 50.1097s]
-05/11/23 11:15:39| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:16:16| INFO ref finished [took 35.0322s]
-05/11/23 11:16:20| INFO atc_mc finished [took 38.4809s]
-05/11/23 11:16:29| INFO mulmc_sld finished [took 48.6466s]
-05/11/23 11:16:29| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 50.0372s]
-05/11/23 11:16:29| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:17:06| INFO ref finished [took 35.2988s]
-05/11/23 11:17:10| INFO atc_mc finished [took 38.3390s]
-05/11/23 11:17:18| INFO mulmc_sld finished [took 47.8829s]
-05/11/23 11:17:18| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 49.2700s]
-05/11/23 11:17:18| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:17:56| INFO ref finished [took 35.2614s]
-05/11/23 11:17:59| INFO atc_mc finished [took 38.1131s]
-05/11/23 11:18:08| INFO mulmc_sld finished [took 49.0925s]
-05/11/23 11:18:09| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 50.4765s]
-----------------------------------------------------------------------------------------------------
-05/11/23 11:26:35| INFO dataset rcv1_CCAT_9prevs
-05/11/23 11:26:39| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:27:17| INFO ref finished [took 35.3305s]
-05/11/23 11:27:21| INFO atc_mc finished [took 37.9469s]
-05/11/23 11:27:28| INFO mulmc_sld finished [took 46.9769s]
-05/11/23 11:27:28| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 48.3022s]
-05/11/23 11:27:28| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:28:05| INFO ref finished [took 35.2459s]
-05/11/23 11:28:09| INFO atc_mc finished [took 38.1660s]
-05/11/23 11:28:15| INFO mulmc_sld finished [took 46.3832s]
-05/11/23 11:28:15| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 47.7328s]
-05/11/23 11:28:15| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:28:53| INFO ref finished [took 35.4919s]
-05/11/23 11:28:57| INFO atc_mc finished [took 38.1023s]
-05/11/23 11:29:03| INFO mulmc_sld finished [took 46.4657s]
-05/11/23 11:29:03| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 47.8578s]
-05/11/23 11:29:03| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:29:41| INFO ref finished [took 35.3209s]
-05/11/23 11:29:45| INFO atc_mc finished [took 38.3693s]
-05/11/23 11:29:51| INFO mulmc_sld finished [took 46.5707s]
-05/11/23 11:29:51| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 47.7036s]
-05/11/23 11:29:51| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:30:28| INFO ref finished [took 35.0276s]
-05/11/23 11:30:32| INFO atc_mc finished [took 38.1508s]
-05/11/23 11:30:40| INFO mulmc_sld finished [took 47.6215s]
-05/11/23 11:30:40| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 48.9244s]
-05/11/23 11:30:40| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:31:17| INFO ref finished [took 35.3308s]
-05/11/23 11:31:21| INFO atc_mc finished [took 38.0629s]
-05/11/23 11:31:29| INFO mulmc_sld finished [took 47.8783s]
-05/11/23 11:31:29| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 49.1655s]
-05/11/23 11:31:29| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:32:07| INFO ref finished [took 35.1485s]
-05/11/23 11:32:10| INFO atc_mc finished [took 38.1974s]
-05/11/23 11:32:18| INFO mulmc_sld finished [took 47.6056s]
-05/11/23 11:32:18| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 48.9545s]
-05/11/23 11:32:18| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:32:56| INFO ref finished [took 35.1879s]
-05/11/23 11:32:59| INFO atc_mc finished [took 38.1684s]
-05/11/23 11:33:07| INFO mulmc_sld finished [took 47.5635s]
-05/11/23 11:33:07| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 48.9364s]
-05/11/23 11:33:07| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-05/11/23 11:33:45| INFO ref finished [took 35.5855s]
-05/11/23 11:33:48| INFO atc_mc finished [took 38.1206s]
-05/11/23 11:33:54| INFO mulmc_sld finished [took 45.1957s]
-05/11/23 11:33:54| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 46.5129s]
-----------------------------------------------------------------------------------------------------
-05/11/23 12:02:53| INFO dataset rcv1_CCAT_9prevs
-05/11/23 12:02:58| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:03:01| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
-05/11/23 12:03:37| INFO ref finished [took 34.9513s]
-05/11/23 12:03:41| INFO atc_mc finished [took 37.7710s]
-05/11/23 12:03:47| INFO mulmc_sld finished [took 47.2144s]
-05/11/23 12:03:56| INFO mul_sld finished [took 56.8347s]
-05/11/23 12:03:56| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 58.1052s]
-05/11/23 12:03:56| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:03:59| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
-05/11/23 12:04:36| INFO ref finished [took 35.5921s]
-05/11/23 12:04:40| INFO atc_mc finished [took 38.4587s]
-05/11/23 12:04:46| INFO mulmc_sld finished [took 47.5756s]
-05/11/23 12:04:47| INFO mul_sld finished [took 50.0690s]
-05/11/23 12:04:47| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 51.3609s]
-05/11/23 12:04:47| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:04:50| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
-05/11/23 12:05:28| INFO ref finished [took 36.0399s]
-05/11/23 12:05:31| INFO atc_mc finished [took 38.9414s]
-05/11/23 12:05:38| INFO mulmc_sld finished [took 48.4594s]
-05/11/23 12:05:38| INFO mul_sld finished [took 49.4355s]
-05/11/23 12:05:38| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 50.7799s]
-05/11/23 12:05:38| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:05:41| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
-----------------------------------------------------------------------------------------------------
-05/11/23 12:06:13| INFO dataset rcv1_CCAT_9prevs
-05/11/23 12:06:18| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:07:03| INFO ref finished [took 41.7793s]
-05/11/23 12:07:10| INFO atc_mc finished [took 48.0537s]
-05/11/23 12:07:38| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
-----------------------------------------------------------------------------------------------------
-05/11/23 12:08:00| INFO dataset rcv1_CCAT_9prevs
-05/11/23 12:08:04| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:08:47| INFO ref finished [took 37.5352s]
-05/11/23 12:08:50| INFO atc_mc finished [took 40.2843s]
-05/11/23 12:08:55| INFO mulne_sld finished [took 47.4558s]
-05/11/23 12:08:56| INFO mulmc_sld finished [took 49.8247s]
-05/11/23 12:09:05| INFO mul_sld finished [took 59.5033s]
-05/11/23 12:09:05| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 60.7605s]
-05/11/23 12:09:05| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:09:47| INFO ref finished [took 37.4891s]
-05/11/23 12:09:52| INFO atc_mc finished [took 40.9763s]
-05/11/23 12:09:58| INFO mulmc_sld finished [took 50.3687s]
-05/11/23 12:09:59| INFO mulne_sld finished [took 50.8494s]
-05/11/23 12:10:00| INFO mul_sld finished [took 53.7955s]
-05/11/23 12:10:00| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 55.1095s]
-05/11/23 12:10:00| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:10:44| INFO ref finished [took 39.3665s]
-05/11/23 12:10:49| INFO atc_mc finished [took 43.1884s]
-05/11/23 12:10:55| INFO mul_sld finished [took 53.2533s]
-05/11/23 12:10:55| INFO mulmc_sld finished [took 52.6179s]
-05/11/23 12:10:56| INFO mulne_sld finished [took 52.7117s]
-05/11/23 12:10:56| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 56.0058s]
-05/11/23 12:10:56| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:11:40| INFO ref finished [took 39.1357s]
-05/11/23 12:11:44| INFO atc_mc finished [took 42.7168s]
-05/11/23 12:11:50| INFO mul_sld finished [took 53.1250s]
-05/11/23 12:11:51| INFO mulmc_sld finished [took 52.6875s]
-05/11/23 12:11:51| INFO mulne_sld finished [took 51.9871s]
-05/11/23 12:11:51| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 55.0715s]
-05/11/23 12:11:51| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:12:34| INFO ref finished [took 38.0624s]
-05/11/23 12:12:38| INFO atc_mc finished [took 40.9414s]
-05/11/23 12:12:45| INFO mul_sld finished [took 52.0220s]
-05/11/23 12:12:46| INFO mulmc_sld finished [took 52.0904s]
-05/11/23 12:12:47| INFO mulne_sld finished [took 52.2011s]
-05/11/23 12:12:47| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 55.6901s]
-05/11/23 12:12:47| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:13:29| INFO ref finished [took 37.9734s]
-05/11/23 12:13:34| INFO atc_mc finished [took 41.4316s]
-05/11/23 12:13:41| INFO mulmc_sld finished [took 51.9276s]
-05/11/23 12:13:42| INFO mul_sld finished [took 53.8232s]
-05/11/23 12:13:43| INFO mulne_sld finished [took 52.4359s]
-05/11/23 12:13:43| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 55.5737s]
-05/11/23 12:13:43| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:14:25| INFO ref finished [took 38.1687s]
-05/11/23 12:14:29| INFO atc_mc finished [took 40.6142s]
-05/11/23 12:14:37| INFO mulmc_sld finished [took 52.4191s]
-05/11/23 12:14:38| INFO mul_sld finished [took 53.7962s]
-05/11/23 12:14:38| INFO mulne_sld finished [took 52.1544s]
-05/11/23 12:14:38| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 55.4465s]
-05/11/23 12:14:38| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:15:21| INFO ref finished [took 38.4494s]
-05/11/23 12:15:25| INFO atc_mc finished [took 40.9944s]
-05/11/23 12:15:32| INFO mulmc_sld finished [took 51.8551s]
-05/11/23 12:15:33| INFO mul_sld finished [took 53.4409s]
-05/11/23 12:15:33| INFO mulne_sld finished [took 51.7256s]
-05/11/23 12:15:33| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 55.1132s]
-05/11/23 12:15:33| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:16:16| INFO ref finished [took 38.2838s]
-05/11/23 12:16:20| INFO atc_mc finished [took 41.3532s]
-05/11/23 12:16:24| INFO mulmc_sld finished [took 49.1257s]
-05/11/23 12:16:26| INFO mulne_sld finished [took 49.8205s]
-05/11/23 12:16:34| INFO mul_sld finished [took 59.1323s]
-05/11/23 12:16:34| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 60.4191s]
-----------------------------------------------------------------------------------------------------
-05/11/23 12:23:45| INFO dataset rcv1_CCAT_9prevs
-05/11/23 12:23:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:24:32| INFO ref finished [took 38.5638s]
-05/11/23 12:24:36| INFO atc_mc finished [took 41.5043s]
-05/11/23 12:27:13| INFO binmc_sld finished [took 201.7673s]
-05/11/23 12:27:14| INFO bin_sld finished [took 203.3515s]
-05/11/23 12:27:17| INFO binne_sld finished [took 204.1403s]
-05/11/23 12:27:17| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 207.1212s]
-05/11/23 12:27:17| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:27:59| INFO ref finished [took 37.8990s]
-05/11/23 12:28:02| INFO atc_mc finished [took 40.1947s]
-05/11/23 12:30:36| INFO bin_sld finished [took 197.7408s]
-05/11/23 12:30:37| INFO binne_sld finished [took 197.0819s]
-05/11/23 12:30:37| INFO binmc_sld finished [took 198.5545s]
-05/11/23 12:30:37| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 200.7762s]
-05/11/23 12:30:37| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:31:19| INFO ref finished [took 37.3749s]
-05/11/23 12:31:23| INFO atc_mc finished [took 40.9120s]
-05/11/23 12:33:54| INFO binmc_sld finished [took 194.5722s]
-05/11/23 12:33:55| INFO bin_sld finished [took 195.8961s]
-05/11/23 12:33:56| INFO binne_sld finished [took 194.9605s]
-05/11/23 12:33:56| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 198.1296s]
-05/11/23 12:33:56| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:34:37| INFO ref finished [took 37.5561s]
-05/11/23 12:34:40| INFO atc_mc finished [took 40.3775s]
-05/11/23 12:37:09| INFO bin_sld finished [took 192.3652s]
-05/11/23 12:37:12| INFO binne_sld finished [took 193.4666s]
-05/11/23 12:37:12| INFO binmc_sld finished [took 194.3499s]
-05/11/23 12:37:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 196.3675s]
-05/11/23 12:37:12| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:37:53| INFO ref finished [took 36.5043s]
-05/11/23 12:37:57| INFO atc_mc finished [took 40.0038s]
-05/11/23 12:40:26| INFO bin_sld finished [took 192.4518s]
-05/11/23 12:40:26| INFO binne_sld finished [took 191.2727s]
-05/11/23 12:40:26| INFO binmc_sld finished [took 192.3339s]
-05/11/23 12:40:26| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 194.5333s]
-05/11/23 12:40:27| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:41:07| INFO ref finished [took 36.6809s]
-05/11/23 12:41:11| INFO atc_mc finished [took 39.9520s]
-05/11/23 12:43:40| INFO bin_sld finished [took 192.1873s]
-05/11/23 12:43:40| INFO binmc_sld finished [took 191.7820s]
-05/11/23 12:43:41| INFO binne_sld finished [took 191.9164s]
-05/11/23 12:43:41| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 194.8818s]
-05/11/23 12:43:41| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:44:22| INFO ref finished [took 36.9564s]
-05/11/23 12:44:26| INFO atc_mc finished [took 40.1293s]
-05/11/23 12:46:55| INFO bin_sld finished [took 192.4960s]
-05/11/23 12:46:56| INFO binmc_sld finished [took 192.8281s]
-05/11/23 12:46:58| INFO binne_sld finished [took 193.1524s]
-05/11/23 12:46:58| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 196.2697s]
-05/11/23 12:46:58| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:47:39| INFO ref finished [took 37.2831s]
-05/11/23 12:47:42| INFO atc_mc finished [took 39.7258s]
-05/11/23 12:50:16| INFO binmc_sld finished [took 195.9783s]
-05/11/23 12:50:16| INFO binne_sld finished [took 195.2592s]
-05/11/23 12:50:16| INFO bin_sld finished [took 197.4676s]
-05/11/23 12:50:16| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 198.8232s]
-05/11/23 12:50:16| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-05/11/23 12:50:58| INFO ref finished [took 37.4054s]
-05/11/23 12:51:02| INFO atc_mc finished [took 40.4573s]
-05/11/23 12:53:36| INFO bin_sld finished [took 198.0953s]
-05/11/23 12:53:36| INFO binmc_sld finished [took 197.8028s]
-05/11/23 12:53:37| INFO binne_sld finished [took 197.3027s]
-05/11/23 12:53:37| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 200.2560s]
-----------------------------------------------------------------------------------------------------
-05/11/23 13:29:43| INFO dataset rcv1_CCAT_9prevs
-05/11/23 13:29:47| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-05/11/23 13:30:43| INFO ref finished [took 47.3558s]
-05/11/23 13:30:48| INFO atc_mc finished [took 50.8788s]
-05/11/23 13:30:52| INFO mulne_sld finished [took 60.4851s]
-05/11/23 13:30:53| INFO mulmc_sld finished [took 63.4717s]
-05/11/23 13:33:31| INFO binmc_sld finished [took 222.0328s]
-05/11/23 13:33:33| INFO binne_sld finished [took 223.0449s]
-05/11/23 13:43:18| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': 'max_conf'} (score=0.00644) [took 803.9708s]
-05/11/23 13:44:01| INFO mul_sld_gs finished [took 847.1261s]
-05/11/23 13:49:04| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00589) [took 1151.2473s]
-05/11/23 13:52:06| INFO bin_sld_gs finished [took 1333.4736s]
-05/11/23 13:52:06| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 1338.9046s]
-05/11/23 13:52:06| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-05/11/23 13:53:00| INFO ref finished [took 45.3095s]
-05/11/23 13:53:04| INFO atc_mc finished [took 48.2659s]
-05/11/23 13:53:08| INFO mulmc_sld finished [took 58.9237s]
-05/11/23 13:53:11| INFO mulne_sld finished [took 59.5712s]
-05/11/23 13:55:46| INFO binmc_sld finished [took 218.1315s]
-05/11/23 13:55:51| INFO binne_sld finished [took 220.8543s]
-05/11/23 14:05:34| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00699) [took 800.6256s]
-05/11/23 14:06:16| INFO mul_sld_gs finished [took 842.1616s]
-05/11/23 14:12:14| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00768) [took 1201.3712s]
-05/11/23 14:15:15| INFO bin_sld_gs finished [took 1382.8113s]
-05/11/23 14:15:15| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 1388.8622s]
-05/11/23 14:15:15| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-05/11/23 14:16:11| INFO ref finished [took 46.8666s]
-05/11/23 14:16:15| INFO atc_mc finished [took 49.6779s]
-05/11/23 14:16:19| INFO mulmc_sld finished [took 61.0610s]
-05/11/23 14:16:22| INFO mulne_sld finished [took 62.2089s]
-05/11/23 14:19:02| INFO binmc_sld finished [took 225.5737s]
-05/11/23 14:19:03| INFO binne_sld finished [took 223.9017s]
-05/11/23 14:28:50| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00756) [took 806.7930s]
-05/11/23 14:29:32| INFO mul_sld_gs finished [took 848.7630s]
-05/11/23 14:36:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00781) [took 1240.9138s]
-05/11/23 14:39:04| INFO bin_sld_gs finished [took 1422.5520s]
-05/11/23 14:39:04| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1428.8824s]
-05/11/23 14:39:04| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-05/11/23 14:39:58| INFO ref finished [took 45.7514s]
-05/11/23 14:40:02| INFO atc_mc finished [took 48.3888s]
-05/11/23 14:40:05| INFO mulmc_sld finished [took 59.0537s]
-05/11/23 14:40:09| INFO mulne_sld finished [took 60.9189s]
-05/11/23 14:42:42| INFO binne_sld finished [took 214.5464s]
-05/11/23 14:42:44| INFO binmc_sld finished [took 218.8429s]
-05/11/23 14:52:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00984) [took 792.5474s]
-05/11/23 14:53:05| INFO mul_sld_gs finished [took 834.1824s]
-05/11/23 14:59:56| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.01112) [took 1247.0092s]
-05/11/23 15:02:57| INFO bin_sld_gs finished [took 1427.5051s]
-05/11/23 15:02:57| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1432.9172s]
-05/11/23 15:02:57| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-05/11/23 15:03:49| INFO ref finished [took 44.4148s]
-05/11/23 15:03:54| INFO atc_mc finished [took 47.7566s]
-05/11/23 15:04:00| INFO mulmc_sld finished [took 60.5480s]
-05/11/23 15:04:03| INFO mulne_sld finished [took 61.2226s]
-05/11/23 15:06:30| INFO binmc_sld finished [took 211.9647s]
-05/11/23 15:06:32| INFO binne_sld finished [took 211.4312s]
-05/11/23 15:16:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'max_conf'} (score=0.00571) [took 776.6085s]
-05/11/23 15:16:42| INFO mul_sld_gs finished [took 817.9358s]
-05/11/23 15:23:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00653) [took 1221.6531s]
-05/11/23 15:26:23| INFO bin_sld_gs finished [took 1400.9688s]
-05/11/23 15:26:23| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 1406.4620s]
-05/11/23 15:26:23| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-05/11/23 15:27:16| INFO ref finished [took 44.3988s]
-05/11/23 15:27:21| INFO atc_mc finished [took 48.5589s]
-05/11/23 15:27:27| INFO mulmc_sld finished [took 61.4269s]
-05/11/23 15:27:29| INFO mulne_sld finished [took 61.8292s]
-05/11/23 15:29:55| INFO binmc_sld finished [took 210.1585s]
-05/11/23 15:29:59| INFO binne_sld finished [took 212.0930s]
-05/11/23 15:39:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'max_conf'} (score=0.00616) [took 771.6071s]
-05/11/23 15:40:03| INFO mul_sld_gs finished [took 813.2905s]
-05/11/23 15:47:04| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.00544) [took 1234.9832s]
-05/11/23 15:50:10| INFO bin_sld_gs finished [took 1421.7775s]
-05/11/23 15:50:10| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1427.0062s]
-05/11/23 15:50:10| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-05/11/23 15:51:11| INFO ref finished [took 49.7682s]
-05/11/23 15:51:19| INFO atc_mc finished [took 54.2855s]
-05/11/23 15:51:22| INFO mulmc_sld finished [took 68.7688s]
-05/11/23 15:51:26| INFO mulne_sld finished [took 69.3711s]
-05/11/23 15:54:07| INFO binmc_sld finished [took 234.7962s]
-05/11/23 15:54:09| INFO binne_sld finished [took 234.6444s]
-05/11/23 16:03:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': 'entropy'} (score=0.00765) [took 811.6704s]
-05/11/23 16:04:34| INFO mul_sld_gs finished [took 854.8196s]
-05/11/23 16:11:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'max_conf'} (score=0.01234) [took 1252.4784s]
-05/11/23 16:14:10| INFO bin_sld_gs finished [took 1431.7446s]
-05/11/23 16:14:10| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 1439.1145s]
-05/11/23 16:14:10| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-05/11/23 16:15:02| INFO ref finished [took 44.0970s]
-05/11/23 16:15:07| INFO atc_mc finished [took 48.2871s]
-05/11/23 16:15:13| INFO mulmc_sld finished [took 61.0461s]
-05/11/23 16:15:15| INFO mulne_sld finished [took 60.6375s]
-05/11/23 16:17:46| INFO binmc_sld finished [took 215.1734s]
-05/11/23 16:17:49| INFO binne_sld finished [took 215.7846s]
-05/11/23 16:27:15| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00822) [took 778.5688s]
-05/11/23 16:27:56| INFO mul_sld_gs finished [took 819.2615s]
-05/11/23 16:34:16| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'entropy'} (score=0.00894) [took 1200.6639s]
-05/11/23 16:37:21| INFO bin_sld_gs finished [took 1385.9035s]
-05/11/23 16:37:21| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 1391.5055s]
-05/11/23 16:37:21| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-05/11/23 16:38:13| INFO ref finished [took 44.7046s]
-05/11/23 16:38:18| INFO atc_mc finished [took 48.7802s]
-05/11/23 16:38:21| INFO mulmc_sld finished [took 57.4163s]
-05/11/23 16:38:24| INFO mulne_sld finished [took 58.9847s]
-05/11/23 16:40:59| INFO binmc_sld finished [took 216.7311s]
-05/11/23 16:41:01| INFO binne_sld finished [took 216.5312s]
-05/11/23 16:50:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00808) [took 758.6896s]
-05/11/23 16:50:46| INFO mul_sld_gs finished [took 798.8038s]
-05/11/23 16:56:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'entropy'} (score=0.00604) [took 1154.7043s]
-05/11/23 16:59:39| INFO bin_sld_gs finished [took 1332.5521s]
-05/11/23 16:59:39| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 1337.7947s]
-----------------------------------------------------------------------------------------------------
-05/11/23 20:08:46| ERROR estimate comparison failed. Exceprion: 'environ' object has no attribute 'OUT_PATH'
-----------------------------------------------------------------------------------------------------
-05/11/23 20:09:08| ERROR estimate comparison failed. Exceprion: 'environ' object has no attribute 'OUT_PATH'
-----------------------------------------------------------------------------------------------------
-05/11/23 20:09:27| INFO dataset imdb_3prevs
-05/11/23 20:09:34| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 20:09:44| INFO ref finished [took 8.9550s]
-05/11/23 20:09:47| INFO atc_mc finished [took 11.8923s]
-05/11/23 20:09:56| INFO mulmc_sld finished [took 21.3196s]
-05/11/23 20:09:56| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 21.7709s]
-05/11/23 20:09:56| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 20:10:05| INFO ref finished [took 8.6116s]
-05/11/23 20:10:08| INFO atc_mc finished [took 11.6880s]
-05/11/23 20:10:16| INFO mulmc_sld finished [took 19.7793s]
-05/11/23 20:10:16| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.3246s]
-05/11/23 20:10:16| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 20:10:26| INFO ref finished [took 8.6654s]
-05/11/23 20:10:29| INFO atc_mc finished [took 11.6975s]
-05/11/23 20:10:35| INFO mulmc_sld finished [took 18.1478s]
-05/11/23 20:10:35| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.7200s]
-----------------------------------------------------------------------------------------------------
-05/11/23 20:11:42| INFO dataset imdb_3prevs
-05/11/23 20:11:49| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 20:11:58| INFO ref finished [took 8.7146s]
-05/11/23 20:12:02| INFO atc_mc finished [took 11.9672s]
-05/11/23 20:12:10| INFO mulmc_sld finished [took 20.7824s]
-05/11/23 20:12:10| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 21.2293s]
-05/11/23 20:12:10| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 20:12:19| INFO ref finished [took 8.5867s]
-05/11/23 20:12:23| INFO atc_mc finished [took 11.6542s]
-05/11/23 20:12:30| INFO mulmc_sld finished [took 19.6709s]
-05/11/23 20:12:30| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.1802s]
-05/11/23 20:12:30| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 20:12:40| INFO ref finished [took 8.7231s]
-05/11/23 20:12:43| INFO atc_mc finished [took 11.8244s]
-05/11/23 20:12:49| INFO mulmc_sld finished [took 18.0420s]
-05/11/23 20:12:49| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.6102s]
-----------------------------------------------------------------------------------------------------
-05/11/23 20:14:32| INFO dataset imdb_3prevs
-05/11/23 20:14:39| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 20:14:48| INFO ref finished [took 8.6247s]
-05/11/23 20:14:51| INFO atc_mc finished [took 11.6363s]
-05/11/23 20:15:00| INFO mulmc_sld finished [took 20.4634s]
-05/11/23 20:15:00| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 20.9026s]
-05/11/23 20:15:00| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 20:15:09| INFO ref finished [took 8.5219s]
-05/11/23 20:15:12| INFO atc_mc finished [took 11.6739s]
-05/11/23 20:15:20| INFO mulmc_sld finished [took 19.8454s]
-05/11/23 20:15:20| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.3705s]
-05/11/23 20:15:20| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 20:15:29| INFO ref finished [took 8.5948s]
-05/11/23 20:15:32| INFO atc_mc finished [took 11.7465s]
-05/11/23 20:15:39| INFO mulmc_sld finished [took 17.9276s]
-05/11/23 20:15:39| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.4893s]
-----------------------------------------------------------------------------------------------------
-05/11/23 20:16:10| INFO dataset imdb_3prevs
-05/11/23 20:16:17| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-05/11/23 20:16:26| INFO ref finished [took 8.3736s]
-05/11/23 20:16:29| INFO atc_mc finished [took 11.3995s]
-05/11/23 20:16:38| INFO mulmc_sld finished [took 20.4916s]
-05/11/23 20:16:38| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 20.9187s]
-05/11/23 20:16:38| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-05/11/23 20:16:47| INFO ref finished [took 8.4368s]
-05/11/23 20:16:50| INFO atc_mc finished [took 11.4889s]
-05/11/23 20:16:58| INFO mulmc_sld finished [took 19.6803s]
-05/11/23 20:16:58| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.2091s]
-05/11/23 20:16:58| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-05/11/23 20:17:08| INFO ref finished [took 8.9281s]
-05/11/23 20:17:11| INFO atc_mc finished [took 11.9333s]
-05/11/23 20:17:17| INFO mulmc_sld finished [took 18.2367s]
-05/11/23 20:17:17| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.8309s]
-----------------------------------------------------------------------------------------------------
-06/11/23 01:34:48| INFO dataset imdb_3prevs
-06/11/23 01:34:59| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-06/11/23 01:35:18| INFO ref finished [took 18.0987s]
-06/11/23 01:35:24| INFO atc_mc finished [took 24.9118s]
-06/11/23 01:35:31| INFO mulmc_sld finished [took 32.0631s]
-06/11/23 01:35:31| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 32.6119s]
-06/11/23 01:35:31| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-06/11/23 01:35:51| INFO ref finished [took 18.7770s]
-06/11/23 01:35:58| INFO atc_mc finished [took 25.5592s]
-06/11/23 01:36:04| INFO mulmc_sld finished [took 31.9103s]
-06/11/23 01:36:04| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 32.5205s]
-06/11/23 01:36:04| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-06/11/23 01:36:23| INFO ref finished [took 18.5730s]
-06/11/23 01:36:31| INFO atc_mc finished [took 25.8019s]
-06/11/23 01:36:33| INFO mulmc_sld finished [took 28.9526s]
-06/11/23 01:36:33| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 29.5292s]
-----------------------------------------------------------------------------------------------------
-06/11/23 02:06:40| INFO dataset imdb_3prevs
-06/11/23 02:06:47| INFO Dataset sample 0.20 of dataset imdb_3prevs started
-06/11/23 02:06:56| INFO ref finished [took 9.0989s]
-06/11/23 02:06:59| INFO atc_mc finished [took 12.2513s]
-06/11/23 03:01:43| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'quantifier__exact_train_prev': False, 'confidence': 'max_conf'} (score=0.00738) [took 3296.0714s]
-06/11/23 03:01:56| INFO mul_sld_gs finished [took 3309.2417s]
-06/11/23 03:01:56| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 3309.7038s]
-06/11/23 03:01:56| INFO Dataset sample 0.50 of dataset imdb_3prevs started
-06/11/23 03:02:06| INFO ref finished [took 8.5518s]
-06/11/23 03:02:09| INFO atc_mc finished [took 11.4390s]
-06/11/23 03:54:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00899) [took 3146.2364s]
-06/11/23 03:54:37| INFO mul_sld_gs finished [took 3159.8209s]
-06/11/23 03:54:37| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 3160.3546s]
-06/11/23 03:54:37| INFO Dataset sample 0.80 of dataset imdb_3prevs started
-06/11/23 03:54:46| INFO ref finished [took 8.2678s]
-06/11/23 03:54:48| INFO atc_mc finished [took 11.0430s]
-06/11/23 04:47:50| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': False, 'confidence': 'entropy'} (score=0.00770) [took 3193.1812s]
-06/11/23 04:48:04| INFO mul_sld_gs finished [took 3206.9550s]
-06/11/23 04:48:04| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 3207.5040s]
-----------------------------------------------------------------------------------------------------
-06/11/23 05:14:48| INFO dataset rcv1_CCAT_9prevs
-06/11/23 05:14:53| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:15:55| INFO ref finished [took 48.0242s]
-06/11/23 05:16:01| INFO atc_mc finished [took 51.7851s]
-06/11/23 05:16:04| INFO mul_pacc finished [took 58.4704s]
-06/11/23 05:16:04| INFO mulne_sld finished [took 62.7354s]
-06/11/23 05:16:04| INFO mulmc_sld finished [took 66.2593s]
-06/11/23 05:16:14| INFO mul_sld finished [took 78.2483s]
-06/11/23 05:18:40| INFO bin_pacc finished [took 217.0012s]
-06/11/23 05:18:43| INFO bin_sld finished [took 227.8835s]
-06/11/23 05:18:43| INFO binne_sld finished [took 223.2764s]
-06/11/23 05:18:44| INFO binmc_sld finished [took 226.7324s]
-06/11/23 05:18:44| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 230.5906s]
-06/11/23 05:18:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:19:44| INFO ref finished [took 49.5147s]
-06/11/23 05:19:51| INFO atc_mc finished [took 54.8022s]
-06/11/23 05:19:53| INFO mul_pacc finished [took 60.3260s]
-06/11/23 05:19:55| INFO mulmc_sld finished [took 67.0280s]
-06/11/23 05:19:56| INFO mul_sld finished [took 70.4092s]
-06/11/23 05:19:58| INFO mulne_sld finished [took 67.3468s]
-06/11/23 05:22:30| INFO bin_sld finished [took 224.7344s]
-06/11/23 05:22:30| INFO bin_pacc finished [took 218.3044s]
-06/11/23 05:22:30| INFO binmc_sld finished [took 223.3607s]
-06/11/23 05:22:33| INFO binne_sld finished [took 223.6042s]
-06/11/23 05:22:33| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 229.0745s]
-06/11/23 05:22:33| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:23:32| INFO ref finished [took 48.1565s]
-06/11/23 05:23:37| INFO atc_mc finished [took 52.1124s]
-06/11/23 05:23:40| INFO mul_pacc finished [took 58.0112s]
-06/11/23 05:23:40| INFO mul_sld finished [took 65.2727s]
-06/11/23 05:23:42| INFO mulmc_sld finished [took 64.5943s]
-06/11/23 05:23:43| INFO mulne_sld finished [took 63.9053s]
-06/11/23 05:26:13| INFO bin_sld finished [took 218.6511s]
-06/11/23 05:26:16| INFO bin_pacc finished [took 215.1485s]
-06/11/23 05:26:17| INFO binne_sld finished [took 218.6855s]
-06/11/23 05:26:17| INFO binmc_sld finished [took 221.2605s]
-06/11/23 05:26:17| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 224.5608s]
-06/11/23 05:26:17| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:27:15| INFO ref finished [took 48.2181s]
-06/11/23 05:27:21| INFO atc_mc finished [took 52.3420s]
-06/11/23 05:27:23| INFO mul_pacc finished [took 57.1950s]
-06/11/23 05:27:24| INFO mul_sld finished [took 64.4722s]
-06/11/23 05:27:26| INFO mulmc_sld finished [took 64.1870s]
-06/11/23 05:27:27| INFO mulne_sld finished [took 63.7407s]
-06/11/23 05:29:52| INFO bin_sld finished [took 213.1913s]
-06/11/23 05:29:53| INFO bin_pacc finished [took 208.1322s]
-06/11/23 05:29:53| INFO binmc_sld finished [took 212.6473s]
-06/11/23 05:29:57| INFO binne_sld finished [took 214.5243s]
-06/11/23 05:29:57| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 219.5765s]
-06/11/23 05:29:57| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:30:55| INFO ref finished [took 47.7289s]
-06/11/23 05:31:01| INFO atc_mc finished [took 52.1531s]
-06/11/23 05:31:03| INFO mul_pacc finished [took 57.3804s]
-06/11/23 05:31:06| INFO mul_sld finished [took 66.9237s]
-06/11/23 05:31:06| INFO mulmc_sld finished [took 65.3230s]
-06/11/23 05:31:09| INFO mulne_sld finished [took 65.6645s]
-06/11/23 05:33:33| INFO bin_sld finished [took 214.3242s]
-06/11/23 05:33:34| INFO bin_pacc finished [took 209.3862s]
-06/11/23 05:33:35| INFO binmc_sld finished [took 214.4687s]
-06/11/23 05:33:37| INFO binne_sld finished [took 214.7267s]
-06/11/23 05:33:37| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 220.0212s]
-06/11/23 05:33:37| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:34:35| INFO ref finished [took 48.0021s]
-06/11/23 05:34:41| INFO atc_mc finished [took 52.2171s]
-06/11/23 05:34:43| INFO mul_pacc finished [took 57.2348s]
-06/11/23 05:34:46| INFO mul_sld finished [took 67.0899s]
-06/11/23 05:34:47| INFO mulmc_sld finished [took 66.1078s]
-06/11/23 05:34:49| INFO mulne_sld finished [took 66.0237s]
-06/11/23 05:37:13| INFO bin_sld finished [took 214.9942s]
-06/11/23 05:37:13| INFO binmc_sld finished [took 213.1574s]
-06/11/23 05:37:14| INFO bin_pacc finished [took 209.1347s]
-06/11/23 05:37:17| INFO binne_sld finished [took 214.9703s]
-06/11/23 05:37:17| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 220.1235s]
-06/11/23 05:37:17| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:38:15| INFO ref finished [took 47.8227s]
-06/11/23 05:38:20| INFO atc_mc finished [took 51.9364s]
-06/11/23 05:38:23| INFO mul_pacc finished [took 56.9053s]
-06/11/23 05:38:27| INFO mul_sld finished [took 67.4535s]
-06/11/23 05:38:27| INFO mulmc_sld finished [took 65.5956s]
-06/11/23 05:38:30| INFO mulne_sld finished [took 66.0476s]
-06/11/23 05:40:55| INFO bin_pacc finished [took 210.0633s]
-06/11/23 05:40:56| INFO binmc_sld finished [took 215.3452s]
-06/11/23 05:40:56| INFO bin_sld finished [took 217.8091s]
-06/11/23 05:40:59| INFO binne_sld finished [took 216.8970s]
-06/11/23 05:40:59| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 222.2971s]
-06/11/23 05:40:59| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:41:57| INFO ref finished [took 47.6970s]
-06/11/23 05:42:03| INFO atc_mc finished [took 52.0893s]
-06/11/23 05:42:05| INFO mul_pacc finished [took 56.6428s]
-06/11/23 05:42:09| INFO mul_sld finished [took 66.8810s]
-06/11/23 05:42:09| INFO mulmc_sld finished [took 65.8427s]
-06/11/23 05:42:11| INFO mulne_sld finished [took 64.8594s]
-06/11/23 05:44:36| INFO bin_pacc finished [took 208.7884s]
-06/11/23 05:44:38| INFO bin_sld finished [took 216.6052s]
-06/11/23 05:44:38| INFO binmc_sld finished [took 215.5486s]
-06/11/23 05:44:43| INFO binne_sld finished [took 217.9926s]
-06/11/23 05:44:43| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 223.2270s]
-06/11/23 05:44:43| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-06/11/23 05:45:40| INFO ref finished [took 48.0710s]
-06/11/23 05:45:46| INFO atc_mc finished [took 52.0992s]
-06/11/23 05:45:48| INFO mul_pacc finished [took 56.6568s]
-06/11/23 05:45:49| INFO mulmc_sld finished [took 61.7314s]
-06/11/23 05:45:52| INFO mulne_sld finished [took 62.7505s]
-06/11/23 05:45:59| INFO mul_sld finished [took 73.7681s]
-06/11/23 05:48:18| INFO bin_pacc finished [took 208.2267s]
-06/11/23 05:48:23| INFO bin_sld finished [took 218.9333s]
-06/11/23 05:48:24| INFO binmc_sld finished [took 218.0032s]
-06/11/23 05:48:27| INFO binne_sld finished [took 219.2450s]
-06/11/23 05:48:27| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 224.3446s]
-06/11/23 05:49:49| INFO dataset imdb_9prevs
-06/11/23 05:49:57| INFO Dataset sample 0.10 of dataset imdb_9prevs started
-06/11/23 05:50:12| INFO ref finished [took 13.3064s]
-06/11/23 05:50:17| INFO atc_mc finished [took 17.3508s]
-06/11/23 05:50:19| INFO mul_pacc finished [took 20.0802s]
-06/11/23 05:50:22| INFO mulne_sld finished [took 23.6723s]
-06/11/23 05:50:24| INFO mulmc_sld finished [took 25.5159s]
-06/11/23 05:50:39| INFO mul_sld finished [took 40.7099s]
-06/11/23 05:52:55| INFO bin_pacc finished [took 176.3728s]
-06/11/23 05:53:05| INFO binmc_sld finished [took 186.8240s]
-06/11/23 05:53:06| INFO binne_sld finished [took 187.6585s]
-06/11/23 05:53:07| INFO bin_sld finished [took 189.1728s]
-06/11/23 05:53:07| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 189.6034s]
-06/11/23 05:53:07| INFO Dataset sample 0.20 of dataset imdb_9prevs started
-06/11/23 05:53:22| INFO ref finished [took 13.2778s]
-06/11/23 05:53:26| INFO atc_mc finished [took 17.4491s]
-06/11/23 05:53:28| INFO mul_pacc finished [took 19.9359s]
-06/11/23 05:53:40| INFO mulmc_sld finished [took 31.6686s]
-06/11/23 05:53:44| INFO mulne_sld finished [took 35.2085s]
-06/11/23 05:53:44| INFO mul_sld finished [took 36.2502s]
-06/11/23 05:56:05| INFO bin_pacc finished [took 177.0225s]
-06/11/23 05:56:13| INFO binmc_sld finished [took 185.4811s]
-06/11/23 05:56:15| INFO bin_sld finished [took 187.1039s]
-06/11/23 05:56:16| INFO binne_sld finished [took 187.3163s]
-06/11/23 05:56:16| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 188.4781s]
-06/11/23 05:56:16| INFO Dataset sample 0.30 of dataset imdb_9prevs started
-06/11/23 05:56:31| INFO ref finished [took 13.4513s]
-06/11/23 05:56:36| INFO atc_mc finished [took 18.1025s]
-06/11/23 05:56:38| INFO mul_pacc finished [took 20.3997s]
-06/11/23 05:56:45| INFO mulmc_sld finished [took 28.4298s]
-06/11/23 05:56:46| INFO mulne_sld finished [took 28.8678s]
-06/11/23 05:56:46| INFO mul_sld finished [took 29.5573s]
-06/11/23 05:59:11| INFO bin_pacc finished [took 174.0262s]
-06/11/23 05:59:17| INFO binmc_sld finished [took 180.1998s]
-06/11/23 05:59:18| INFO binne_sld finished [took 181.2200s]
-06/11/23 05:59:19| INFO bin_sld finished [took 182.1672s]
-06/11/23 05:59:19| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 183.0515s]
-06/11/23 05:59:19| INFO Dataset sample 0.40 of dataset imdb_9prevs started
-06/11/23 05:59:34| INFO ref finished [took 13.5163s]
-06/11/23 05:59:39| INFO atc_mc finished [took 17.9856s]
-06/11/23 05:59:41| INFO mul_pacc finished [took 20.7441s]
-06/11/23 05:59:49| INFO mulmc_sld finished [took 29.2747s]
-06/11/23 05:59:50| INFO mulne_sld finished [took 29.6624s]
-06/11/23 05:59:50| INFO mul_sld finished [took 30.3432s]
-06/11/23 06:02:17| INFO bin_pacc finished [took 176.7354s]
-06/11/23 06:02:19| INFO binmc_sld finished [took 179.9981s]
-06/11/23 06:02:21| INFO bin_sld finished [took 181.6844s]
-06/11/23 06:02:22| INFO binne_sld finished [took 182.0846s]
-06/11/23 06:02:22| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 183.2033s]
-06/11/23 06:02:22| INFO Dataset sample 0.50 of dataset imdb_9prevs started
-06/11/23 06:02:37| INFO ref finished [took 13.4688s]
-06/11/23 06:02:42| INFO atc_mc finished [took 18.0218s]
-06/11/23 06:02:44| INFO mul_pacc finished [took 20.5800s]
-06/11/23 06:02:52| INFO mulmc_sld finished [took 29.0192s]
-06/11/23 06:02:52| INFO mul_sld finished [took 29.4403s]
-06/11/23 06:02:52| INFO mulne_sld finished [took 29.1611s]
-06/11/23 06:05:19| INFO bin_pacc finished [took 175.5125s]
-06/11/23 06:05:23| INFO binmc_sld finished [took 180.0427s]
-06/11/23 06:05:25| INFO binne_sld finished [took 182.5814s]
-06/11/23 06:05:26| INFO bin_sld finished [took 183.2892s]
-06/11/23 06:05:26| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 183.8611s]
-06/11/23 06:05:26| INFO Dataset sample 0.60 of dataset imdb_9prevs started
-06/11/23 06:05:41| INFO ref finished [took 13.4643s]
-06/11/23 06:05:45| INFO atc_mc finished [took 17.9768s]
-06/11/23 06:05:48| INFO mul_pacc finished [took 20.7525s]
-06/11/23 06:05:55| INFO mulmc_sld finished [took 28.8234s]
-06/11/23 06:05:55| INFO mulne_sld finished [took 28.6537s]
-06/11/23 06:05:56| INFO mul_sld finished [took 29.6167s]
-06/11/23 06:08:24| INFO bin_pacc finished [took 176.5335s]
-06/11/23 06:08:27| INFO binmc_sld finished [took 180.4803s]
-06/11/23 06:08:28| INFO bin_sld finished [took 181.6676s]
-06/11/23 06:08:29| INFO binne_sld finished [took 182.0534s]
-06/11/23 06:08:29| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 183.0240s]
-06/11/23 06:08:29| INFO Dataset sample 0.70 of dataset imdb_9prevs started
-06/11/23 06:08:44| INFO ref finished [took 13.7566s]
-06/11/23 06:08:49| INFO atc_mc finished [took 17.9495s]
-06/11/23 06:08:51| INFO mul_pacc finished [took 20.5859s]
-06/11/23 06:08:57| INFO mulmc_sld finished [took 27.4370s]
-06/11/23 06:08:58| INFO mul_sld finished [took 28.3224s]
-06/11/23 06:08:58| INFO mulne_sld finished [took 28.1390s]
-06/11/23 06:11:26| INFO bin_pacc finished [took 175.7412s]
-06/11/23 06:11:31| INFO binmc_sld finished [took 181.4310s]
-06/11/23 06:11:32| INFO binne_sld finished [took 182.0095s]
-06/11/23 06:11:33| INFO bin_sld finished [took 183.6520s]
-06/11/23 06:11:33| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 184.2005s]
-06/11/23 06:11:33| INFO Dataset sample 0.80 of dataset imdb_9prevs started
-06/11/23 06:11:48| INFO ref finished [took 13.5418s]
-06/11/23 06:11:53| INFO atc_mc finished [took 17.8150s]
-06/11/23 06:11:55| INFO mul_pacc finished [took 20.4761s]
-06/11/23 06:12:01| INFO mulmc_sld finished [took 27.2741s]
-06/11/23 06:12:02| INFO mulne_sld finished [took 27.2693s]
-06/11/23 06:12:02| INFO mul_sld finished [took 28.3364s]
-06/11/23 06:14:30| INFO bin_pacc finished [took 175.7637s]
-06/11/23 06:14:37| INFO binmc_sld finished [took 183.2422s]
-06/11/23 06:14:38| INFO bin_sld finished [took 184.1064s]
-06/11/23 06:14:39| INFO binne_sld finished [took 184.9073s]
-06/11/23 06:14:39| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 186.2580s]
-06/11/23 06:14:39| INFO Dataset sample 0.90 of dataset imdb_9prevs started
-06/11/23 06:14:41| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 06:14:41| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 06:14:52| INFO ref finished [took 11.6315s]
-06/11/23 06:14:56| INFO atc_mc finished [took 15.3068s]
-06/11/23 06:15:01| INFO mulne_sld finished [took 21.1133s]
-06/11/23 06:15:02| INFO mulmc_sld finished [took 22.2375s]
-06/11/23 06:15:08| INFO mul_sld finished [took 27.8149s]
-06/11/23 06:17:32| INFO binne_sld finished [took 171.8722s]
-06/11/23 06:17:32| INFO bin_sld finished [took 172.4710s]
-06/11/23 06:17:33| INFO binmc_sld finished [took 172.8193s]
-06/11/23 06:17:33| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 173.4411s]
-06/11/23 06:18:54| INFO dataset rcv1_GCAT_9prevs
-06/11/23 06:18:59| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:19:11| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 06:19:11| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 06:19:54| INFO ref finished [took 42.0769s]
-06/11/23 06:19:59| INFO atc_mc finished [took 45.5011s]
-06/11/23 06:20:14| INFO mulne_sld finished [took 66.0516s]
-06/11/23 06:20:15| INFO mul_sld finished [took 73.1171s]
-06/11/23 06:20:17| INFO mulmc_sld finished [took 72.1930s]
-06/11/23 06:22:23| INFO bin_sld finished [took 203.0368s]
-06/11/23 06:22:27| INFO binmc_sld finished [took 203.2975s]
-06/11/23 06:22:29| INFO binne_sld finished [took 202.7501s]
-06/11/23 06:22:29| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 210.2201s]
-06/11/23 06:22:29| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:23:26| INFO ref finished [took 46.6022s]
-06/11/23 06:23:31| INFO atc_mc finished [took 50.3293s]
-06/11/23 06:23:33| INFO mul_pacc finished [took 54.9265s]
-06/11/23 06:23:46| INFO mul_sld finished [took 74.9035s]
-06/11/23 06:23:52| INFO mulne_sld finished [took 76.2697s]
-06/11/23 06:23:54| INFO mulmc_sld finished [took 80.8754s]
-06/11/23 06:26:06| INFO bin_pacc finished [took 209.7751s]
-06/11/23 06:26:08| INFO bin_sld finished [took 217.8889s]
-06/11/23 06:26:13| INFO binmc_sld finished [took 220.7753s]
-06/11/23 06:26:14| INFO binne_sld finished [took 219.7510s]
-06/11/23 06:26:14| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 224.9268s]
-06/11/23 06:26:14| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:27:10| INFO ref finished [took 46.4938s]
-06/11/23 06:27:16| INFO atc_mc finished [took 50.5904s]
-06/11/23 06:27:18| INFO mul_pacc finished [took 55.4949s]
-06/11/23 06:27:26| INFO mulmc_sld finished [took 67.7140s]
-06/11/23 06:27:26| INFO mul_sld finished [took 70.0891s]
-06/11/23 06:27:28| INFO mulne_sld finished [took 68.1806s]
-06/11/23 06:29:50| INFO bin_pacc finished [took 208.6091s]
-06/11/23 06:29:51| INFO binmc_sld finished [took 213.7985s]
-06/11/23 06:29:51| INFO bin_sld finished [took 215.8158s]
-06/11/23 06:29:55| INFO binne_sld finished [took 215.5523s]
-06/11/23 06:29:55| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 220.4589s]
-06/11/23 06:29:55| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:30:51| INFO ref finished [took 46.3752s]
-06/11/23 06:30:56| INFO atc_mc finished [took 50.7062s]
-06/11/23 06:30:58| INFO mul_pacc finished [took 55.2260s]
-06/11/23 06:31:01| INFO mul_sld finished [took 64.2359s]
-06/11/23 06:31:02| INFO mulmc_sld finished [took 63.5099s]
-06/11/23 06:31:04| INFO mulne_sld finished [took 62.9188s]
-06/11/23 06:33:29| INFO bin_sld finished [took 213.2716s]
-06/11/23 06:33:30| INFO bin_pacc finished [took 208.6574s]
-06/11/23 06:33:31| INFO binmc_sld finished [took 213.1856s]
-06/11/23 06:33:33| INFO binne_sld finished [took 213.2771s]
-06/11/23 06:33:33| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 218.1742s]
-06/11/23 06:33:33| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:34:29| INFO ref finished [took 46.6793s]
-06/11/23 06:34:34| INFO atc_mc finished [took 50.9915s]
-06/11/23 06:34:37| INFO mul_pacc finished [took 55.9725s]
-06/11/23 06:34:38| INFO mul_sld finished [took 63.1317s]
-06/11/23 06:34:40| INFO mulmc_sld finished [took 62.7473s]
-06/11/23 06:34:41| INFO mulne_sld finished [took 62.1303s]
-06/11/23 06:37:08| INFO bin_pacc finished [took 207.7854s]
-06/11/23 06:37:08| INFO bin_sld finished [took 213.7945s]
-06/11/23 06:37:08| INFO binmc_sld finished [took 212.6207s]
-06/11/23 06:37:12| INFO binne_sld finished [took 213.8742s]
-06/11/23 06:37:12| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 218.7265s]
-06/11/23 06:37:12| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:38:08| INFO ref finished [took 46.6057s]
-06/11/23 06:38:14| INFO atc_mc finished [took 51.1055s]
-06/11/23 06:38:15| INFO mul_pacc finished [took 55.5338s]
-06/11/23 06:38:17| INFO mul_sld finished [took 63.2113s]
-06/11/23 06:38:18| INFO mulmc_sld finished [took 62.2265s]
-06/11/23 06:38:20| INFO mulne_sld finished [took 61.9918s]
-06/11/23 06:40:46| INFO bin_pacc finished [took 207.5094s]
-06/11/23 06:40:46| INFO bin_sld finished [took 213.6350s]
-06/11/23 06:40:47| INFO binmc_sld finished [took 212.8363s]
-06/11/23 06:40:49| INFO binne_sld finished [took 212.2587s]
-06/11/23 06:40:49| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 217.1976s]
-06/11/23 06:40:49| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:41:44| INFO ref finished [took 45.9582s]
-06/11/23 06:41:50| INFO atc_mc finished [took 50.0401s]
-06/11/23 06:41:54| INFO mul_sld finished [took 62.6045s]
-06/11/23 06:41:54| INFO mulmc_sld finished [took 61.4168s]
-06/11/23 06:41:56| INFO mulne_sld finished [took 61.3708s]
-06/11/23 06:42:00| INFO mul_pacc finished [took 62.6486s]
-06/11/23 06:44:23| INFO bin_sld finished [took 212.5992s]
-06/11/23 06:44:23| INFO bin_pacc finished [took 207.5241s]
-06/11/23 06:44:24| INFO binmc_sld finished [took 212.2794s]
-06/11/23 06:44:27| INFO binne_sld finished [took 212.8325s]
-06/11/23 06:44:27| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 217.7909s]
-06/11/23 06:44:27| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:45:23| INFO ref finished [took 46.6997s]
-06/11/23 06:45:28| INFO atc_mc finished [took 50.6417s]
-06/11/23 06:45:30| INFO mul_sld finished [took 61.5352s]
-06/11/23 06:45:31| INFO mul_pacc finished [took 55.9055s]
-06/11/23 06:45:31| INFO mulmc_sld finished [took 60.6608s]
-06/11/23 06:45:33| INFO mulne_sld finished [took 60.1616s]
-06/11/23 06:48:01| INFO bin_pacc finished [took 207.7543s]
-06/11/23 06:48:02| INFO bin_sld finished [took 213.7056s]
-06/11/23 06:48:03| INFO binmc_sld finished [took 213.7901s]
-06/11/23 06:48:04| INFO binne_sld finished [took 212.4421s]
-06/11/23 06:48:04| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 217.4465s]
-06/11/23 06:48:04| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
-06/11/23 06:48:06| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 06:48:07| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 06:48:09| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 06:48:11| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 06:48:13| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 06:48:49| INFO ref finished [took 36.4085s]
-06/11/23 06:48:53| INFO atc_mc finished [took 39.1380s]
-06/11/23 06:48:54| INFO mulmc_sld finished [took 46.0254s]
-06/11/23 06:48:55| INFO mulne_sld finished [took 45.1935s]
-06/11/23 06:49:00| INFO mul_sld finished [took 53.9145s]
-06/11/23 06:49:00| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 55.9159s]
-06/11/23 06:50:22| INFO dataset rcv1_MCAT_9prevs
-06/11/23 06:50:27| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
-06/11/23 06:51:29| INFO ref finished [took 47.8430s]
-06/11/23 06:51:34| INFO atc_mc finished [took 51.2418s]
-06/11/23 06:51:36| INFO mul_pacc finished [took 56.8770s]
-06/11/23 06:52:00| INFO mulne_sld finished [took 85.8579s]
-06/11/23 06:52:00| INFO mul_sld finished [took 90.6401s]
-06/11/23 06:52:12| INFO mulmc_sld finished [took 100.3728s]
-06/11/23 06:54:15| INFO bin_pacc finished [took 217.8843s]
-06/11/23 06:54:15| INFO bin_sld finished [took 226.6925s]
-06/11/23 06:54:17| INFO binne_sld finished [took 224.5785s]
-06/11/23 06:54:17| INFO binmc_sld finished [took 226.9490s]
-06/11/23 06:54:17| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 229.9256s]
-06/11/23 06:54:17| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
-06/11/23 06:55:14| INFO ref finished [took 46.7323s]
-06/11/23 06:55:20| INFO atc_mc finished [took 51.0126s]
-06/11/23 06:55:22| INFO mul_pacc finished [took 55.8357s]
-06/11/23 06:55:23| INFO mulmc_sld finished [took 62.0464s]
-06/11/23 06:55:24| INFO mul_sld finished [took 64.8106s]
-06/11/23 06:55:25| INFO mulne_sld finished [took 61.6750s]
-06/11/23 06:57:56| INFO bin_pacc finished [took 210.8901s]
-06/11/23 06:57:56| INFO bin_sld finished [took 217.3461s]
-06/11/23 06:57:57| INFO binmc_sld finished [took 216.6599s]
-06/11/23 06:58:00| INFO binne_sld finished [took 216.9668s]
-06/11/23 06:58:00| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 222.3450s]
-06/11/23 06:58:00| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
-06/11/23 06:58:57| INFO ref finished [took 47.5989s]
-06/11/23 06:59:02| INFO atc_mc finished [took 51.5080s]
-06/11/23 06:59:04| INFO mul_pacc finished [took 56.1671s]
-06/11/23 06:59:09| INFO mulmc_sld finished [took 65.0229s]
-06/11/23 06:59:10| INFO mul_sld finished [took 68.8366s]
-06/11/23 06:59:11| INFO mulne_sld finished [took 65.2964s]
-06/11/23 07:01:39| INFO bin_pacc finished [took 212.3570s]
-06/11/23 07:01:40| INFO bin_sld finished [took 219.3886s]
-06/11/23 07:01:42| INFO binmc_sld finished [took 219.1471s]
-06/11/23 07:01:43| INFO binne_sld finished [took 218.3714s]
-06/11/23 07:01:43| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 223.2305s]
-06/11/23 07:01:43| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
-06/11/23 07:02:40| INFO ref finished [took 47.3513s]
-06/11/23 07:02:45| INFO atc_mc finished [took 51.3858s]
-06/11/23 07:02:47| INFO mul_pacc finished [took 56.3829s]
-06/11/23 07:02:50| INFO mul_sld finished [took 64.9257s]
-06/11/23 07:02:50| INFO mulmc_sld finished [took 63.6515s]
-06/11/23 07:02:52| INFO mulne_sld finished [took 63.8008s]
-06/11/23 07:05:22| INFO bin_pacc finished [took 211.8418s]
-06/11/23 07:05:22| INFO binmc_sld finished [took 216.4950s]
-06/11/23 07:05:22| INFO bin_sld finished [took 218.2730s]
-06/11/23 07:05:25| INFO binne_sld finished [took 217.6016s]
-06/11/23 07:05:25| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 222.4416s]
-06/11/23 07:05:25| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
-06/11/23 07:06:22| INFO ref finished [took 47.3783s]
-06/11/23 07:06:27| INFO atc_mc finished [took 51.1924s]
-06/11/23 07:06:30| INFO mul_pacc finished [took 56.3115s]
-06/11/23 07:06:34| INFO mul_sld finished [took 66.6559s]
-06/11/23 07:06:34| INFO mulmc_sld finished [took 65.2448s]
-06/11/23 07:06:37| INFO mulne_sld finished [took 65.6557s]
-06/11/23 07:09:03| INFO binmc_sld finished [took 214.4549s]
-06/11/23 07:09:03| INFO bin_sld finished [took 216.8097s]
-06/11/23 07:09:04| INFO bin_pacc finished [took 211.9484s]
-06/11/23 07:09:06| INFO binne_sld finished [took 215.5010s]
-06/11/23 07:09:06| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 220.4788s]
-06/11/23 07:09:06| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
-06/11/23 07:10:03| INFO ref finished [took 47.0882s]
-06/11/23 07:10:08| INFO atc_mc finished [took 51.1826s]
-06/11/23 07:10:10| INFO mul_pacc finished [took 55.8766s]
-06/11/23 07:10:14| INFO mulmc_sld finished [took 64.7175s]
-06/11/23 07:10:15| INFO mul_sld finished [took 67.2892s]
-06/11/23 07:10:17| INFO mulne_sld finished [took 64.9305s]
-06/11/23 07:12:40| INFO bin_pacc finished [took 207.6921s]
-06/11/23 07:12:41| INFO binmc_sld finished [took 212.3821s]
-06/11/23 07:12:41| INFO bin_sld finished [took 214.5241s]
-06/11/23 07:12:43| INFO binne_sld finished [took 212.5115s]
-06/11/23 07:12:43| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 217.3597s]
-06/11/23 07:12:43| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
-06/11/23 07:13:39| INFO ref finished [took 46.5374s]
-06/11/23 07:13:45| INFO atc_mc finished [took 51.0121s]
-06/11/23 07:13:47| INFO mul_pacc finished [took 55.4950s]
-06/11/23 07:13:52| INFO mulmc_sld finished [took 64.7651s]
-06/11/23 07:13:52| INFO mul_sld finished [took 67.0632s]
-06/11/23 07:13:54| INFO mulne_sld finished [took 65.2533s]
-06/11/23 07:16:18| INFO bin_pacc finished [took 207.9541s]
-06/11/23 07:16:19| INFO bin_sld finished [took 214.6495s]
-06/11/23 07:16:19| INFO binmc_sld finished [took 213.2167s]
-06/11/23 07:16:24| INFO binne_sld finished [took 215.5646s]
-06/11/23 07:16:24| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 220.4851s]
-06/11/23 07:16:24| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
-06/11/23 07:17:20| INFO ref finished [took 46.7655s]
-06/11/23 07:17:25| INFO atc_mc finished [took 50.9430s]
-06/11/23 07:17:27| INFO mul_pacc finished [took 55.4948s]
-06/11/23 07:17:44| INFO mul_sld finished [took 78.5002s]
-06/11/23 07:17:46| INFO mulmc_sld finished [took 78.7519s]
-06/11/23 07:17:48| INFO mulne_sld finished [took 78.4293s]
-06/11/23 07:19:59| INFO bin_pacc finished [took 208.5200s]
-06/11/23 07:20:02| INFO bin_sld finished [took 216.9046s]
-06/11/23 07:20:03| INFO binmc_sld finished [took 216.2736s]
-06/11/23 07:20:03| INFO binne_sld finished [took 214.9573s]
-06/11/23 07:20:03| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 219.7592s]
-06/11/23 07:20:03| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
-06/11/23 07:20:05| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 07:20:06| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 07:20:08| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 07:20:10| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 07:20:12| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 07:20:48| INFO ref finished [took 36.6985s]
-06/11/23 07:20:52| INFO atc_mc finished [took 39.8292s]
-06/11/23 07:20:55| INFO mulmc_sld finished [took 48.0943s]
-06/11/23 07:20:56| INFO mul_sld finished [took 50.2138s]
-06/11/23 07:20:57| INFO mulne_sld finished [took 47.9755s]
-06/11/23 07:20:57| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 53.5645s]
-----------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------
-06/11/23 10:25:08| INFO dataset rcv1_CCAT_1prevs
-06/11/23 10:25:12| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs started
-06/11/23 10:26:02| INFO ref finished [took 43.6300s]
-06/11/23 10:26:05| INFO atc_mc finished [took 46.2297s]
-06/11/23 10:26:46| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00906) [took 88.7593s]
-06/11/23 10:27:29| INFO mul_pacc_gs finished [took 132.4595s]
-06/11/23 10:31:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00900) [took 379.8213s]
-06/11/23 10:34:52| INFO bin_pacc_gs finished [took 576.1136s]
-----------------------------------------------------------------------------------------------------
-06/11/23 10:55:40| INFO dataset rcv1_CCAT_1prevs
-06/11/23 10:55:44| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs started
-06/11/23 10:56:36| INFO ref finished [took 44.5230s]
-06/11/23 10:56:40| INFO atc_mc finished [took 47.6566s]
-06/11/23 10:57:20| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00927) [took 90.0830s]
-06/11/23 10:58:04| INFO mul_pacc_gs finished [took 134.5283s]
-06/11/23 11:02:12| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00974) [took 383.6784s]
-06/11/23 11:05:24| INFO bin_pacc_gs finished [took 574.8730s]
-06/11/23 11:10:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00775) [took 897.6622s]
-06/11/23 11:11:27| INFO mul_sld_gs finished [took 940.1205s]
-06/11/23 11:18:11| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00835) [took 1344.8544s]
-06/11/23 11:21:09| INFO bin_sld_gs finished [took 1523.4358s]
-06/11/23 11:21:09| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs finished [took 1525.2268s]
-----------------------------------------------------------------------------------------------------
-06/11/23 11:21:26| INFO dataset rcv1_CCAT_1prevs
-06/11/23 11:21:30| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs started
-06/11/23 11:22:18| INFO ref finished [took 42.1948s]
-06/11/23 11:22:23| INFO atc_mc finished [took 45.7857s]
-06/11/23 11:23:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00987) [took 87.4022s]
-06/11/23 11:23:45| INFO mul_pacc_gs finished [took 130.6127s]
-06/11/23 11:27:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00925) [took 374.1460s]
-06/11/23 11:29:46| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00775) [took 493.2309s]
-06/11/23 11:30:30| INFO mul_sld_gs finished [took 537.7362s]
-06/11/23 11:30:56| INFO bin_pacc_gs finished [took 562.8681s]
-06/11/23 11:35:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00835) [took 840.9875s]
-06/11/23 11:38:31| INFO bin_sld_gs finished [took 1019.8362s]
-06/11/23 11:38:31| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs finished [took 1021.3535s]
-----------------------------------------------------------------------------------------------------
-06/11/23 11:53:50| INFO dataset rcv1_CCAT_9prevs
-06/11/23 11:53:56| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-06/11/23 11:56:45| INFO doc_feat finished [took 83.7957s]
-06/11/23 11:56:58| INFO mulne_pacc finished [took 146.6577s]
-06/11/23 11:57:03| INFO ref finished [took 120.2665s]
-06/11/23 11:57:05| INFO mul_pacc finished [took 169.5909s]
-06/11/23 11:57:07| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-06/11/23 11:57:08| INFO kfcv finished [took 130.0948s]
-06/11/23 11:57:13| INFO mulmc_pacc finished [took 173.0431s]
-06/11/23 11:57:16| INFO atc_mc finished [took 125.2363s]
-06/11/23 11:57:17| INFO mul_sld finished [took 199.1179s]
-06/11/23 11:57:18| INFO mul_cc finished [took 148.2203s]
-06/11/23 11:57:20| INFO atc_ne finished [took 121.9570s]
-06/11/23 11:57:39| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00899) [took 176.8809s]
-06/11/23 11:58:48| INFO mul_pacc_gs finished [took 245.7641s]
-06/11/23 12:00:56| INFO bin_pacc finished [took 409.8967s]
-06/11/23 12:01:03| INFO bin_sld finished [took 426.0031s]
-06/11/23 12:01:09| INFO binmc_pacc finished [took 412.9057s]
-06/11/23 12:01:13| INFO bin_cc finished [took 389.4719s]
-06/11/23 12:01:14| INFO binne_pacc finished [took 411.1276s]
-06/11/23 12:02:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 12:03:18| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00719) [took 523.4665s]
-06/11/23 12:04:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 643.3372s]
-06/11/23 12:05:27| INFO mul_sld_gs finished [took 686.5912s]
-06/11/23 12:06:25| INFO bin_pacc_gs finished [took 710.5248s]
-06/11/23 12:08:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 892.3454s]
-06/11/23 12:11:50| INFO bin_sld_gs finished [took 1070.2847s]
-06/11/23 12:11:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 1073.7689s]
-06/11/23 12:11:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-06/11/23 12:14:15| INFO doc_feat finished [took 80.2198s]
-06/11/23 12:14:27| INFO ref finished [took 106.1446s]
-06/11/23 12:14:36| INFO mul_pacc finished [took 155.8715s]
-06/11/23 12:14:37| INFO mul_sld finished [took 162.7857s]
-06/11/23 12:14:47| INFO kfcv finished [took 132.1178s]
-06/11/23 12:14:55| INFO atc_mc finished [took 127.9109s]
-06/11/23 12:14:57| INFO atc_ne finished [took 121.6128s]
-06/11/23 12:14:58| INFO mulmc_pacc finished [took 173.9023s]
-06/11/23 12:14:58| INFO mulne_pacc finished [took 167.2920s]
-06/11/23 12:14:59| INFO mul_cc finished [took 147.7428s]
-06/11/23 12:15:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00931) [took 186.6087s]
-06/11/23 12:16:44| INFO mul_pacc_gs finished [took 261.9352s]
-06/11/23 12:18:49| INFO binmc_pacc finished [took 407.0394s]
-06/11/23 12:18:50| INFO bin_pacc finished [took 410.4620s]
-06/11/23 12:18:55| INFO bin_sld finished [took 422.8949s]
-06/11/23 12:19:01| INFO binne_pacc finished [took 410.3575s]
-06/11/23 12:19:03| INFO bin_cc finished [took 396.9482s]
-06/11/23 12:20:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 12:20:41| INFO bin_sld_gsq finished [took 524.4318s]
-06/11/23 12:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00784) [took 546.2730s]
-06/11/23 12:22:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 640.2364s]
-06/11/23 12:23:20| INFO mul_sld_gs finished [took 683.6191s]
-06/11/23 12:24:29| INFO bin_pacc_gs finished [took 732.6258s]
-06/11/23 12:27:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 948.8111s]
-06/11/23 12:30:43| INFO bin_sld_gs finished [took 1128.0644s]
-06/11/23 12:30:43| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 1132.7995s]
-06/11/23 12:30:43| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-06/11/23 12:33:12| INFO mul_sld finished [took 146.3214s]
-06/11/23 12:33:24| INFO mul_cc finished [took 118.2992s]
-06/11/23 12:33:26| INFO doc_feat finished [took 96.3414s]
-06/11/23 12:33:36| INFO atc_ne finished [took 108.2657s]
-06/11/23 12:33:37| INFO mulne_pacc finished [took 155.4759s]
-06/11/23 12:33:39| INFO atc_mc finished [took 119.0950s]
-06/11/23 12:33:39| INFO mul_pacc finished [took 166.1039s]
-06/11/23 12:33:40| INFO ref finished [took 122.3921s]
-06/11/23 12:33:40| INFO mulmc_pacc finished [took 164.5722s]
-06/11/23 12:33:43| INFO kfcv finished [took 131.6124s]
-06/11/23 12:34:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00857) [took 188.0301s]
-06/11/23 12:35:45| INFO mul_pacc_gs finished [took 269.4655s]
-06/11/23 12:37:47| INFO binne_pacc finished [took 409.7038s]
-06/11/23 12:37:47| INFO bin_sld finished [took 421.4590s]
-06/11/23 12:37:55| INFO bin_pacc finished [took 423.8805s]
-06/11/23 12:37:57| INFO binmc_pacc finished [took 422.8180s]
-06/11/23 12:38:01| INFO bin_cc finished [took 400.2199s]
-06/11/23 12:39:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 12:39:41| INFO bin_sld_gsq finished [took 531.7360s]
-06/11/23 12:40:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.6726s]
-06/11/23 12:41:35| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 646.0507s]
-06/11/23 12:42:19| INFO mul_sld_gs finished [took 690.7431s]
-06/11/23 12:43:25| INFO bin_pacc_gs finished [took 737.2287s]
-06/11/23 12:47:07| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 979.3211s]
-06/11/23 12:50:07| INFO bin_sld_gs finished [took 1159.4207s]
-06/11/23 12:50:07| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1163.9370s]
-06/11/23 12:50:07| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-06/11/23 12:52:34| INFO doc_feat finished [took 79.3857s]
-06/11/23 12:52:39| INFO mul_pacc finished [took 143.2358s]
-06/11/23 12:52:49| INFO mul_sld finished [took 159.6160s]
-06/11/23 12:52:58| INFO kfcv finished [took 121.1756s]
-06/11/23 12:53:07| INFO mulmc_pacc finished [took 167.6154s]
-06/11/23 12:53:09| INFO atc_ne finished [took 115.9704s]
-06/11/23 12:53:11| INFO ref finished [took 127.9906s]
-06/11/23 12:53:17| INFO atc_mc finished [took 129.9605s]
-06/11/23 12:53:19| INFO mulne_pacc finished [took 166.1444s]
-06/11/23 12:53:21| INFO mul_cc finished [took 152.0451s]
-06/11/23 12:53:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.1015s]
-06/11/23 12:55:03| INFO mul_pacc_gs finished [took 261.6088s]
-06/11/23 12:57:20| INFO binmc_pacc finished [took 422.6680s]
-06/11/23 12:57:23| INFO bin_sld finished [took 434.1109s]
-06/11/23 12:57:26| INFO bin_pacc finished [took 431.1893s]
-06/11/23 12:57:28| INFO binne_pacc finished [took 427.7980s]
-06/11/23 12:57:29| INFO bin_cc finished [took 402.6463s]
-06/11/23 12:58:43| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 12:59:20| INFO bin_sld_gsq finished [took 546.8013s]
-06/11/23 12:59:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00858) [took 550.8127s]
-06/11/23 13:01:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 652.8483s]
-06/11/23 13:01:47| INFO mul_sld_gs finished [took 695.7927s]
-06/11/23 13:02:56| INFO bin_pacc_gs finished [took 739.4380s]
-06/11/23 13:06:49| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 999.0699s]
-06/11/23 13:09:50| INFO bin_sld_gs finished [took 1179.8181s]
-06/11/23 13:09:50| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1183.4124s]
-06/11/23 13:09:50| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-06/11/23 13:12:34| INFO doc_feat finished [took 88.8963s]
-06/11/23 13:12:43| INFO mul_sld finished [took 169.3932s]
-06/11/23 13:12:47| INFO mul_pacc finished [took 166.5633s]
-06/11/23 13:12:50| INFO kfcv finished [took 134.2527s]
-06/11/23 13:12:58| INFO ref finished [took 128.7367s]
-06/11/23 13:12:59| INFO mulne_pacc finished [took 161.0902s]
-06/11/23 13:13:00| INFO mulmc_pacc finished [took 176.8006s]
-06/11/23 13:13:01| INFO atc_mc finished [took 129.5173s]
-06/11/23 13:13:06| INFO atc_ne finished [took 122.8886s]
-06/11/23 13:13:16| INFO mul_cc finished [took 152.5218s]
-06/11/23 13:13:34| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00774) [took 183.0928s]
-06/11/23 13:14:57| INFO mul_pacc_gs finished [took 266.4369s]
-06/11/23 13:17:06| INFO bin_pacc finished [took 427.3693s]
-06/11/23 13:17:08| INFO binmc_pacc finished [took 426.6359s]
-06/11/23 13:17:14| INFO bin_sld finished [took 441.7834s]
-06/11/23 13:17:20| INFO binne_pacc finished [took 435.6569s]
-06/11/23 13:17:22| INFO bin_cc finished [took 412.7263s]
-06/11/23 13:18:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 13:19:06| INFO bin_sld_gsq finished [took 549.0379s]
-06/11/23 13:19:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00709) [took 545.0306s]
-06/11/23 13:20:41| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 645.5669s]
-06/11/23 13:21:25| INFO mul_sld_gs finished [took 689.4814s]
-06/11/23 13:22:32| INFO bin_pacc_gs finished [took 730.0602s]
-06/11/23 13:26:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 985.8522s]
-06/11/23 13:29:21| INFO bin_sld_gs finished [took 1166.4200s]
-06/11/23 13:29:21| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 1170.8744s]
-06/11/23 13:29:21| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-06/11/23 13:31:52| INFO doc_feat finished [took 80.3058s]
-06/11/23 13:32:00| INFO mul_sld finished [took 153.1261s]
-06/11/23 13:32:00| INFO mul_pacc finished [took 148.0156s]
-06/11/23 13:32:13| INFO kfcv finished [took 122.2270s]
-06/11/23 13:32:13| INFO mulne_pacc finished [took 145.0130s]
-06/11/23 13:32:22| INFO ref finished [took 122.3525s]
-06/11/23 13:32:23| INFO atc_mc finished [took 120.2587s]
-06/11/23 13:32:23| INFO atc_ne finished [took 113.5667s]
-06/11/23 13:32:23| INFO mulmc_pacc finished [took 167.7106s]
-06/11/23 13:32:36| INFO mul_cc finished [took 143.6517s]
-06/11/23 13:33:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00802) [took 182.2049s]
-06/11/23 13:34:23| INFO mul_pacc_gs finished [took 261.0038s]
-06/11/23 13:36:19| INFO binmc_pacc finished [took 405.9199s]
-06/11/23 13:36:31| INFO bin_sld finished [took 426.3780s]
-06/11/23 13:36:32| INFO bin_pacc finished [took 420.2833s]
-06/11/23 13:36:34| INFO binne_pacc finished [took 417.2048s]
-06/11/23 13:36:42| INFO bin_cc finished [took 394.3524s]
-06/11/23 13:37:45| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 13:38:18| INFO bin_sld_gsq finished [took 528.6956s]
-06/11/23 13:38:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00707) [took 544.2769s]
-06/11/23 13:39:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 628.0656s]
-06/11/23 13:40:41| INFO mul_sld_gs finished [took 673.3968s]
-06/11/23 13:41:58| INFO bin_pacc_gs finished [took 730.5371s]
-06/11/23 13:45:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 960.1061s]
-06/11/23 13:48:28| INFO bin_sld_gs finished [took 1140.6073s]
-06/11/23 13:48:28| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1146.6395s]
-06/11/23 13:48:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-06/11/23 13:50:49| INFO mul_pacc finished [took 130.9408s]
-06/11/23 13:51:02| INFO doc_feat finished [took 86.2411s]
-06/11/23 13:51:07| INFO mul_sld finished [took 155.4513s]
-06/11/23 13:51:15| INFO atc_ne finished [took 101.0761s]
-06/11/23 13:51:20| INFO ref finished [took 121.3689s]
-06/11/23 13:51:20| INFO atc_mc finished [took 106.6415s]
-06/11/23 13:51:22| INFO mulmc_pacc finished [took 160.4221s]
-06/11/23 13:51:22| INFO mulne_pacc finished [took 150.1203s]
-06/11/23 13:51:25| INFO kfcv finished [took 127.5280s]
-06/11/23 13:51:35| INFO mul_cc finished [took 145.4437s]
-06/11/23 13:52:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00886) [took 182.0543s]
-06/11/23 13:53:23| INFO mul_pacc_gs finished [took 262.2496s]
-06/11/23 13:55:28| INFO bin_sld finished [took 417.7315s]
-06/11/23 13:55:30| INFO binmc_pacc finished [took 410.0114s]
-06/11/23 13:55:30| INFO bin_pacc finished [took 413.5912s]
-06/11/23 13:55:35| INFO binne_pacc finished [took 411.8241s]
-06/11/23 13:55:42| INFO bin_cc finished [took 396.5011s]
-06/11/23 13:56:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 13:57:22| INFO bin_sld_gsq finished [took 527.2507s]
-06/11/23 13:58:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00910) [took 547.7641s]
-06/11/23 13:59:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 634.8469s]
-06/11/23 13:59:54| INFO mul_sld_gs finished [took 680.2027s]
-06/11/23 14:01:07| INFO bin_pacc_gs finished [took 731.8655s]
-06/11/23 14:04:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 960.6861s]
-06/11/23 14:07:34| INFO bin_sld_gs finished [took 1141.7199s]
-06/11/23 14:07:34| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 1146.2680s]
-06/11/23 14:07:34| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-06/11/23 14:10:08| INFO mulmc_pacc finished [took 141.2266s]
-06/11/23 14:10:19| INFO atc_ne finished [took 101.4512s]
-06/11/23 14:10:20| INFO mul_sld finished [took 162.5808s]
-06/11/23 14:10:23| INFO mul_pacc finished [took 158.9068s]
-06/11/23 14:10:30| INFO kfcv finished [took 123.4790s]
-06/11/23 14:10:33| INFO mulne_pacc finished [took 158.4983s]
-06/11/23 14:10:33| INFO doc_feat finished [took 111.7987s]
-06/11/23 14:10:35| INFO ref finished [took 124.4184s]
-06/11/23 14:10:40| INFO atc_mc finished [took 126.3543s]
-06/11/23 14:10:40| INFO mul_cc finished [took 139.5958s]
-06/11/23 14:11:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.01309) [took 184.0645s]
-06/11/23 14:12:44| INFO mul_pacc_gs finished [took 272.5404s]
-06/11/23 14:14:32| INFO binmc_pacc finished [took 406.3609s]
-06/11/23 14:14:38| INFO bin_pacc finished [took 414.8972s]
-06/11/23 14:14:43| INFO binne_pacc finished [took 414.4123s]
-06/11/23 14:14:51| INFO bin_cc finished [took 395.5254s]
-06/11/23 14:14:55| INFO bin_sld finished [took 437.7681s]
-06/11/23 14:15:58| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 14:16:33| INFO bin_sld_gsq finished [took 532.4040s]
-06/11/23 14:16:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00812) [took 536.4746s]
-06/11/23 14:18:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 636.4067s]
-06/11/23 14:19:00| INFO mul_sld_gs finished [took 680.2467s]
-06/11/23 14:20:01| INFO bin_pacc_gs finished [took 720.9205s]
-06/11/23 14:23:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 954.4487s]
-06/11/23 14:26:41| INFO bin_sld_gs finished [took 1142.3328s]
-06/11/23 14:26:41| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 1146.7713s]
-06/11/23 14:26:41| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-06/11/23 14:29:04| INFO mul_pacc finished [took 133.1736s]
-06/11/23 14:29:07| INFO ref finished [took 87.1594s]
-06/11/23 14:29:16| INFO doc_feat finished [took 83.8190s]
-06/11/23 14:29:21| INFO mulmc_pacc finished [took 147.5202s]
-06/11/23 14:29:22| INFO atc_mc finished [took 99.1039s]
-06/11/23 14:29:23| INFO kfcv finished [took 109.5348s]
-06/11/23 14:29:27| INFO mulne_pacc finished [took 148.1672s]
-06/11/23 14:29:33| INFO atc_ne finished [took 101.4673s]
-06/11/23 14:29:36| INFO mul_cc finished [took 126.0447s]
-06/11/23 14:29:42| INFO mul_sld finished [took 177.5880s]
-06/11/23 14:30:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01497) [took 175.1432s]
-06/11/23 14:31:33| INFO mul_pacc_gs finished [took 252.3399s]
-06/11/23 14:33:34| INFO binmc_pacc finished [took 401.7891s]
-06/11/23 14:33:35| INFO binne_pacc finished [took 400.4138s]
-06/11/23 14:33:36| INFO bin_pacc finished [took 406.7598s]
-06/11/23 14:33:48| INFO bin_cc finished [took 378.7595s]
-06/11/23 14:33:48| INFO bin_sld finished [took 423.7366s]
-06/11/23 14:34:47| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 14:35:26| INFO bin_sld_gsq finished [took 518.8996s]
-06/11/23 14:36:13| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00880) [took 539.3992s]
-06/11/23 14:37:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 622.0419s]
-06/11/23 14:37:53| INFO mul_sld_gs finished [took 666.0058s]
-06/11/23 14:39:16| INFO bin_pacc_gs finished [took 722.5231s]
-06/11/23 14:42:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 929.3464s]
-06/11/23 14:45:14| INFO bin_sld_gs finished [took 1108.7356s]
-06/11/23 14:45:14| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 1113.2364s]
-06/11/23 14:48:04| INFO dataset imdb_9prevs
-06/11/23 14:48:14| INFO Dataset sample 0.10 of dataset imdb_9prevs started
-06/11/23 14:48:17| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 14:48:18| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 14:48:31| INFO doc_feat finished [took 11.5257s]
-06/11/23 14:48:36| INFO ref finished [took 18.5620s]
-06/11/23 14:48:42| INFO kfcv finished [took 24.7227s]
-06/11/23 14:48:44| INFO atc_ne finished [took 25.5676s]
-06/11/23 14:48:46| INFO atc_mc finished [took 27.4910s]
-06/11/23 14:48:50| INFO mulne_pacc finished [took 34.0415s]
-06/11/23 14:48:57| INFO mulmc_pacc finished [took 41.7500s]
-06/11/23 14:48:58| INFO mul_pacc finished [took 43.0162s]
-06/11/23 14:48:58| INFO mul_cc finished [took 40.3279s]
-06/11/23 14:49:16| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-06/11/23 14:49:26| INFO mul_sld finished [took 71.4588s]
-06/11/23 14:50:10| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-06/11/23 14:52:12| INFO binne_pacc finished [took 236.2174s]
-06/11/23 14:52:16| INFO binmc_pacc finished [took 240.4686s]
-06/11/23 14:52:19| INFO bin_cc finished [took 241.9141s]
-06/11/23 14:52:20| INFO bin_pacc finished [took 244.5632s]
-06/11/23 14:52:23| INFO bin_sld finished [took 249.0477s]
-06/11/23 14:53:48| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 14:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 443.6010s]
-06/11/23 14:55:51| INFO mul_sld_gs finished [took 455.9932s]
-06/11/23 14:55:51| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 456.7746s]
-06/11/23 14:55:51| INFO Dataset sample 0.20 of dataset imdb_9prevs started
-06/11/23 14:56:07| INFO doc_feat finished [took 11.2758s]
-06/11/23 14:56:18| INFO atc_mc finished [took 22.2986s]
-06/11/23 14:56:22| INFO ref finished [took 26.3482s]
-06/11/23 14:56:25| INFO kfcv finished [took 30.4761s]
-06/11/23 14:56:29| INFO mul_pacc finished [took 36.5892s]
-06/11/23 14:56:29| INFO mulmc_pacc finished [took 36.7773s]
-06/11/23 14:56:38| INFO atc_ne finished [took 41.7824s]
-06/11/23 14:56:41| INFO mulne_pacc finished [took 47.8318s]
-06/11/23 14:56:41| INFO mul_cc finished [took 46.7221s]
-06/11/23 14:56:55| INFO mul_sld finished [took 63.3547s]
-06/11/23 14:57:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.01017) [took 119.9166s]
-06/11/23 14:58:15| INFO mul_pacc_gs finished [took 141.4446s]
-06/11/23 15:00:38| INFO binne_pacc finished [took 285.5562s]
-06/11/23 15:00:48| INFO bin_cc finished [took 293.8727s]
-06/11/23 15:00:49| INFO binmc_pacc finished [took 296.7176s]
-06/11/23 15:00:49| INFO bin_pacc finished [took 297.1868s]
-06/11/23 15:01:03| INFO bin_sld finished [took 312.0358s]
-06/11/23 15:02:29| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 15:02:34| INFO bin_sld_gsq finished [took 402.0748s]
-06/11/23 15:03:56| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00980) [took 482.9237s]
-06/11/23 15:05:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 548.0443s]
-06/11/23 15:05:14| INFO mul_sld_gs finished [took 562.2966s]
-06/11/23 15:06:30| INFO bin_pacc_gs finished [took 636.7956s]
-06/11/23 15:10:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 884.9748s]
-06/11/23 15:13:11| INFO bin_sld_gs finished [took 1039.3282s]
-06/11/23 15:13:11| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 1040.0772s]
-06/11/23 15:13:11| INFO Dataset sample 0.30 of dataset imdb_9prevs started
-06/11/23 15:13:39| INFO doc_feat finished [took 22.8145s]
-06/11/23 15:13:41| INFO atc_ne finished [took 24.3471s]
-06/11/23 15:13:45| INFO ref finished [took 28.7559s]
-06/11/23 15:13:52| INFO mulne_pacc finished [took 38.1365s]
-06/11/23 15:13:53| INFO kfcv finished [took 37.4026s]
-06/11/23 15:13:56| INFO atc_mc finished [took 39.4198s]
-06/11/23 15:13:59| INFO mul_pacc finished [took 45.9542s]
-06/11/23 15:13:59| INFO mul_cc finished [took 43.9076s]
-06/11/23 15:13:59| INFO mulmc_pacc finished [took 45.9395s]
-06/11/23 15:14:11| INFO mul_sld finished [took 59.8835s]
-06/11/23 15:15:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01028) [took 128.2866s]
-06/11/23 15:15:44| INFO mul_pacc_gs finished [took 149.5820s]
-06/11/23 15:18:03| INFO binne_pacc finished [took 289.3504s]
-06/11/23 15:18:07| INFO bin_pacc finished [took 294.7115s]
-06/11/23 15:18:14| INFO bin_cc finished [took 298.6839s]
-06/11/23 15:18:14| INFO binmc_pacc finished [took 300.9499s]
-06/11/23 15:18:14| INFO bin_sld finished [took 302.9035s]
-06/11/23 15:19:46| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 15:20:05| INFO bin_sld_gsq finished [took 413.1151s]
-06/11/23 15:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00916) [took 488.7327s]
-06/11/23 15:22:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 541.2865s]
-06/11/23 15:22:28| INFO mul_sld_gs finished [took 556.0867s]
-06/11/23 15:23:57| INFO bin_pacc_gs finished [took 643.0717s]
-06/11/23 15:27:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 860.3135s]
-06/11/23 15:30:05| INFO bin_sld_gs finished [took 1013.1878s]
-06/11/23 15:30:05| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 1014.3141s]
-06/11/23 15:30:05| INFO Dataset sample 0.40 of dataset imdb_9prevs started
-06/11/23 15:30:24| INFO doc_feat finished [took 13.8500s]
-06/11/23 15:30:32| INFO ref finished [took 22.3531s]
-06/11/23 15:30:41| INFO mul_pacc finished [took 34.1860s]
-06/11/23 15:30:45| INFO atc_ne finished [took 34.8111s]
-06/11/23 15:30:46| INFO kfcv finished [took 36.4055s]
-06/11/23 15:30:49| INFO atc_mc finished [took 38.7978s]
-06/11/23 15:30:49| INFO mulmc_pacc finished [took 42.4552s]
-06/11/23 15:30:51| INFO mul_cc finished [took 42.6899s]
-06/11/23 15:30:53| INFO mulne_pacc finished [took 45.2694s]
-06/11/23 15:30:57| INFO mul_sld finished [took 51.2705s]
-06/11/23 15:32:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01220) [took 124.5801s]
-06/11/23 15:32:34| INFO mul_pacc_gs finished [took 145.3368s]
-06/11/23 15:34:56| INFO binmc_pacc finished [took 289.1451s]
-06/11/23 15:35:04| INFO bin_sld finished [took 298.3514s]
-06/11/23 15:35:04| INFO binne_pacc finished [took 296.5538s]
-06/11/23 15:35:05| INFO bin_pacc finished [took 298.5077s]
-06/11/23 15:35:09| INFO bin_cc finished [took 300.1332s]
-06/11/23 15:36:41| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 15:37:08| INFO bin_sld_gsq finished [took 421.3938s]
-06/11/23 15:38:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01137) [took 490.9644s]
-06/11/23 15:38:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 531.8225s]
-06/11/23 15:39:12| INFO mul_sld_gs finished [took 546.4524s]
-06/11/23 15:40:53| INFO bin_pacc_gs finished [took 645.0957s]
-06/11/23 15:44:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 882.0550s]
-06/11/23 15:47:19| INFO bin_sld_gs finished [took 1033.2802s]
-06/11/23 15:47:19| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 1034.1241s]
-06/11/23 15:47:19| INFO Dataset sample 0.50 of dataset imdb_9prevs started
-06/11/23 15:47:36| INFO doc_feat finished [took 11.6005s]
-06/11/23 15:47:40| INFO ref finished [took 16.3058s]
-06/11/23 15:47:50| INFO atc_mc finished [took 25.8745s]
-06/11/23 15:47:52| INFO kfcv finished [took 29.0931s]
-06/11/23 15:47:53| INFO atc_ne finished [took 28.8903s]
-06/11/23 15:47:53| INFO mul_pacc finished [took 32.5473s]
-06/11/23 15:48:00| INFO mul_cc finished [took 37.3478s]
-06/11/23 15:48:01| INFO mulne_pacc finished [took 39.9745s]
-06/11/23 15:48:02| INFO mulmc_pacc finished [took 40.5057s]
-06/11/23 15:48:10| INFO mul_sld finished [took 50.1825s]
-06/11/23 15:49:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01107) [took 125.0329s]
-06/11/23 15:49:49| INFO mul_pacc_gs finished [took 146.7316s]
-06/11/23 15:52:15| INFO bin_cc finished [took 292.6719s]
-06/11/23 15:52:15| INFO binne_pacc finished [took 293.9844s]
-06/11/23 15:52:17| INFO bin_pacc finished [took 296.2830s]
-06/11/23 15:52:21| INFO binmc_pacc finished [took 299.4873s]
-06/11/23 15:52:23| INFO bin_sld finished [took 303.4889s]
-06/11/23 15:53:57| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 15:54:18| INFO bin_sld_gsq finished [took 418.0959s]
-06/11/23 15:55:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 489.7797s]
-06/11/23 15:56:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 536.7408s]
-06/11/23 15:56:33| INFO mul_sld_gs finished [took 552.5393s]
-06/11/23 15:58:05| INFO bin_pacc_gs finished [took 643.1581s]
-06/11/23 16:01:42| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 862.6012s]
-06/11/23 16:04:15| INFO bin_sld_gs finished [took 1015.3606s]
-06/11/23 16:04:15| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 1016.0642s]
-06/11/23 16:04:15| INFO Dataset sample 0.60 of dataset imdb_9prevs started
-06/11/23 16:04:40| INFO doc_feat finished [took 19.9628s]
-06/11/23 16:04:41| INFO kfcv finished [took 21.8848s]
-06/11/23 16:04:46| INFO ref finished [took 26.2613s]
-06/11/23 16:04:56| INFO mulmc_pacc finished [took 38.6399s]
-06/11/23 16:04:56| INFO atc_ne finished [took 35.7501s]
-06/11/23 16:04:57| INFO atc_mc finished [took 37.3907s]
-06/11/23 16:05:01| INFO mul_cc finished [took 41.6420s]
-06/11/23 16:05:01| INFO mul_pacc finished [took 44.6898s]
-06/11/23 16:05:02| INFO mulne_pacc finished [took 44.7679s]
-06/11/23 16:05:12| INFO mul_sld finished [took 56.0834s]
-06/11/23 16:06:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01082) [took 125.2569s]
-06/11/23 16:06:44| INFO mul_pacc_gs finished [took 146.2318s]
-06/11/23 16:09:05| INFO binne_pacc finished [took 288.1949s]
-06/11/23 16:09:10| INFO bin_pacc finished [took 293.3207s]
-06/11/23 16:09:12| INFO bin_sld finished [took 296.1022s]
-06/11/23 16:09:13| INFO binmc_pacc finished [took 296.4000s]
-06/11/23 16:09:18| INFO bin_cc finished [took 299.1982s]
-06/11/23 16:10:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 16:11:22| INFO bin_sld_gsq finished [took 425.6641s]
-06/11/23 16:12:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00976) [took 492.8847s]
-06/11/23 16:13:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 536.8669s]
-06/11/23 16:13:28| INFO mul_sld_gs finished [took 551.6187s]
-06/11/23 16:15:03| INFO bin_pacc_gs finished [took 645.6602s]
-06/11/23 16:19:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 907.7074s]
-06/11/23 16:21:57| INFO bin_sld_gs finished [took 1060.9759s]
-06/11/23 16:21:57| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 1061.7730s]
-06/11/23 16:21:57| INFO Dataset sample 0.70 of dataset imdb_9prevs started
-06/11/23 16:22:23| INFO doc_feat finished [took 20.2428s]
-06/11/23 16:22:34| INFO kfcv finished [took 32.1532s]
-06/11/23 16:22:36| INFO ref finished [took 34.3738s]
-06/11/23 16:22:38| INFO mul_sld finished [took 40.1101s]
-06/11/23 16:22:40| INFO mul_cc finished [took 38.6722s]
-06/11/23 16:22:41| INFO atc_mc finished [took 38.9379s]
-06/11/23 16:22:43| INFO atc_ne finished [took 40.3132s]
-06/11/23 16:22:43| INFO mulne_pacc finished [took 43.7833s]
-06/11/23 16:22:44| INFO mulmc_pacc finished [took 44.4084s]
-06/11/23 16:22:46| INFO mul_pacc finished [took 47.7998s]
-06/11/23 16:24:08| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01575) [took 127.2393s]
-06/11/23 16:24:31| INFO mul_pacc_gs finished [took 150.2100s]
-06/11/23 16:26:49| INFO bin_cc finished [took 288.6128s]
-06/11/23 16:26:51| INFO bin_pacc finished [took 292.1757s]
-06/11/23 16:26:52| INFO binne_pacc finished [took 293.0194s]
-06/11/23 16:27:01| INFO binmc_pacc finished [took 302.5703s]
-06/11/23 16:27:01| INFO bin_sld finished [took 303.9303s]
-06/11/23 16:28:32| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 16:28:53| INFO bin_sld_gsq finished [took 414.4520s]
-06/11/23 16:30:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01641) [took 494.7681s]
-06/11/23 16:31:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 542.3282s]
-06/11/23 16:31:15| INFO mul_sld_gs finished [took 557.2859s]
-06/11/23 16:32:49| INFO bin_pacc_gs finished [took 648.9428s]
-06/11/23 16:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 864.7237s]
-06/11/23 16:38:54| INFO bin_sld_gs finished [took 1015.9618s]
-06/11/23 16:38:54| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 1016.7743s]
-06/11/23 16:38:54| INFO Dataset sample 0.80 of dataset imdb_9prevs started
-06/11/23 16:39:19| INFO doc_feat finished [took 19.9639s]
-06/11/23 16:39:22| INFO atc_mc finished [took 22.9650s]
-06/11/23 16:39:26| INFO kfcv finished [took 27.9671s]
-06/11/23 16:39:30| INFO mul_pacc finished [took 34.3899s]
-06/11/23 16:39:31| INFO ref finished [took 32.4692s]
-06/11/23 16:39:33| INFO mulne_pacc finished [took 37.2045s]
-06/11/23 16:39:39| INFO atc_ne finished [took 39.7686s]
-06/11/23 16:39:41| INFO mul_cc finished [took 42.9411s]
-06/11/23 16:39:41| INFO mulmc_pacc finished [took 44.9724s]
-06/11/23 16:39:46| INFO mul_sld finished [took 51.4269s]
-06/11/23 16:40:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01013) [took 122.2196s]
-06/11/23 16:41:24| INFO mul_pacc_gs finished [took 146.7076s]
-06/11/23 16:43:40| INFO binne_pacc finished [took 284.1154s]
-06/11/23 16:43:52| INFO bin_pacc finished [took 296.8885s]
-06/11/23 16:43:54| INFO bin_cc finished [took 297.1714s]
-06/11/23 16:43:56| INFO binmc_pacc finished [took 300.6806s]
-06/11/23 16:43:57| INFO bin_sld finished [took 302.6966s]
-06/11/23 16:45:26| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
-06/11/23 16:45:41| INFO bin_sld_gsq finished [took 405.8247s]
-06/11/23 16:47:00| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00949) [took 483.3129s]
-06/11/23 16:47:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 539.6504s]
-06/11/23 16:48:09| INFO mul_sld_gs finished [took 553.8401s]
-06/11/23 16:49:34| INFO bin_pacc_gs finished [took 637.2772s]
-06/11/23 16:53:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 875.8870s]
-06/11/23 16:56:08| INFO bin_sld_gs finished [took 1033.4325s]
-06/11/23 16:56:08| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 1034.1983s]
-06/11/23 16:56:08| INFO Dataset sample 0.90 of dataset imdb_9prevs started
-06/11/23 16:56:09| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:09| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:10| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:10| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:10| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:10| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:10| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:10| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:11| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:11| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 16:56:22| INFO doc_feat finished [took 10.1613s]
-06/11/23 16:56:25| INFO ref finished [took 13.7569s]
-06/11/23 16:56:27| INFO kfcv finished [took 15.6337s]
-06/11/23 16:56:29| INFO atc_mc finished [took 18.0104s]
-06/11/23 16:56:30| INFO atc_ne finished [took 18.0260s]
-06/11/23 16:56:31| INFO mul_cc finished [took 20.6201s]
-06/11/23 16:56:40| INFO mul_sld finished [took 31.2942s]
-06/11/23 16:56:47| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 16:58:55| INFO bin_cc finished [took 164.5182s]
-06/11/23 16:58:59| INFO bin_sld finished [took 170.5046s]
-06/11/23 17:02:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 368.6067s]
-06/11/23 17:02:29| INFO mul_sld_gs finished [took 380.7801s]
-06/11/23 17:02:29| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 381.5305s]
-----------------------------------------------------------------------------------------------------
-06/11/23 18:04:06| INFO dataset rcv1_GCAT_9prevs
-06/11/23 18:04:12| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
-06/11/23 18:04:19| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:21| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:22| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:24| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:24| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:26| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:27| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:28| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:04:29| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:05:10| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-06/11/23 18:05:41| INFO ref finished [took 65.3048s]
-06/11/23 18:05:43| INFO kfcv finished [took 66.9585s]
-06/11/23 18:05:45| INFO doc_feat finished [took 56.7504s]
-06/11/23 18:05:49| INFO mul_cc finished [took 77.6035s]
-06/11/23 18:05:49| INFO atc_mc finished [took 66.4650s]
-06/11/23 18:05:52| INFO atc_ne finished [took 65.1035s]
-06/11/23 18:05:52| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-06/11/23 18:05:56| INFO mul_sld finished [took 101.3427s]
-06/11/23 18:08:12| INFO bin_sld finished [took 238.6323s]
-06/11/23 18:08:21| INFO bin_cc finished [took 230.3034s]
-06/11/23 18:10:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00897) [took 402.3046s]
-06/11/23 18:11:39| INFO mul_sld_gs finished [took 441.7473s]
-06/11/23 18:11:39| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 446.6543s]
-06/11/23 18:11:39| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
-06/11/23 18:14:11| INFO mulmc_pacc finished [took 140.5240s]
-06/11/23 18:14:13| INFO kfcv finished [took 108.3325s]
-06/11/23 18:14:16| INFO doc_feat finished [took 91.1407s]
-06/11/23 18:14:21| INFO atc_ne finished [took 96.9645s]
-06/11/23 18:14:22| INFO mul_pacc finished [took 154.9757s]
-06/11/23 18:14:36| INFO ref finished [took 118.1583s]
-06/11/23 18:14:37| INFO atc_mc finished [took 118.5016s]
-06/11/23 18:14:41| INFO mulne_pacc finished [took 157.8831s]
-06/11/23 18:14:49| INFO mul_cc finished [took 144.8053s]
-06/11/23 18:14:50| INFO mul_sld finished [took 188.8450s]
-06/11/23 18:15:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01452) [took 184.0929s]
-06/11/23 18:16:33| INFO mul_pacc_gs finished [took 258.2234s]
-06/11/23 18:18:46| INFO binmc_pacc finished [took 417.1372s]
-06/11/23 18:18:48| INFO bin_pacc finished [took 422.0619s]
-06/11/23 18:18:52| INFO bin_sld finished [took 431.4426s]
-06/11/23 18:18:56| INFO binne_pacc finished [took 421.5812s]
-06/11/23 18:19:02| INFO bin_cc finished [took 402.4673s]
-06/11/23 18:19:32| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
-06/11/23 18:20:26| INFO bin_sld_gsq finished [took 522.0734s]
-06/11/23 18:21:11| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 540.4022s]
-06/11/23 18:21:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00821) [took 600.6611s]
-06/11/23 18:22:25| INFO mul_sld_gs finished [took 642.1063s]
-06/11/23 18:24:14| INFO bin_pacc_gs finished [took 723.2605s]
-06/11/23 18:26:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00816) [took 911.5066s]
-06/11/23 18:29:56| INFO bin_sld_gs finished [took 1093.4674s]
-06/11/23 18:29:56| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 1096.7184s]
-06/11/23 18:29:56| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
-06/11/23 18:32:21| INFO ref finished [took 89.3355s]
-06/11/23 18:32:33| INFO doc_feat finished [took 91.9119s]
-06/11/23 18:32:35| INFO mulmc_pacc finished [took 147.2084s]
-06/11/23 18:32:38| INFO mulne_pacc finished [took 137.0643s]
-06/11/23 18:32:54| INFO atc_mc finished [took 117.6847s]
-06/11/23 18:32:56| INFO kfcv finished [took 129.8598s]
-06/11/23 18:33:00| INFO mul_pacc finished [took 174.5769s]
-06/11/23 18:33:00| INFO mul_sld finished [took 181.1734s]
-06/11/23 18:33:03| INFO atc_ne finished [took 123.9984s]
-06/11/23 18:33:09| INFO mul_cc finished [took 148.8635s]
-06/11/23 18:33:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00629) [took 177.7598s]
-06/11/23 18:34:51| INFO mul_pacc_gs finished [took 256.4186s]
-06/11/23 18:37:10| INFO bin_pacc finished [took 425.7912s]
-06/11/23 18:37:12| INFO binmc_pacc finished [took 425.7599s]
-06/11/23 18:37:14| INFO binne_pacc finished [took 424.0101s]
-06/11/23 18:37:18| INFO bin_sld finished [took 440.4389s]
-06/11/23 18:37:22| INFO bin_cc finished [took 407.2413s]
-06/11/23 18:37:52| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
-06/11/23 18:38:51| INFO bin_sld_gsq finished [took 529.6242s]
-06/11/23 18:39:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00489) [took 541.8062s]
-06/11/23 18:40:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00615) [took 601.7630s]
-06/11/23 18:40:45| INFO mul_sld_gs finished [took 644.5111s]
-06/11/23 18:42:37| INFO bin_pacc_gs finished [took 729.3942s]
-06/11/23 18:45:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00490) [took 936.3088s]
-06/11/23 18:48:37| INFO bin_sld_gs finished [took 1117.0610s]
-06/11/23 18:48:37| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 1120.9681s]
-06/11/23 18:48:37| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
-06/11/23 18:51:02| INFO doc_feat finished [took 79.6380s]
-06/11/23 18:51:20| INFO mulne_pacc finished [took 144.5625s]
-06/11/23 18:51:30| INFO mul_sld finished [took 171.1473s]
-06/11/23 18:51:35| INFO mulmc_pacc finished [took 166.1468s]
-06/11/23 18:51:39| INFO mul_pacc finished [took 172.9449s]
-06/11/23 18:51:43| INFO ref finished [took 132.2492s]
-06/11/23 18:51:45| INFO kfcv finished [took 137.9538s]
-06/11/23 18:51:52| INFO atc_mc finished [took 137.7185s]
-06/11/23 18:51:54| INFO atc_ne finished [took 134.1066s]
-06/11/23 18:51:59| INFO mul_cc finished [took 159.0670s]
-06/11/23 18:52:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01049) [took 180.3366s]
-06/11/23 18:53:38| INFO mul_pacc_gs finished [took 266.6075s]
-06/11/23 18:56:00| INFO bin_sld finished [took 441.9022s]
-06/11/23 18:56:02| INFO binne_pacc finished [took 431.1354s]
-06/11/23 18:56:02| INFO binmc_pacc finished [took 434.5268s]
-06/11/23 18:56:04| INFO bin_pacc finished [took 438.8400s]
-06/11/23 18:56:07| INFO bin_cc finished [took 412.8827s]
-06/11/23 18:56:38| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
-06/11/23 18:57:38| INFO bin_sld_gsq finished [took 534.9970s]
-06/11/23 18:58:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.5790s]
-06/11/23 18:58:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00692) [took 616.7506s]
-06/11/23 18:59:43| INFO mul_sld_gs finished [took 661.6976s]
-06/11/23 19:01:20| INFO bin_pacc_gs finished [took 735.1934s]
-06/11/23 19:04:29| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00601) [took 948.3129s]
-06/11/23 19:07:30| INFO bin_sld_gs finished [took 1129.1432s]
-06/11/23 19:07:30| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 1133.2853s]
-06/11/23 19:07:30| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
-06/11/23 19:10:11| INFO doc_feat finished [took 90.8028s]
-06/11/23 19:10:12| INFO mul_sld finished [took 159.3725s]
-06/11/23 19:10:17| INFO atc_mc finished [took 108.3872s]
-06/11/23 19:10:20| INFO mulmc_pacc finished [took 158.7937s]
-06/11/23 19:10:27| INFO kfcv finished [took 125.4384s]
-06/11/23 19:10:32| INFO mul_cc finished [took 134.1449s]
-06/11/23 19:10:33| INFO atc_ne finished [took 115.0137s]
-06/11/23 19:10:33| INFO mul_pacc finished [took 173.4398s]
-06/11/23 19:10:35| INFO ref finished [took 127.6900s]
-06/11/23 19:10:35| INFO mulne_pacc finished [took 158.1989s]
-06/11/23 19:11:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00893) [took 181.2645s]
-06/11/23 19:12:28| INFO mul_pacc_gs finished [took 263.1619s]
-06/11/23 19:14:45| INFO bin_sld finished [took 432.8401s]
-06/11/23 19:14:48| INFO bin_pacc finished [took 430.1210s]
-06/11/23 19:14:54| INFO binmc_pacc finished [took 433.8715s]
-06/11/23 19:14:58| INFO bin_cc finished [took 405.7688s]
-06/11/23 19:14:59| INFO binne_pacc finished [took 435.7315s]
-06/11/23 19:15:29| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
-06/11/23 19:16:36| INFO bin_sld_gsq finished [took 539.4078s]
-06/11/23 19:17:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00831) [took 545.8362s]
-06/11/23 19:17:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00797) [took 609.7895s]
-06/11/23 19:18:32| INFO mul_sld_gs finished [took 657.1765s]
-06/11/23 19:20:08| INFO bin_pacc_gs finished [took 728.9184s]
-06/11/23 19:23:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00738) [took 966.8750s]
-06/11/23 19:26:42| INFO bin_sld_gs finished [took 1148.2428s]
-06/11/23 19:26:42| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 1152.4463s]
-06/11/23 19:26:43| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
-06/11/23 19:29:16| INFO mul_pacc finished [took 142.3375s]
-06/11/23 19:29:26| INFO doc_feat finished [took 92.0123s]
-06/11/23 19:29:29| INFO atc_ne finished [took 96.1697s]
-06/11/23 19:29:32| INFO mul_sld finished [took 164.7852s]
-06/11/23 19:29:33| INFO ref finished [took 114.3664s]
-06/11/23 19:29:36| INFO kfcv finished [took 118.4300s]
-06/11/23 19:29:37| INFO atc_mc finished [took 111.6950s]
-06/11/23 19:29:37| INFO mul_cc finished [took 127.8860s]
-06/11/23 19:29:39| INFO mulmc_pacc finished [took 162.5217s]
-06/11/23 19:29:46| INFO mulne_pacc finished [took 159.7535s]
-06/11/23 19:30:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.2267s]
-06/11/23 19:31:42| INFO mul_pacc_gs finished [took 263.2959s]
-06/11/23 19:33:48| INFO bin_pacc finished [took 415.7355s]
-06/11/23 19:33:49| INFO binne_pacc finished [took 411.7032s]
-06/11/23 19:33:49| INFO bin_sld finished [took 423.6935s]
-06/11/23 19:33:56| INFO binmc_pacc finished [took 422.0731s]
-06/11/23 19:34:02| INFO bin_cc finished [took 394.8074s]
-06/11/23 19:34:45| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
-06/11/23 19:35:33| INFO bin_sld_gsq finished [took 523.6794s]
-06/11/23 19:36:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00651) [took 539.0149s]
-06/11/23 19:36:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00646) [took 605.4721s]
-06/11/23 19:37:37| INFO mul_sld_gs finished [took 647.9998s]
-06/11/23 19:39:13| INFO bin_pacc_gs finished [took 722.3065s]
-06/11/23 19:42:14| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00635) [took 926.2548s]
-06/11/23 19:45:13| INFO bin_sld_gs finished [took 1105.8303s]
-06/11/23 19:45:13| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 1110.5345s]
-06/11/23 19:45:13| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
-06/11/23 19:47:55| INFO mul_pacc finished [took 151.2717s]
-06/11/23 19:48:01| INFO mul_sld finished [took 164.7303s]
-06/11/23 19:48:02| INFO doc_feat finished [took 95.7218s]
-06/11/23 19:48:20| INFO kfcv finished [took 132.6414s]
-06/11/23 19:48:26| INFO ref finished [took 136.4855s]
-06/11/23 19:48:27| INFO mulmc_pacc finished [took 180.2510s]
-06/11/23 19:48:30| INFO mulne_pacc finished [took 173.6996s]
-06/11/23 19:48:33| INFO atc_mc finished [took 135.5939s]
-06/11/23 19:48:34| INFO atc_ne finished [took 129.3719s]
-06/11/23 19:48:35| INFO mul_cc finished [took 153.9587s]
-06/11/23 19:48:47| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00782) [took 177.0918s]
-06/11/23 19:50:13| INFO mul_pacc_gs finished [took 262.7047s]
-06/11/23 19:52:34| INFO bin_pacc finished [took 431.9695s]
-06/11/23 19:52:36| INFO binmc_pacc finished [took 430.1566s]
-06/11/23 19:52:43| INFO bin_sld finished [took 446.4452s]
-06/11/23 19:52:44| INFO bin_cc finished [took 407.8850s]
-06/11/23 19:52:47| INFO binne_pacc finished [took 438.4423s]
-06/11/23 19:53:19| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
-06/11/23 19:54:09| INFO bin_sld_gsq finished [took 528.9254s]
-06/11/23 19:54:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00669) [took 545.8164s]
-06/11/23 19:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00814) [took 619.0258s]
-06/11/23 19:56:21| INFO mul_sld_gs finished [took 661.4303s]
-06/11/23 19:57:51| INFO bin_pacc_gs finished [took 733.3970s]
-06/11/23 20:00:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00795) [took 935.9973s]
-06/11/23 20:03:55| INFO bin_sld_gs finished [took 1117.3981s]
-06/11/23 20:03:55| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 1121.8060s]
-06/11/23 20:03:55| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
-06/11/23 20:06:27| INFO mul_sld finished [took 147.0727s]
-06/11/23 20:06:30| INFO doc_feat finished [took 81.1117s]
-06/11/23 20:06:48| INFO mul_pacc finished [took 162.2312s]
-06/11/23 20:07:04| INFO kfcv finished [took 133.4389s]
-06/11/23 20:07:04| INFO ref finished [took 132.6728s]
-06/11/23 20:07:05| INFO mulne_pacc finished [took 171.0782s]
-06/11/23 20:07:08| INFO mulmc_pacc finished [took 179.6909s]
-06/11/23 20:07:10| INFO atc_mc finished [took 130.5941s]
-06/11/23 20:07:14| INFO mul_cc finished [took 150.3795s]
-06/11/23 20:07:15| INFO atc_ne finished [took 131.0309s]
-06/11/23 20:07:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00813) [took 177.7289s]
-06/11/23 20:08:49| INFO mul_pacc_gs finished [took 257.9675s]
-06/11/23 20:10:44| INFO bin_pacc finished [took 399.4800s]
-06/11/23 21:01:51| INFO bin_pacc_gs finished [took 3446.1854s]
-06/11/23 21:03:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00684) [took 3563.0699s]
-06/11/23 21:04:07| INFO mul_sld_gs finished [took 3606.0194s]
-06/11/23 21:08:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00519) [took 3863.9570s]
-06/11/23 21:11:26| INFO bin_sld_gs finished [took 4046.4500s]
-06/11/23 21:11:26| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 4051.2016s]
-06/11/23 21:11:26| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
-06/11/23 21:11:31| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:32| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:34| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:35| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
-06/11/23 21:11:36| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:38| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 21:11:38| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:40| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 21:11:40| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:42| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 21:11:42| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:11:44| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 21:11:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 21:12:27| INFO mul_sld finished [took 56.8958s]
-06/11/23 21:12:32| INFO ref finished [took 44.3311s]
-06/11/23 21:12:32| INFO doc_feat finished [took 41.1551s]
-06/11/23 21:12:33| INFO kfcv finished [took 46.1873s]
-06/11/23 21:12:36| INFO atc_mc finished [took 47.9541s]
-06/11/23 21:12:37| INFO mul_cc finished [took 51.8838s]
-06/11/23 21:12:37| INFO atc_ne finished [took 47.4962s]
-06/11/23 21:16:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00843) [took 312.8612s]
-06/11/23 21:17:24| INFO mul_sld_gs finished [took 351.5693s]
-06/11/23 21:17:24| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 357.7321s]
-06/11/23 21:20:10| INFO dataset rcv1_MCAT_9prevs
-06/11/23 21:20:18| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
-06/11/23 21:23:12| INFO doc_feat finished [took 81.2849s]
-06/11/23 21:23:21| INFO mul_pacc finished [took 168.3242s]
-06/11/23 21:23:30| INFO mulmc_pacc finished [took 173.2730s]
-06/11/23 21:23:35| INFO atc_mc finished [took 115.3803s]
-06/11/23 21:23:41| INFO ref finished [took 125.5611s]
-06/11/23 21:23:41| INFO kfcv finished [took 136.3040s]
-06/11/23 21:23:51| INFO mulne_pacc finished [took 185.3346s]
-06/11/23 21:23:58| INFO atc_ne finished [took 129.7752s]
-06/11/23 21:23:59| INFO mul_cc finished [took 164.3501s]
-06/11/23 21:24:26| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.02036) [took 203.9839s]
-06/11/23 21:24:32| INFO mul_sld finished [took 249.6979s]
-06/11/23 21:25:50| INFO mul_pacc_gs finished [took 287.7634s]
-06/11/23 21:28:08| INFO binne_pacc finished [took 443.1314s]
-06/11/23 21:28:11| INFO bin_cc finished [took 427.7416s]
-06/11/23 21:28:26| INFO bin_pacc finished [took 475.7859s]
-06/11/23 21:28:28| INFO binmc_pacc finished [took 472.2702s]
-06/11/23 21:28:33| INFO bin_sld finished [took 492.0457s]
-06/11/23 21:29:19| INFO mul_sld_gsq finished [took 529.8190s]
-06/11/23 21:29:26| INFO bin_sld_gsq finished [took 539.2552s]
-06/11/23 21:30:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00591) [took 573.3773s]
-06/11/23 21:31:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00754) [took 661.4704s]
-06/11/23 21:32:10| INFO mul_sld_gs finished [took 704.6441s]
-06/11/23 21:33:40| INFO bin_pacc_gs finished [took 763.3541s]
-06/11/23 21:36:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00760) [took 965.4559s]
-06/11/23 21:39:31| INFO bin_sld_gs finished [took 1146.5622s]
-06/11/23 21:39:31| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 1152.1700s]
-06/11/23 21:39:31| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
-06/11/23 21:42:13| INFO doc_feat finished [took 88.9970s]
-06/11/23 21:42:24| INFO mul_pacc finished [took 161.9999s]
-06/11/23 21:42:31| INFO mulmc_pacc finished [took 159.0109s]
-06/11/23 21:42:34| INFO mul_sld finished [took 179.5397s]
-06/11/23 21:42:42| INFO kfcv finished [took 138.3784s]
-06/11/23 21:42:42| INFO atc_mc finished [took 127.5150s]
-06/11/23 21:42:45| INFO ref finished [took 133.9163s]
-06/11/23 21:42:48| INFO mulne_pacc finished [took 170.3191s]
-06/11/23 21:42:53| INFO mul_cc finished [took 153.9952s]
-06/11/23 21:42:57| INFO atc_ne finished [took 133.9857s]
-06/11/23 21:43:07| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01406) [took 179.2817s]
-06/11/23 21:44:27| INFO mul_pacc_gs finished [took 259.4430s]
-06/11/23 21:46:57| INFO bin_pacc finished [took 435.9586s]
-06/11/23 21:47:02| INFO binmc_pacc finished [took 436.7170s]
-06/11/23 21:47:02| INFO bin_sld finished [took 448.6901s]
-06/11/23 21:47:03| INFO binne_pacc finished [took 430.3933s]
-06/11/23 21:47:06| INFO bin_cc finished [took 413.3717s]
-06/11/23 21:47:44| INFO mul_sld_gsq finished [took 485.8565s]
-06/11/23 21:48:40| INFO bin_sld_gsq finished [took 542.6385s]
-06/11/23 21:49:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01029) [took 558.1111s]
-06/11/23 21:49:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00862) [took 617.7204s]
-06/11/23 21:50:38| INFO mul_sld_gs finished [took 661.3619s]
-06/11/23 21:52:31| INFO bin_pacc_gs finished [took 747.8605s]
-06/11/23 21:55:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00631) [took 947.6305s]
-06/11/23 21:58:25| INFO bin_sld_gs finished [took 1128.9705s]
-06/11/23 21:58:25| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 1133.8038s]
-06/11/23 21:58:25| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
-06/11/23 22:01:11| INFO doc_feat finished [took 91.6284s]
-06/11/23 22:01:13| INFO mul_pacc finished [took 157.8979s]
-06/11/23 22:01:21| INFO ref finished [took 117.5064s]
-06/11/23 22:01:29| INFO mulmc_pacc finished [took 171.3367s]
-06/11/23 22:01:34| INFO kfcv finished [took 138.8623s]
-06/11/23 22:01:44| INFO atc_ne finished [took 127.4515s]
-06/11/23 22:01:45| INFO mulne_pacc finished [took 175.7659s]
-06/11/23 22:01:45| INFO atc_mc finished [took 134.5717s]
-06/11/23 22:01:47| INFO mul_sld finished [took 198.7132s]
-06/11/23 22:01:53| INFO mul_cc finished [took 156.7010s]
-06/11/23 22:01:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00920) [took 169.8061s]
-06/11/23 22:03:15| INFO mul_pacc_gs finished [took 248.7885s]
-06/11/23 22:05:47| INFO bin_pacc finished [took 433.9454s]
-06/11/23 22:05:52| INFO binmc_pacc finished [took 435.7566s]
-06/11/23 22:05:55| INFO binne_pacc finished [took 432.5216s]
-06/11/23 22:06:02| INFO bin_sld finished [took 455.4425s]
-06/11/23 22:06:03| INFO bin_cc finished [took 409.9712s]
-06/11/23 22:06:43| INFO mul_sld_gsq finished [took 490.7571s]
-06/11/23 22:07:34| INFO bin_sld_gsq finished [took 542.4371s]
-06/11/23 22:08:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00585) [took 557.7911s]
-06/11/23 22:08:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 598.8338s]
-06/11/23 22:09:12| INFO mul_sld_gs finished [took 641.4050s]
-06/11/23 22:11:15| INFO bin_pacc_gs finished [took 742.8423s]
-06/11/23 22:14:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00443) [took 940.7448s]
-06/11/23 22:17:12| INFO bin_sld_gs finished [took 1122.5660s]
-06/11/23 22:17:12| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 1126.9865s]
-06/11/23 22:17:12| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
-06/11/23 22:19:32| INFO ref finished [took 85.6333s]
-06/11/23 22:19:43| INFO mulmc_pacc finished [took 138.3833s]
-06/11/23 22:19:44| INFO doc_feat finished [took 84.2844s]
-06/11/23 22:19:54| INFO atc_ne finished [took 99.6744s]
-06/11/23 22:19:57| INFO kfcv finished [took 114.5018s]
-06/11/23 22:19:59| INFO mul_cc finished [took 123.4161s]
-06/11/23 22:20:05| INFO mul_pacc finished [took 163.4607s]
-06/11/23 22:20:09| INFO mul_sld finished [took 173.7721s]
-06/11/23 22:20:16| INFO mulne_pacc finished [took 162.8502s]
-06/11/23 22:20:16| INFO atc_mc finished [took 124.1504s]
-06/11/23 22:20:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00596) [took 169.9575s]
-06/11/23 22:21:55| INFO mul_pacc_gs finished [took 248.8139s]
-06/11/23 22:24:04| INFO binmc_pacc finished [took 400.7570s]
-06/11/23 22:24:12| INFO bin_pacc finished [took 411.2454s]
-06/11/23 22:24:21| INFO binne_pacc finished [took 414.5496s]
-06/11/23 22:24:21| INFO bin_cc finished [took 389.2880s]
-06/11/23 22:24:25| INFO bin_sld finished [took 431.6256s]
-06/11/23 22:25:13| INFO mul_sld_gsq finished [took 474.0621s]
-06/11/23 22:25:54| INFO bin_sld_gsq finished [took 515.9435s]
-06/11/23 22:26:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00626) [took 539.2315s]
-06/11/23 22:27:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00612) [took 594.2222s]
-06/11/23 22:27:54| INFO mul_sld_gs finished [took 637.0683s]
-06/11/23 22:29:48| INFO bin_pacc_gs finished [took 725.8952s]
-06/11/23 22:33:01| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00682) [took 945.7122s]
-06/11/23 22:36:02| INFO bin_sld_gs finished [took 1126.7133s]
-06/11/23 22:36:02| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 1130.5566s]
-06/11/23 22:36:02| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
-06/11/23 22:38:42| INFO doc_feat finished [took 76.3995s]
-06/11/23 22:39:04| INFO mul_pacc finished [took 170.8108s]
-06/11/23 22:39:11| INFO mulmc_pacc finished [took 169.1537s]
-06/11/23 22:39:22| INFO ref finished [took 134.5551s]
-06/11/23 22:39:23| INFO kfcv finished [took 144.5049s]
-06/11/23 22:39:28| INFO mul_sld finished [took 201.7112s]
-06/11/23 22:39:31| INFO atc_ne finished [took 127.5871s]
-06/11/23 22:39:32| INFO atc_mc finished [took 141.1615s]
-06/11/23 22:39:33| INFO mulne_pacc finished [took 181.7155s]
-06/11/23 22:39:34| INFO mul_cc finished [took 156.9505s]
-06/11/23 22:39:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00848) [took 178.6463s]
-06/11/23 22:41:02| INFO mul_pacc_gs finished [took 264.1109s]
-06/11/23 22:43:34| INFO binmc_pacc finished [took 438.9742s]
-06/11/23 22:43:34| INFO bin_pacc finished [took 442.7005s]
-06/11/23 22:43:43| INFO bin_sld finished [took 458.4940s]
-06/11/23 22:43:44| INFO binne_pacc finished [took 443.0455s]
-06/11/23 22:43:55| INFO bin_cc finished [took 423.6361s]
-06/11/23 22:44:45| INFO mul_sld_gsq finished [took 514.4586s]
-06/11/23 22:45:32| INFO bin_sld_gsq finished [took 562.7681s]
-06/11/23 22:46:12| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00790) [took 574.1156s]
-06/11/23 22:46:42| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00824) [took 633.5645s]
-06/11/23 22:47:24| INFO mul_sld_gs finished [took 676.3552s]
-06/11/23 22:49:27| INFO bin_pacc_gs finished [took 768.3574s]
-06/11/23 22:52:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00861) [took 979.5729s]
-06/11/23 22:55:32| INFO bin_sld_gs finished [took 1164.7331s]
-06/11/23 22:55:32| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 1169.2748s]
-06/11/23 22:55:32| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
-06/11/23 22:58:47| INFO doc_feat finished [took 112.6375s]
-06/11/23 22:59:00| INFO kfcv finished [took 150.2412s]
-06/11/23 22:59:00| INFO mul_pacc finished [took 197.0521s]
-06/11/23 22:59:06| INFO mul_sld finished [took 209.9482s]
-06/11/23 22:59:07| INFO mulmc_pacc finished [took 198.8911s]
-06/11/23 22:59:07| INFO ref finished [took 148.7702s]
-06/11/23 22:59:16| INFO atc_ne finished [took 143.7730s]
-06/11/23 22:59:18| INFO atc_mc finished [took 151.2783s]
-06/11/23 22:59:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01122) [took 190.1694s]
-06/11/23 22:59:26| INFO mul_cc finished [took 179.0100s]
-06/11/23 22:59:33| INFO mulne_pacc finished [took 211.9002s]
-06/11/23 23:00:52| INFO mul_pacc_gs finished [took 283.5718s]
-06/11/23 23:03:21| INFO bin_sld finished [took 466.9682s]
-06/11/23 23:03:24| INFO binmc_pacc finished [took 456.9500s]
-06/11/23 23:03:25| INFO bin_pacc finished [took 464.1421s]
-06/11/23 23:03:39| INFO bin_cc finished [took 445.8302s]
-06/11/23 23:03:40| INFO binne_pacc finished [took 466.3427s]
-06/11/23 23:04:10| INFO mul_sld_gsq finished [took 509.0584s]
-06/11/23 23:04:56| INFO bin_sld_gsq finished [took 556.7578s]
-06/11/23 23:05:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01033) [took 581.0899s]
-06/11/23 23:06:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00791) [took 636.6955s]
-06/11/23 23:07:00| INFO mul_sld_gs finished [took 682.1829s]
-06/11/23 23:08:59| INFO bin_pacc_gs finished [took 772.0584s]
-06/11/23 23:11:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00722) [took 966.7367s]
-06/11/23 23:14:47| INFO bin_sld_gs finished [took 1150.2138s]
-06/11/23 23:14:47| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 1155.4582s]
-06/11/23 23:14:47| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
-06/11/23 23:17:29| INFO mulmc_pacc finished [took 140.6592s]
-06/11/23 23:17:37| INFO doc_feat finished [took 93.5374s]
-06/11/23 23:17:58| INFO mul_pacc finished [took 176.1101s]
-06/11/23 23:18:06| INFO mulne_pacc finished [took 168.2578s]
-06/11/23 23:18:06| INFO ref finished [took 138.9670s]
-06/11/23 23:18:13| INFO atc_ne finished [took 133.8368s]
-06/11/23 23:18:13| INFO mul_cc finished [took 156.3809s]
-06/11/23 23:18:14| INFO atc_mc finished [took 140.7865s]
-06/11/23 23:18:15| INFO kfcv finished [took 150.8563s]
-06/11/23 23:18:28| INFO mul_sld finished [took 213.5502s]
-06/11/23 23:18:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00696) [took 184.7202s]
-06/11/23 23:20:04| INFO mul_pacc_gs finished [took 271.8620s]
-06/11/23 23:22:38| INFO binne_pacc finished [took 444.7274s]
-06/11/23 23:22:39| INFO binmc_pacc finished [took 454.8866s]
-06/11/23 23:22:39| INFO bin_pacc finished [took 458.6381s]
-06/11/23 23:22:47| INFO bin_cc finished [took 432.1075s]
-06/11/23 23:22:54| INFO bin_sld finished [took 480.5003s]
-06/11/23 23:23:33| INFO mul_sld_gsq finished [took 514.0066s]
-06/11/23 23:24:13| INFO bin_sld_gsq finished [took 554.7885s]
-06/11/23 23:24:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00603) [took 574.6463s]
-06/11/23 23:25:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00528) [took 609.3079s]
-06/11/23 23:25:51| INFO mul_sld_gs finished [took 654.2885s]
-06/11/23 23:28:10| INFO bin_pacc_gs finished [took 767.8253s]
-06/11/23 23:30:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00733) [took 947.2105s]
-06/11/23 23:33:48| INFO bin_sld_gs finished [took 1132.1309s]
-06/11/23 23:33:48| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 1140.6743s]
-06/11/23 23:33:48| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
-06/11/23 23:36:55| INFO doc_feat finished [took 101.6311s]
-06/11/23 23:37:16| INFO atc_ne finished [took 124.5854s]
-06/11/23 23:37:39| INFO mulne_pacc finished [took 198.5060s]
-06/11/23 23:37:42| INFO mulmc_pacc finished [took 210.8408s]
-06/11/23 23:37:43| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01019) [took 194.4422s]
-06/11/23 23:37:44| INFO mul_pacc finished [took 224.0155s]
-06/11/23 23:37:44| INFO kfcv finished [took 178.0222s]
-06/11/23 23:37:47| INFO ref finished [took 176.1278s]
-06/11/23 23:37:55| INFO atc_mc finished [took 173.0154s]
-06/11/23 23:37:58| INFO mul_cc finished [took 198.1420s]
-06/11/23 23:38:10| INFO mul_sld finished [took 258.4898s]
-06/11/23 23:39:25| INFO mul_pacc_gs finished [took 297.0552s]
-06/11/23 23:41:55| INFO binmc_pacc finished [took 471.8397s]
-06/11/23 23:42:06| INFO binne_pacc finished [took 470.6917s]
-06/11/23 23:42:08| INFO bin_pacc finished [took 490.2025s]
-06/11/23 23:42:11| INFO bin_sld finished [took 500.3974s]
-06/11/23 23:42:17| INFO bin_cc finished [took 463.2719s]
-06/11/23 23:42:33| INFO mul_sld_gsq finished [took 515.9211s]
-06/11/23 23:43:19| INFO bin_sld_gsq finished [took 563.2792s]
-06/11/23 23:44:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01110) [took 580.7011s]
-06/11/23 23:44:33| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00755) [took 638.9055s]
-06/11/23 23:45:18| INFO mul_sld_gs finished [took 683.7473s]
-06/11/23 23:47:14| INFO bin_pacc_gs finished [took 769.5136s]
-06/11/23 23:50:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00653) [took 986.1331s]
-06/11/23 23:53:23| INFO bin_sld_gs finished [took 1170.3407s]
-06/11/23 23:53:23| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 1175.4004s]
-06/11/23 23:53:23| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
-06/11/23 23:53:29| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:31| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:32| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:34| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
-06/11/23 23:53:34| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:36| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 23:53:37| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:38| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:39| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 23:53:41| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 23:53:41| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:53:43| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
-06/11/23 23:53:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-06/11/23 23:54:33| INFO ref finished [took 46.5615s]
-06/11/23 23:54:34| INFO doc_feat finished [took 43.4254s]
-06/11/23 23:54:34| INFO kfcv finished [took 48.7260s]
-06/11/23 23:54:34| INFO mul_sld finished [took 64.5496s]
-06/11/23 23:54:38| INFO atc_mc finished [took 49.9172s]
-06/11/23 23:54:39| INFO atc_ne finished [took 49.8635s]
-06/11/23 23:54:39| INFO mul_cc finished [took 54.7417s]
-06/11/23 23:58:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01247) [took 295.7388s]
-06/11/23 23:59:08| INFO mul_sld_gs finished [took 336.2009s]
-06/11/23 23:59:08| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 344.1389s]
-----------------------------------------------------------------------------------------------------
-07/11/23 01:05:25| INFO dataset rcv1_CCAT_9prevs
-07/11/23 01:05:30| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
-07/11/23 01:06:23| INFO ref finished [took 48.3560s]
-07/11/23 01:06:29| INFO atc_mc finished [took 52.9929s]
-07/11/23 01:06:30| INFO atc_ne finished [took 53.3908s]
-07/11/23 01:07:06| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-07/11/23 01:11:38| INFO mul_sld_gsq finished [took 364.0698s]
-07/11/23 01:13:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 499.4945s]
-07/11/23 01:14:34| INFO mul_sld_gs finished [took 542.6047s]
-07/11/23 01:18:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 750.8663s]
-07/11/23 01:21:01| INFO bin_sld_gs finished [took 930.1356s]
-07/11/23 01:21:01| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 931.4321s]
-07/11/23 01:21:01| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
-07/11/23 01:22:02| INFO ref finished [took 55.2212s]
-07/11/23 01:22:07| INFO atc_mc finished [took 59.3890s]
-07/11/23 01:22:09| INFO atc_ne finished [took 59.7388s]
-07/11/23 01:27:21| INFO mul_sld_gsq finished [took 375.2352s]
-07/11/23 01:27:24| INFO bin_sld_gsq finished [took 379.6159s]
-07/11/23 01:29:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 502.0302s]
-07/11/23 01:30:08| INFO mul_sld_gs finished [took 545.0285s]
-07/11/23 01:34:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 802.3620s]
-07/11/23 01:37:25| INFO bin_sld_gs finished [took 982.3260s]
-07/11/23 01:37:25| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 983.7236s]
-07/11/23 01:37:25| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
-07/11/23 01:38:20| INFO ref finished [took 49.9803s]
-07/11/23 01:38:25| INFO atc_mc finished [took 53.3765s]
-07/11/23 01:38:26| INFO atc_ne finished [took 53.8925s]
-07/11/23 01:43:41| INFO mul_sld_gsq finished [took 372.2608s]
-07/11/23 01:43:45| INFO bin_sld_gsq finished [took 377.3380s]
-07/11/23 01:45:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 497.5768s]
-07/11/23 01:46:28| INFO mul_sld_gs finished [took 540.8267s]
-07/11/23 01:51:09| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 822.2849s]
-07/11/23 01:54:10| INFO bin_sld_gs finished [took 1003.7804s]
-07/11/23 01:54:10| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1005.2506s]
-07/11/23 01:54:10| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
-07/11/23 01:55:05| INFO ref finished [took 49.8884s]
-07/11/23 01:55:09| INFO atc_mc finished [took 53.3594s]
-07/11/23 01:55:10| INFO atc_ne finished [took 53.5162s]
-07/11/23 02:00:25| INFO mul_sld_gsq finished [took 371.4460s]
-07/11/23 02:00:41| INFO bin_sld_gsq finished [took 387.6183s]
-07/11/23 02:02:30| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 498.0096s]
-07/11/23 02:03:11| INFO mul_sld_gs finished [took 539.1531s]
-07/11/23 02:07:53| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 821.8730s]
-07/11/23 02:10:52| INFO bin_sld_gs finished [took 1001.0803s]
-07/11/23 02:10:52| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1002.3085s]
-07/11/23 02:10:52| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
-07/11/23 02:11:44| INFO ref finished [took 47.2218s]
-07/11/23 02:11:48| INFO atc_mc finished [took 49.6349s]
-07/11/23 02:11:50| INFO atc_ne finished [took 50.9082s]
-07/11/23 02:16:51| INFO mul_sld_gsq finished [took 354.3706s]
-07/11/23 02:17:11| INFO bin_sld_gsq finished [took 376.0124s]
-07/11/23 02:18:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 476.0587s]
-07/11/23 02:19:33| INFO mul_sld_gs finished [took 518.5692s]
-07/11/23 02:24:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 803.4978s]
-07/11/23 02:27:16| INFO bin_sld_gs finished [took 982.4395s]
-07/11/23 02:27:16| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 983.7838s]
-07/11/23 02:27:16| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
-07/11/23 02:28:08| INFO ref finished [took 46.6191s]
-07/11/23 02:28:13| INFO atc_mc finished [took 50.3543s]
-07/11/23 02:28:15| INFO atc_ne finished [took 51.6601s]
-07/11/23 02:33:15| INFO mul_sld_gsq finished [took 354.6014s]
-07/11/23 02:33:34| INFO bin_sld_gsq finished [took 374.7872s]
-07/11/23 02:35:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 475.9302s]
-07/11/23 02:35:57| INFO mul_sld_gs finished [took 518.5425s]
-07/11/23 02:40:20| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 782.7268s]
-07/11/23 02:43:18| INFO bin_sld_gs finished [took 960.6334s]
-07/11/23 02:43:18| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 961.9030s]
-07/11/23 02:43:18| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
-07/11/23 02:44:10| INFO ref finished [took 47.1234s]
-07/11/23 02:44:14| INFO atc_mc finished [took 49.9871s]
-07/11/23 02:44:16| INFO atc_ne finished [took 50.9160s]
-07/11/23 02:49:19| INFO mul_sld_gsq finished [took 357.0613s]
-07/11/23 02:49:30| INFO bin_sld_gsq finished [took 368.8000s]
-07/11/23 02:51:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 475.7332s]
-07/11/23 02:51:59| INFO mul_sld_gs finished [took 518.6671s]
-07/11/23 02:56:28| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 788.7117s]
-07/11/23 02:59:28| INFO bin_sld_gs finished [took 968.7653s]
-07/11/23 02:59:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 970.1516s]
-07/11/23 02:59:28| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
-07/11/23 03:00:20| INFO ref finished [took 46.9898s]
-07/11/23 03:00:24| INFO atc_mc finished [took 49.8768s]
-07/11/23 03:00:25| INFO atc_ne finished [took 49.6324s]
-07/11/23 03:05:23| INFO mul_sld_gsq finished [took 350.7932s]
-07/11/23 03:05:32| INFO bin_sld_gsq finished [took 360.8665s]
-07/11/23 03:07:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 474.6581s]
-07/11/23 03:08:07| INFO mul_sld_gs finished [took 516.4890s]
-07/11/23 03:12:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 774.9140s]
-07/11/23 03:15:29| INFO bin_sld_gs finished [took 959.3579s]
-07/11/23 03:15:29| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 960.6992s]
-07/11/23 03:15:29| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
-07/11/23 03:16:21| INFO ref finished [took 47.3281s]
-07/11/23 03:16:25| INFO atc_mc finished [took 49.8016s]
-07/11/23 03:16:28| INFO atc_ne finished [took 51.2288s]
-07/11/23 03:21:16| INFO mul_sld_gsq finished [took 343.2861s]
-07/11/23 03:21:22| INFO bin_sld_gsq finished [took 349.6065s]
-07/11/23 03:23:20| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 468.7910s]
-07/11/23 03:24:01| INFO mul_sld_gs finished [took 509.9001s]
-07/11/23 03:28:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 752.8185s]
-07/11/23 03:31:01| INFO bin_sld_gs finished [took 930.3934s]
-07/11/23 03:31:01| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 931.7055s]
-07/11/23 03:31:29| INFO dataset imdb_9prevs
-07/11/23 03:31:37| INFO Dataset sample 0.10 of dataset imdb_9prevs started
-07/11/23 03:31:49| INFO ref finished [took 11.4117s]
-07/11/23 03:31:53| INFO atc_mc finished [took 14.8218s]
-07/11/23 03:31:53| INFO atc_ne finished [took 14.8359s]
-07/11/23 03:32:11| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-07/11/23 03:32:56| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
-07/11/23 03:36:32| INFO mul_sld_gsq finished [took 294.6812s]
-07/11/23 03:38:05| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 387.7698s]
-07/11/23 03:38:18| INFO mul_sld_gs finished [took 400.7660s]
-07/11/23 03:38:18| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 401.3208s]
-07/11/23 03:38:18| INFO Dataset sample 0.20 of dataset imdb_9prevs started
-07/11/23 03:38:30| INFO ref finished [took 11.1665s]
-07/11/23 03:38:34| INFO atc_mc finished [took 14.4483s]
-07/11/23 03:38:34| INFO atc_ne finished [took 14.8634s]
-07/11/23 03:43:16| INFO bin_sld_gsq finished [took 296.8786s]
-07/11/23 03:43:32| INFO mul_sld_gsq finished [took 312.4588s]
-07/11/23 03:45:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 445.1331s]
-07/11/23 03:45:58| INFO mul_sld_gs finished [took 459.5855s]
-07/11/23 03:51:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 766.1528s]
-07/11/23 03:53:40| INFO bin_sld_gs finished [took 921.5996s]
-07/11/23 03:53:40| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 922.0949s]
-07/11/23 03:53:40| INFO Dataset sample 0.30 of dataset imdb_9prevs started
-07/11/23 03:53:53| INFO ref finished [took 11.5825s]
-07/11/23 03:53:57| INFO atc_mc finished [took 14.8590s]
-07/11/23 03:53:57| INFO atc_ne finished [took 15.3090s]
-07/11/23 03:58:53| INFO mul_sld_gsq finished [took 311.9891s]
-07/11/23 03:58:54| INFO bin_sld_gsq finished [took 313.1182s]
-07/11/23 04:01:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 441.3198s]
-07/11/23 04:01:18| INFO mul_sld_gs finished [took 456.2347s]
-07/11/23 04:06:06| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 745.0596s]
-07/11/23 04:08:40| INFO bin_sld_gs finished [took 898.9046s]
-07/11/23 04:08:40| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 899.6778s]
-07/11/23 04:08:40| INFO Dataset sample 0.40 of dataset imdb_9prevs started
-07/11/23 04:08:52| INFO ref finished [took 11.0605s]
-07/11/23 04:08:56| INFO atc_mc finished [took 14.9590s]
-07/11/23 04:08:56| INFO atc_ne finished [took 14.8804s]
-07/11/23 04:13:54| INFO mul_sld_gsq finished [took 313.3797s]
-07/11/23 04:13:56| INFO bin_sld_gsq finished [took 315.5862s]
-07/11/23 04:15:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 432.9025s]
-07/11/23 04:16:08| INFO mul_sld_gs finished [took 447.1098s]
-07/11/23 04:21:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 764.2230s]
-07/11/23 04:23:56| INFO bin_sld_gs finished [took 915.4905s]
-07/11/23 04:23:56| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 916.1187s]
-07/11/23 04:23:56| INFO Dataset sample 0.50 of dataset imdb_9prevs started
-07/11/23 04:24:08| INFO ref finished [took 10.9214s]
-07/11/23 04:24:12| INFO atc_mc finished [took 14.9236s]
-07/11/23 04:24:12| INFO atc_ne finished [took 14.9240s]
-07/11/23 04:29:11| INFO bin_sld_gsq finished [took 314.3071s]
-07/11/23 04:29:19| INFO mul_sld_gsq finished [took 322.1027s]
-07/11/23 04:31:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 448.0202s]
-07/11/23 04:31:40| INFO mul_sld_gs finished [took 463.2243s]
-07/11/23 04:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 746.2797s]
-07/11/23 04:38:55| INFO bin_sld_gs finished [took 898.7899s]
-07/11/23 04:38:55| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 899.2924s]
-07/11/23 04:38:55| INFO Dataset sample 0.60 of dataset imdb_9prevs started
-07/11/23 04:39:08| INFO ref finished [took 11.9811s]
-07/11/23 04:39:12| INFO atc_mc finished [took 15.7159s]
-07/11/23 04:39:12| INFO atc_ne finished [took 15.9512s]
-07/11/23 04:44:19| INFO bin_sld_gsq finished [took 323.1420s]
-07/11/23 04:44:21| INFO mul_sld_gsq finished [took 325.2299s]
-07/11/23 04:46:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 445.8872s]
-07/11/23 04:46:37| INFO mul_sld_gs finished [took 460.6339s]
-07/11/23 04:52:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 786.7500s]
-07/11/23 04:54:36| INFO bin_sld_gs finished [took 940.1627s]
-07/11/23 04:54:36| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 940.6023s]
-07/11/23 04:54:36| INFO Dataset sample 0.70 of dataset imdb_9prevs started
-07/11/23 04:54:48| INFO ref finished [took 11.1744s]
-07/11/23 04:54:52| INFO atc_mc finished [took 14.7518s]
-07/11/23 04:54:52| INFO atc_ne finished [took 14.8147s]
-07/11/23 04:59:45| INFO bin_sld_gsq finished [took 308.3645s]
-07/11/23 05:00:07| INFO mul_sld_gsq finished [took 330.3332s]
-07/11/23 05:02:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 456.8448s]
-07/11/23 05:02:28| INFO mul_sld_gs finished [took 471.4675s]
-07/11/23 05:06:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 731.2847s]
-07/11/23 05:09:19| INFO bin_sld_gs finished [took 882.2200s]
-07/11/23 05:09:19| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 882.8165s]
-07/11/23 05:09:19| INFO Dataset sample 0.80 of dataset imdb_9prevs started
-07/11/23 05:09:31| INFO ref finished [took 11.0645s]
-07/11/23 05:09:35| INFO atc_mc finished [took 14.7375s]
-07/11/23 05:09:35| INFO atc_ne finished [took 14.7704s]
-07/11/23 05:14:22| INFO bin_sld_gsq finished [took 302.1848s]
-07/11/23 05:14:33| INFO mul_sld_gsq finished [took 313.5459s]
-07/11/23 05:16:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 438.9863s]
-07/11/23 05:16:52| INFO mul_sld_gs finished [took 452.7273s]
-07/11/23 05:21:59| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 759.8355s]
-07/11/23 05:24:38| INFO bin_sld_gs finished [took 918.7338s]
-07/11/23 05:24:38| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 919.2981s]
-07/11/23 05:24:38| INFO Dataset sample 0.90 of dataset imdb_9prevs started
-07/11/23 05:24:39| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-07/11/23 05:24:39| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
-07/11/23 05:24:48| INFO ref finished [took 9.1378s]
-07/11/23 05:24:51| INFO atc_mc finished [took 12.1603s]
-07/11/23 05:24:52| INFO atc_ne finished [took 12.3482s]
-07/11/23 05:25:08| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
-07/11/23 05:30:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 353.7904s]
-07/11/23 05:30:45| INFO mul_sld_gs finished [took 365.9283s]
-07/11/23 05:30:45| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 366.4930s]
-----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+30/10/23 14:14:05| INFO: dataset imdb
+----------------------------------------------------------------------------------------------------
+30/10/23 14:14:24| INFO: dataset imdb
+30/10/23 14:14:31| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 14:14:35| WARNING: Method ref failed. Exception: 'dict' object has no attribute 'Keys'
+30/10/23 14:14:35| WARNING: Method atc_mc failed. Exception: 'dict' object has no attribute 'Keys'
+30/10/23 14:14:35| WARNING: Method atc_ne failed. Exception: 'dict' object has no attribute 'Keys'
+30/10/23 14:14:42| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:14:52| WARNING: Method mul_sld failed. Exception: 'dict' object has no attribute 'Keys'
+30/10/23 14:14:52| INFO: Dataset sample 0.90 of dataset imdb finished [took 21.1198s]
+30/10/23 14:14:52| WARNING: Dataset sample 0.90 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 14:14:52| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
+30/10/23 14:14:52| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 14:16:15| INFO: dataset imdb
+30/10/23 14:16:22| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 14:16:34| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:16:36| INFO: ref finished [took 11.6636s]
+30/10/23 14:16:39| INFO: atc_mc finished [took 14.8672s]
+30/10/23 14:16:39| INFO: atc_ne finished [took 14.8614s]
+30/10/23 14:16:49| INFO: mul_sld finished [took 24.6212s]
+30/10/23 14:16:49| INFO: Dataset sample 0.90 of dataset imdb finished [took 26.7805s]
+30/10/23 14:16:49| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 14:17:02| INFO: ref finished [took 13.0129s]
+30/10/23 14:17:06| INFO: atc_mc finished [took 16.0277s]
+30/10/23 14:17:06| INFO: atc_ne finished [took 16.1381s]
+30/10/23 14:17:17| INFO: mul_sld finished [took 28.1917s]
+30/10/23 14:17:23| INFO: mul_sld_bcts finished [took 33.5628s]
+30/10/23 14:17:23| INFO: Dataset sample 0.80 of dataset imdb finished [took 34.3680s]
+30/10/23 14:17:23| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 14:17:36| INFO: ref finished [took 12.5930s]
+30/10/23 14:17:40| INFO: atc_mc finished [took 16.1461s]
+30/10/23 14:17:40| INFO: atc_ne finished [took 16.1788s]
+30/10/23 14:17:52| INFO: mul_sld finished [took 28.5367s]
+30/10/23 14:18:00| INFO: mul_sld_bcts finished [took 36.0452s]
+30/10/23 14:18:00| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.7488s]
+30/10/23 14:18:00| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 14:18:13| INFO: ref finished [took 12.3910s]
+30/10/23 14:18:17| INFO: atc_mc finished [took 15.8804s]
+30/10/23 14:18:17| INFO: atc_ne finished [took 15.7115s]
+30/10/23 14:18:32| INFO: mul_sld_bcts finished [took 31.9997s]
+30/10/23 14:18:34| INFO: mul_sld finished [took 33.3735s]
+30/10/23 14:18:34| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.9557s]
+30/10/23 14:18:34| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 14:18:44| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:18:46| INFO: ref finished [took 11.7451s]
+30/10/23 14:18:50| INFO: atc_mc finished [took 15.2294s]
+30/10/23 14:18:50| INFO: atc_ne finished [took 15.1239s]
+30/10/23 14:18:55| INFO: mul_sld finished [took 21.3092s]
+30/10/23 14:18:55| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.7186s]
+30/10/23 14:18:55| ERROR: Configuration imdb_1prevs failed. Exception: 'mul_sld_bcts'
+30/10/23 14:18:55| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 14:32:36| INFO: dataset imdb
+30/10/23 14:32:43| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 14:32:56| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:32:58| INFO: ref finished [took 12.0197s]
+30/10/23 14:33:01| INFO: atc_mc finished [took 15.0884s]
+30/10/23 14:33:01| INFO: atc_ne finished [took 15.0503s]
+30/10/23 14:33:10| INFO: mul_sld finished [took 24.4470s]
+30/10/23 14:33:10| INFO: Dataset sample 0.90 of dataset imdb finished [took 26.6099s]
+30/10/23 14:33:10| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 14:33:23| INFO: ref finished [took 12.1812s]
+30/10/23 14:33:27| INFO: atc_mc finished [took 15.5589s]
+30/10/23 14:33:27| INFO: atc_ne finished [took 15.5283s]
+30/10/23 14:33:38| INFO: mul_sld finished [took 27.1282s]
+30/10/23 14:33:44| INFO: mul_sld_bcts finished [took 33.1098s]
+30/10/23 14:33:44| INFO: Dataset sample 0.80 of dataset imdb finished [took 33.9196s]
+30/10/23 14:33:44| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 14:33:57| INFO: ref finished [took 12.5959s]
+30/10/23 14:34:01| INFO: atc_mc finished [took 15.9389s]
+30/10/23 14:34:01| INFO: atc_ne finished [took 16.0795s]
+30/10/23 14:34:13| INFO: mul_sld finished [took 28.1568s]
+30/10/23 14:34:20| INFO: mul_sld_bcts finished [took 35.7147s]
+30/10/23 14:34:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.3828s]
+30/10/23 14:34:20| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 14:34:33| INFO: ref finished [took 12.2399s]
+30/10/23 14:34:37| INFO: atc_mc finished [took 15.4570s]
+30/10/23 14:34:37| INFO: atc_ne finished [took 15.5302s]
+30/10/23 14:34:52| INFO: mul_sld_bcts finished [took 31.1972s]
+30/10/23 14:34:54| INFO: mul_sld finished [took 32.9409s]
+30/10/23 14:34:54| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.5034s]
+30/10/23 14:34:54| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 14:35:04| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:35:06| INFO: ref finished [took 11.6742s]
+30/10/23 14:35:09| INFO: atc_mc finished [took 14.8324s]
+30/10/23 14:35:10| INFO: atc_ne finished [took 14.8661s]
+30/10/23 14:35:15| INFO: mul_sld finished [took 21.1356s]
+30/10/23 14:35:15| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.5814s]
+30/10/23 14:35:15| ERROR: Configuration imdb_1prevs failed. Exception: ('acc', None)
+30/10/23 14:35:15| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 14:37:47| INFO: dataset imdb
+30/10/23 14:37:54| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 14:38:07| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:38:09| INFO: ref finished [took 12.0443s]
+30/10/23 14:38:12| INFO: atc_mc finished [took 14.8929s]
+30/10/23 14:38:12| INFO: atc_ne finished [took 15.0431s]
+30/10/23 14:38:21| INFO: mul_sld finished [took 24.7987s]
+30/10/23 14:38:21| INFO: Dataset sample 0.90 of dataset imdb finished [took 27.0182s]
+30/10/23 14:38:21| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 14:38:35| INFO: ref finished [took 12.4504s]
+30/10/23 14:38:38| INFO: atc_mc finished [took 16.1560s]
+30/10/23 14:38:39| INFO: atc_ne finished [took 16.1785s]
+30/10/23 14:38:49| INFO: mul_sld finished [took 27.0617s]
+30/10/23 14:38:55| INFO: mul_sld_bcts finished [took 32.7384s]
+30/10/23 14:38:55| INFO: Dataset sample 0.80 of dataset imdb finished [took 33.5347s]
+30/10/23 14:38:55| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 14:39:08| INFO: ref finished [took 12.4381s]
+30/10/23 14:39:11| INFO: atc_mc finished [took 15.6709s]
+30/10/23 14:39:11| INFO: atc_ne finished [took 15.7319s]
+30/10/23 14:39:23| INFO: mul_sld finished [took 27.9301s]
+30/10/23 14:39:31| INFO: mul_sld_bcts finished [took 35.5094s]
+30/10/23 14:39:31| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.1333s]
+30/10/23 14:39:31| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 14:39:44| INFO: ref finished [took 12.0382s]
+30/10/23 14:39:47| INFO: atc_mc finished [took 15.0164s]
+30/10/23 14:39:47| INFO: atc_ne finished [took 15.1080s]
+30/10/23 14:40:02| INFO: mul_sld_bcts finished [took 30.9659s]
+30/10/23 14:40:04| INFO: mul_sld finished [took 32.9418s]
+30/10/23 14:40:04| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.4681s]
+30/10/23 14:40:04| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 14:40:14| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:40:17| INFO: ref finished [took 11.8501s]
+30/10/23 14:40:20| INFO: atc_mc finished [took 14.8473s]
+30/10/23 14:40:21| INFO: atc_ne finished [took 15.2000s]
+30/10/23 14:40:26| INFO: mul_sld finished [took 21.4799s]
+30/10/23 14:40:26| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.9220s]
+30/10/23 14:40:26| ERROR: Configuration imdb_1prevs failed. Exception: NDFrame.droplevel() got an unexpected keyword argument 'index'
+30/10/23 14:40:26| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 14:42:13| INFO: dataset imdb
+30/10/23 14:42:20| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 14:42:33| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:42:34| INFO: ref finished [took 12.1951s]
+30/10/23 14:42:38| INFO: atc_ne finished [took 15.3431s]
+30/10/23 14:42:38| INFO: atc_mc finished [took 15.4508s]
+30/10/23 14:42:47| INFO: mul_sld finished [took 25.0246s]
+30/10/23 14:42:47| INFO: Dataset sample 0.90 of dataset imdb finished [took 27.1381s]
+30/10/23 14:42:47| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 14:43:00| INFO: ref finished [took 12.3269s]
+30/10/23 14:43:04| INFO: atc_ne finished [took 15.9216s]
+30/10/23 14:43:04| INFO: atc_mc finished [took 16.1140s]
+30/10/23 14:43:16| INFO: mul_sld finished [took 28.0575s]
+30/10/23 14:43:22| INFO: mul_sld_bcts finished [took 33.9201s]
+30/10/23 14:43:22| INFO: Dataset sample 0.80 of dataset imdb finished [took 34.7703s]
+30/10/23 14:43:22| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 14:43:35| INFO: ref finished [took 12.6508s]
+30/10/23 14:43:39| INFO: atc_mc finished [took 16.0527s]
+30/10/23 14:43:39| INFO: atc_ne finished [took 16.0515s]
+30/10/23 14:43:50| INFO: mul_sld finished [took 28.1061s]
+30/10/23 14:43:57| INFO: mul_sld_bcts finished [took 34.9278s]
+30/10/23 14:43:57| INFO: Dataset sample 0.50 of dataset imdb finished [took 35.6587s]
+30/10/23 14:43:57| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 14:44:10| INFO: ref finished [took 12.0801s]
+30/10/23 14:44:14| INFO: atc_mc finished [took 15.4685s]
+30/10/23 14:44:14| INFO: atc_ne finished [took 15.4165s]
+30/10/23 14:44:29| INFO: mul_sld_bcts finished [took 31.5628s]
+30/10/23 14:44:31| INFO: mul_sld finished [took 33.3113s]
+30/10/23 14:44:31| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.8828s]
+30/10/23 14:44:31| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 14:44:41| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:44:44| INFO: ref finished [took 11.6822s]
+30/10/23 14:44:47| INFO: atc_mc finished [took 14.8091s]
+30/10/23 14:44:47| INFO: atc_ne finished [took 14.7900s]
+30/10/23 14:44:53| INFO: mul_sld finished [took 21.0390s]
+30/10/23 14:44:53| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.4515s]
+30/10/23 14:44:53| ERROR: Configuration imdb_1prevs failed. Exception: 'function' object has no attribute 'index'
+30/10/23 14:44:53| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 14:46:34| INFO: dataset imdb
+30/10/23 14:46:41| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 14:46:54| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:46:56| INFO: ref finished [took 12.5001s]
+30/10/23 14:46:59| INFO: atc_mc finished [took 15.5415s]
+30/10/23 14:46:59| INFO: atc_ne finished [took 15.6358s]
+30/10/23 14:47:08| INFO: mul_sld finished [took 24.5102s]
+30/10/23 14:47:08| INFO: Dataset sample 0.90 of dataset imdb finished [took 26.5553s]
+30/10/23 14:47:08| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 14:47:21| INFO: ref finished [took 12.0997s]
+30/10/23 14:47:24| INFO: atc_mc finished [took 15.4285s]
+30/10/23 14:47:24| INFO: atc_ne finished [took 15.5599s]
+30/10/23 14:47:36| INFO: mul_sld finished [took 27.6146s]
+30/10/23 14:47:43| INFO: mul_sld_bcts finished [took 34.2610s]
+30/10/23 14:47:43| INFO: Dataset sample 0.80 of dataset imdb finished [took 35.0096s]
+30/10/23 14:47:43| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 14:47:56| INFO: ref finished [took 12.1238s]
+30/10/23 14:48:00| INFO: atc_mc finished [took 15.6990s]
+30/10/23 14:48:00| INFO: atc_ne finished [took 15.8708s]
+30/10/23 14:48:11| INFO: mul_sld finished [took 28.0048s]
+30/10/23 14:48:20| INFO: mul_sld_bcts finished [took 36.1524s]
+30/10/23 14:48:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 36.8480s]
+30/10/23 14:48:20| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 14:48:32| INFO: ref finished [took 11.3690s]
+30/10/23 14:48:35| INFO: atc_mc finished [took 14.3092s]
+30/10/23 14:48:35| INFO: atc_ne finished [took 14.4043s]
+30/10/23 14:48:51| INFO: mul_sld_bcts finished [took 30.2595s]
+30/10/23 14:48:52| INFO: mul_sld finished [took 31.4270s]
+30/10/23 14:48:52| INFO: Dataset sample 0.20 of dataset imdb finished [took 31.9598s]
+30/10/23 14:48:52| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 14:49:02| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 14:49:04| INFO: ref finished [took 12.1449s]
+30/10/23 14:49:08| INFO: atc_mc finished [took 15.0332s]
+30/10/23 14:49:08| INFO: atc_ne finished [took 15.3463s]
+30/10/23 14:49:13| INFO: mul_sld finished [took 21.2802s]
+30/10/23 14:49:13| INFO: Dataset sample 0.10 of dataset imdb finished [took 21.7079s]
+30/10/23 14:49:14| ERROR: Configuration imdb_1prevs failed. Exception: unsupported operand type(s) for -: 'list' and 'list'
+30/10/23 14:49:14| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 15:10:08| INFO: dataset imdb
+30/10/23 15:10:14| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 15:10:26| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 15:10:27| INFO: ref finished [took 10.8100s]
+30/10/23 15:10:30| INFO: atc_mc finished [took 13.5996s]
+30/10/23 15:10:30| INFO: atc_ne finished [took 13.6110s]
+30/10/23 15:10:39| INFO: mul_sld finished [took 22.7361s]
+30/10/23 15:10:39| INFO: Dataset sample 0.90 of dataset imdb finished [took 24.8056s]
+30/10/23 15:10:39| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 15:10:51| INFO: ref finished [took 10.9293s]
+30/10/23 15:10:54| INFO: atc_mc finished [took 13.8377s]
+30/10/23 15:10:54| INFO: atc_ne finished [took 13.9983s]
+30/10/23 15:11:05| INFO: mul_sld finished [took 25.1977s]
+30/10/23 15:11:11| INFO: mul_sld_bcts finished [took 31.1124s]
+30/10/23 15:11:11| INFO: Dataset sample 0.80 of dataset imdb finished [took 31.8294s]
+30/10/23 15:11:11| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 15:11:23| INFO: ref finished [took 11.0056s]
+30/10/23 15:11:26| INFO: atc_mc finished [took 14.3946s]
+30/10/23 15:11:27| INFO: atc_ne finished [took 14.6355s]
+30/10/23 15:11:38| INFO: mul_sld finished [took 26.2697s]
+30/10/23 15:11:45| INFO: mul_sld_bcts finished [took 33.8992s]
+30/10/23 15:11:45| INFO: Dataset sample 0.50 of dataset imdb finished [took 34.4963s]
+30/10/23 15:11:45| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 15:11:57| INFO: ref finished [took 10.9836s]
+30/10/23 15:12:00| INFO: atc_mc finished [took 13.8378s]
+30/10/23 15:12:00| INFO: atc_ne finished [took 13.8318s]
+30/10/23 15:12:16| INFO: mul_sld_bcts finished [took 29.9813s]
+30/10/23 15:12:17| INFO: mul_sld finished [took 30.7175s]
+30/10/23 15:12:17| INFO: Dataset sample 0.20 of dataset imdb finished [took 31.2508s]
+30/10/23 15:12:17| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 15:12:26| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 15:12:28| INFO: ref finished [took 10.4376s]
+30/10/23 15:12:31| INFO: atc_ne finished [took 13.3510s]
+30/10/23 15:12:31| INFO: atc_mc finished [took 13.5172s]
+30/10/23 15:12:37| INFO: mul_sld finished [took 19.7440s]
+30/10/23 15:12:37| INFO: Dataset sample 0.10 of dataset imdb finished [took 20.1519s]
+30/10/23 15:12:37| ERROR: Configuration imdb_1prevs failed. Exception: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
+30/10/23 15:12:37| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 17:12:41| INFO: dataset imdb
+30/10/23 17:12:48| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 17:13:01| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 17:13:03| INFO: ref finished [took 12.6699s]
+30/10/23 17:13:07| INFO: atc_ne finished [took 15.6073s]
+30/10/23 17:13:07| INFO: atc_mc finished [took 15.6695s]
+30/10/23 17:13:15| INFO: mul_sld finished [took 24.8617s]
+30/10/23 17:13:15| INFO: Dataset sample 0.90 of dataset imdb finished [took 27.6018s]
+30/10/23 17:13:15| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 17:13:29| INFO: ref finished [took 12.6205s]
+30/10/23 17:13:33| INFO: atc_mc finished [took 16.2005s]
+30/10/23 17:13:33| INFO: atc_ne finished [took 16.2091s]
+30/10/23 17:13:43| INFO: mul_sld finished [took 27.1113s]
+30/10/23 17:13:49| INFO: mul_sld_bcts finished [took 33.3939s]
+30/10/23 17:13:49| INFO: Dataset sample 0.80 of dataset imdb finished [took 34.1222s]
+30/10/23 17:13:49| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 17:14:04| INFO: ref finished [took 13.2345s]
+30/10/23 17:14:07| INFO: atc_mc finished [took 16.5475s]
+30/10/23 17:14:07| INFO: atc_ne finished [took 16.6557s]
+30/10/23 17:14:19| INFO: mul_sld finished [took 28.8817s]
+30/10/23 17:14:27| INFO: mul_sld_bcts finished [took 36.5726s]
+30/10/23 17:14:27| INFO: Dataset sample 0.50 of dataset imdb finished [took 37.2057s]
+30/10/23 17:14:27| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 17:14:39| INFO: ref finished [took 11.7051s]
+30/10/23 17:14:42| INFO: atc_mc finished [took 14.8335s]
+30/10/23 17:14:43| INFO: atc_ne finished [took 15.0826s]
+30/10/23 17:14:59| INFO: mul_sld_bcts finished [took 31.7685s]
+30/10/23 17:15:00| INFO: mul_sld finished [took 33.2861s]
+30/10/23 17:15:00| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.8225s]
+30/10/23 17:15:00| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 17:15:11| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 17:15:13| INFO: ref finished [took 12.0927s]
+30/10/23 17:15:17| INFO: atc_mc finished [took 15.4201s]
+30/10/23 17:15:17| INFO: atc_ne finished [took 15.5212s]
+30/10/23 17:15:23| INFO: mul_sld finished [took 21.7236s]
+30/10/23 17:15:23| INFO: Dataset sample 0.10 of dataset imdb finished [took 22.2065s]
+30/10/23 17:15:23| ERROR: Configuration imdb_1prevs failed. Exception: operands could not be broadcast together with shapes (0,) (0,21)
+30/10/23 17:15:23| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 17:16:39| INFO: dataset imdb
+30/10/23 17:16:46| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 17:16:58| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 17:17:00| INFO: ref finished [took 11.7575s]
+30/10/23 17:17:03| INFO: atc_ne finished [took 14.7709s]
+30/10/23 17:17:03| INFO: atc_mc finished [took 14.8925s]
+30/10/23 17:17:12| INFO: mul_sld finished [took 23.7037s]
+30/10/23 17:17:12| INFO: Dataset sample 0.90 of dataset imdb finished [took 25.8491s]
+30/10/23 17:17:12| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 17:17:25| INFO: ref finished [took 12.2081s]
+30/10/23 17:17:28| INFO: atc_ne finished [took 15.3145s]
+30/10/23 17:17:28| INFO: atc_mc finished [took 15.5166s]
+30/10/23 17:17:39| INFO: mul_sld finished [took 26.7520s]
+30/10/23 17:17:45| INFO: mul_sld_bcts finished [took 32.0850s]
+30/10/23 17:17:45| INFO: Dataset sample 0.80 of dataset imdb finished [took 32.8702s]
+30/10/23 17:17:45| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 17:17:57| INFO: ref finished [took 11.9494s]
+30/10/23 17:18:01| INFO: atc_mc finished [took 15.3034s]
+30/10/23 17:18:01| INFO: atc_ne finished [took 15.3254s]
+30/10/23 17:18:12| INFO: mul_sld finished [took 27.2902s]
+30/10/23 17:18:20| INFO: mul_sld_bcts finished [took 34.4237s]
+30/10/23 17:18:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 35.1216s]
+30/10/23 17:18:20| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 17:18:32| INFO: ref finished [took 11.7945s]
+30/10/23 17:18:35| INFO: atc_mc finished [took 14.9218s]
+30/10/23 17:18:36| INFO: atc_ne finished [took 14.9745s]
+30/10/23 17:18:51| INFO: mul_sld_bcts finished [took 30.7287s]
+30/10/23 17:18:53| INFO: mul_sld finished [took 32.5641s]
+30/10/23 17:18:53| INFO: Dataset sample 0.20 of dataset imdb finished [took 33.0982s]
+30/10/23 17:18:53| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 17:19:02| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 17:19:05| INFO: ref finished [took 11.4568s]
+30/10/23 17:19:08| INFO: atc_mc finished [took 14.4778s]
+30/10/23 17:19:08| INFO: atc_ne finished [took 14.5099s]
+30/10/23 17:19:14| INFO: mul_sld finished [took 20.5183s]
+30/10/23 17:19:14| INFO: Dataset sample 0.10 of dataset imdb finished [took 20.9251s]
+30/10/23 17:19:14| ERROR: Configuration imdb_1prevs failed. Exception: operands could not be broadcast together with shapes (0,) (0,21)
+30/10/23 17:19:14| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+30/10/23 19:57:49| INFO: dataset imdb
+30/10/23 19:58:00| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 19:58:11| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 19:58:22| INFO: ref finished [took 20.9010s]
+30/10/23 19:58:29| INFO: atc_ne finished [took 27.8453s]
+30/10/23 19:58:29| INFO: atc_mc finished [took 28.1079s]
+30/10/23 19:58:37| INFO: mul_sld finished [took 36.1699s]
+30/10/23 19:58:37| INFO: Dataset sample 0.90 of dataset imdb finished [took 36.7140s]
+30/10/23 19:58:37| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 19:59:01| INFO: ref finished [took 23.2803s]
+30/10/23 19:59:09| INFO: atc_ne finished [took 31.1099s]
+30/10/23 19:59:09| INFO: atc_mc finished [took 31.5916s]
+30/10/23 19:59:19| INFO: mul_sld finished [took 41.5113s]
+30/10/23 19:59:24| INFO: mul_sld_bcts finished [took 46.6603s]
+30/10/23 19:59:24| INFO: Dataset sample 0.80 of dataset imdb finished [took 47.4989s]
+30/10/23 19:59:24| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 19:59:49| INFO: ref finished [took 23.6312s]
+30/10/23 19:59:57| INFO: atc_ne finished [took 31.5195s]
+30/10/23 19:59:57| INFO: atc_mc finished [took 31.8197s]
+30/10/23 20:00:08| INFO: mul_sld finished [took 42.8675s]
+30/10/23 20:00:15| INFO: mul_sld_bcts finished [took 50.5527s]
+30/10/23 20:00:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 51.3659s]
+30/10/23 20:00:16| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 20:00:41| INFO: ref finished [took 24.2178s]
+30/10/23 20:00:48| INFO: atc_mc finished [took 31.9886s]
+30/10/23 20:00:49| INFO: atc_ne finished [took 32.1537s]
+30/10/23 20:01:03| INFO: mul_sld_bcts finished [took 46.2477s]
+30/10/23 20:01:07| INFO: mul_sld finished [took 50.8912s]
+30/10/23 20:01:07| INFO: Dataset sample 0.20 of dataset imdb finished [took 51.4589s]
+30/10/23 20:01:07| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 20:01:18| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 20:01:30| INFO: ref finished [took 22.6404s]
+30/10/23 20:01:38| INFO: atc_mc finished [took 29.8371s]
+30/10/23 20:01:38| INFO: atc_ne finished [took 30.2098s]
+30/10/23 20:01:41| INFO: mul_sld finished [took 33.6271s]
+30/10/23 20:01:41| INFO: Dataset sample 0.10 of dataset imdb finished [took 34.1993s]
+30/10/23 20:01:42| ERROR: Configuration imdb_1prevs failed. Exception: operands could not be broadcast together with shapes (0,) (0,21)
+30/10/23 20:01:42| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 20:05:04| INFO: dataset imdb
+30/10/23 20:05:14| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 20:05:26| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 20:05:38| INFO: ref finished [took 22.7241s]
+30/10/23 20:05:45| INFO: atc_mc finished [took 29.9191s]
+30/10/23 20:05:45| INFO: atc_ne finished [took 29.8405s]
+30/10/23 20:05:52| INFO: mul_sld finished [took 37.4045s]
+30/10/23 20:05:52| INFO: Dataset sample 0.90 of dataset imdb finished [took 37.9554s]
+30/10/23 20:05:52| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 20:06:17| INFO: ref finished [took 23.2465s]
+30/10/23 20:06:25| INFO: atc_ne finished [took 31.0138s]
+30/10/23 20:06:25| INFO: atc_mc finished [took 31.1341s]
+30/10/23 20:06:34| INFO: mul_sld finished [took 40.8777s]
+30/10/23 20:06:40| INFO: mul_sld_bcts finished [took 46.7083s]
+30/10/23 20:06:40| INFO: Dataset sample 0.80 of dataset imdb finished [took 47.5062s]
+30/10/23 20:06:40| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:07:05| INFO: ref finished [took 24.3375s]
+30/10/23 20:07:15| INFO: atc_mc finished [took 33.8014s]
+30/10/23 20:07:15| INFO: atc_ne finished [took 33.7355s]
+30/10/23 20:07:25| INFO: mul_sld finished [took 44.2891s]
+30/10/23 20:07:32| INFO: mul_sld_bcts finished [took 51.2404s]
+30/10/23 20:07:32| INFO: Dataset sample 0.50 of dataset imdb finished [took 51.9917s]
+30/10/23 20:07:32| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 20:07:55| INFO: ref finished [took 21.6828s]
+30/10/23 20:08:01| INFO: atc_mc finished [took 28.2369s]
+30/10/23 20:08:01| INFO: atc_ne finished [took 28.4328s]
+30/10/23 20:08:15| INFO: mul_sld_bcts finished [took 41.9176s]
+30/10/23 20:08:18| INFO: mul_sld finished [took 45.4999s]
+30/10/23 20:08:18| INFO: Dataset sample 0.20 of dataset imdb finished [took 46.0301s]
+30/10/23 20:08:18| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 20:08:28| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 20:08:38| INFO: ref finished [took 19.4082s]
+30/10/23 20:08:45| INFO: atc_mc finished [took 26.2343s]
+30/10/23 20:08:45| INFO: atc_ne finished [took 26.2322s]
+30/10/23 20:08:48| INFO: mul_sld finished [took 29.8392s]
+30/10/23 20:08:48| INFO: Dataset sample 0.10 of dataset imdb finished [took 30.3563s]
+----------------------------------------------------------------------------------------------------
+30/10/23 20:29:28| INFO: dataset imdb
+30/10/23 20:29:38| INFO: Dataset sample 0.50 of dataset imdb started
+ 30/10/23 20:29:59| INFO: ref finished [took 19.1581s]
+ 30/10/23 20:30:06| INFO: atc_mc finished [took 26.3398s]
+ 30/10/23 20:30:07| INFO: atc_ne finished [took 26.4359s]
+30/10/23 20:30:07| INFO: Dataset sample 0.50 of dataset imdb finished [took 28.7984s]
+----------------------------------------------------------------------------------------------------
+30/10/23 20:31:50| INFO: dataset imdb
+30/10/23 20:32:00| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:33:59|INFO: ref finished [took 118.1306s]
+----------------------------------------------------------------------------------------------------
+30/10/23 20:36:06| INFO: dataset imdb
+30/10/23 20:36:17| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:38:52|WARNING: Method ref failed. Exception: "['acc_score' 'f1_score' 'ref'] not in index"
+30/10/23 20:41:28|WARNING: Method atc_mc failed. Exception: "['acc' 'acc_score' 'atc_mc' 'f1' 'f1_score'] not in index"
+30/10/23 20:41:32|WARNING: Method atc_ne failed. Exception: "['acc' 'acc_score' 'atc_ne' 'f1' 'f1_score'] not in index"
+30/10/23 20:41:32| INFO: Dataset sample 0.50 of dataset imdb finished [took 315.4626s]
+30/10/23 20:41:32| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:41:32| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
+30/10/23 20:41:32| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 20:41:43| INFO: dataset imdb
+30/10/23 20:41:54| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:42:26| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
+30/10/23 20:43:01| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:43:08| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:43:08| INFO: Dataset sample 0.50 of dataset imdb finished [took 73.6011s]
+30/10/23 20:43:08| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:43:08| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
+30/10/23 20:43:08| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 20:44:25| INFO: dataset imdb
+30/10/23 20:44:35| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:44:37| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
+30/10/23 20:44:37| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:44:38| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:44:38| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.6758s]
+30/10/23 20:44:38| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:44:38| ERROR: Configuration imdb_1prevs failed. Exception: 'module' object is not callable
+30/10/23 20:44:38| ERROR: estimate comparison failed. Exceprion: 'module' object is not callable
+----------------------------------------------------------------------------------------------------
+30/10/23 20:47:08| INFO: dataset imdb
+30/10/23 20:47:18| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:47:20| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
+30/10/23 20:47:21| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:47:21| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:47:21| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.6147s]
+30/10/23 20:47:21| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:47:21| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
+----------------------------------------------------------------------------------------------------
+30/10/23 20:50:07| INFO: dataset imdb
+30/10/23 20:50:17| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:50:19| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
+30/10/23 20:50:20| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:50:20| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:50:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.5897s]
+30/10/23 20:50:20| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:50:20| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
+----------------------------------------------------------------------------------------------------
+30/10/23 20:51:29| INFO: dataset imdb
+30/10/23 20:51:39| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:51:42| WARNING: Method ref failed. Exception: Shape of passed values is (2, 1), indices imply (1, 2)
+30/10/23 20:51:42| WARNING: Method atc_mc failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:51:42| WARNING: Method atc_ne failed. Exception: Shape of passed values is (4, 1), indices imply (1, 4)
+30/10/23 20:51:42| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.5821s]
+30/10/23 20:51:42| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:51:42| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
+----------------------------------------------------------------------------------------------------
+30/10/23 20:56:28| INFO: dataset imdb
+30/10/23 20:56:38| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:56:40| WARNING: Method ref failed. Exception: cannot reshape array of size 1 into shape (1,2)
+30/10/23 20:56:40| WARNING: Method atc_mc failed. Exception: cannot reshape array of size 1 into shape (1,4)
+30/10/23 20:56:40| WARNING: Method atc_ne failed. Exception: cannot reshape array of size 1 into shape (1,4)
+30/10/23 20:56:40| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.6150s]
+30/10/23 20:56:40| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:56:40| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
+----------------------------------------------------------------------------------------------------
+30/10/23 20:57:13| INFO: dataset imdb
+30/10/23 20:57:23| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 20:59:40| WARNING: Method ref failed. Exception: cannot reshape array of size 1 into shape (1,2)
+30/10/23 20:59:51| WARNING: Method atc_mc failed. Exception: cannot reshape array of size 1 into shape (1,4)
+30/10/23 20:59:52| WARNING: Method atc_ne failed. Exception: cannot reshape array of size 1 into shape (1,4)
+30/10/23 20:59:52| INFO: Dataset sample 0.50 of dataset imdb finished [took 149.2395s]
+30/10/23 20:59:52| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 20:59:52| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
+----------------------------------------------------------------------------------------------------
+30/10/23 21:00:04| INFO: dataset imdb
+30/10/23 21:00:14| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:01:33| INFO: ref finished [took 78.2917s]
+30/10/23 21:01:42| INFO: atc_mc finished [took 86.9003s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:01:59| INFO: dataset imdb
+30/10/23 21:02:09| INFO: Dataset sample 0.50 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 21:04:09| INFO: dataset imdb
+30/10/23 21:04:19| INFO: Dataset sample 0.50 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 21:06:25| INFO: dataset imdb
+30/10/23 21:06:35| INFO: Dataset sample 0.50 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 21:07:33| INFO: dataset imdb
+30/10/23 21:07:43| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:07:45| WARNING: Method ref failed. Exception: setting an array element with a sequence.
+30/10/23 21:07:45| WARNING: Method atc_mc failed. Exception: setting an array element with a sequence.
+30/10/23 21:07:45| WARNING: Method atc_ne failed. Exception: setting an array element with a sequence.
+30/10/23 21:07:45| INFO: Dataset sample 0.50 of dataset imdb finished [took 2.5382s]
+30/10/23 21:07:45| WARNING: Dataset sample 0.50 of dataset imdb failed. Exception: No objects to concatenate
+30/10/23 21:07:45| ERROR: Configuration imdb_1prevs failed. Exception: No objects to concatenate
+----------------------------------------------------------------------------------------------------
+30/10/23 21:09:07| INFO: dataset imdb
+30/10/23 21:09:16| INFO: Dataset sample 0.50 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 21:10:48| INFO: dataset imdb
+30/10/23 21:10:58| INFO: Dataset sample 0.50 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 21:18:53| INFO: dataset imdb
+30/10/23 21:19:03| INFO: Dataset sample 0.50 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 21:22:03| INFO: dataset imdb
+30/10/23 21:22:12| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:22:31| INFO: ref finished [took 17.0861s]
+30/10/23 21:22:37| INFO: atc_mc finished [took 23.6279s]
+30/10/23 21:22:38| INFO: atc_ne finished [took 23.7395s]
+30/10/23 21:22:38| INFO: Dataset sample 0.50 of dataset imdb finished [took 25.2007s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:29:55| INFO: dataset imdb
+30/10/23 21:30:05| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:30:23| INFO: ref finished [took 16.7801s]
+30/10/23 21:30:30| INFO: atc_mc finished [took 23.5645s]
+30/10/23 21:30:30| INFO: atc_ne finished [took 23.5639s]
+30/10/23 21:30:30| INFO: Dataset sample 0.50 of dataset imdb finished [took 25.0459s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:33:45| INFO: dataset imdb
+30/10/23 21:33:55| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:34:13| INFO: ref finished [took 17.0169s]
+30/10/23 21:34:20| INFO: atc_mc finished [took 23.4725s]
+30/10/23 21:34:20| INFO: atc_ne finished [took 23.5928s]
+30/10/23 21:34:20| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.9542s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:37:32| INFO: dataset imdb
+30/10/23 21:37:39| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:37:49| INFO: ref finished [took 8.9050s]
+30/10/23 21:37:52| INFO: atc_mc finished [took 11.7412s]
+30/10/23 21:37:52| INFO: atc_ne finished [took 11.7256s]
+30/10/23 21:37:52| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.9758s]
+30/10/23 21:37:53| ERROR: Configuration imdb_1prevs failed. Exception: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
+----------------------------------------------------------------------------------------------------
+30/10/23 21:39:14| INFO: dataset imdb
+30/10/23 21:39:21| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:39:31| INFO: ref finished [took 8.5615s]
+30/10/23 21:39:34| INFO: atc_mc finished [took 11.4156s]
+30/10/23 21:39:34| INFO: atc_ne finished [took 11.4156s]
+30/10/23 21:39:34| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.7024s]
+30/10/23 21:39:35| ERROR: Configuration imdb_1prevs failed. Exception: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
+----------------------------------------------------------------------------------------------------
+30/10/23 21:40:51| INFO: dataset imdb
+30/10/23 21:41:01| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:41:19| INFO: ref finished [took 16.7164s]
+30/10/23 21:41:26| INFO: atc_mc finished [took 23.3181s]
+30/10/23 21:41:26| INFO: atc_ne finished [took 23.4811s]
+30/10/23 21:41:26| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.9698s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:43:25| INFO: dataset imdb
+30/10/23 21:43:35| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:43:53| INFO: ref finished [took 16.9333s]
+30/10/23 21:44:00| INFO: atc_mc finished [took 23.4183s]
+30/10/23 21:44:00| INFO: atc_ne finished [took 23.4274s]
+30/10/23 21:44:00| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.9308s]
+30/10/23 21:44:19| ERROR: Configuration imdb_1prevs failed. Exception: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
+----------------------------------------------------------------------------------------------------
+30/10/23 21:45:16| INFO: dataset imdb
+30/10/23 21:45:26| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:45:44| INFO: ref finished [took 17.6768s]
+30/10/23 21:45:51| INFO: atc_mc finished [took 24.3756s]
+30/10/23 21:45:52| INFO: atc_ne finished [took 24.5307s]
+30/10/23 21:45:52| INFO: Dataset sample 0.50 of dataset imdb finished [took 25.8971s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:48:20| INFO: dataset imdb
+30/10/23 21:48:27| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:48:36| INFO: ref finished [took 8.6456s]
+30/10/23 21:48:39| INFO: atc_mc finished [took 11.2686s]
+30/10/23 21:48:39| INFO: atc_ne finished [took 11.3112s]
+30/10/23 21:48:39| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.5747s]
+30/10/23 21:48:40| ERROR: Configuration imdb_1prevs failed. Exception: NDFrame.droplevel() got an unexpected keyword argument 'index'
+----------------------------------------------------------------------------------------------------
+30/10/23 21:49:49| INFO: dataset imdb
+30/10/23 21:49:55| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:50:05| INFO: ref finished [took 8.6556s]
+30/10/23 21:50:08| INFO: atc_mc finished [took 11.6953s]
+30/10/23 21:50:08| INFO: atc_ne finished [took 11.6000s]
+30/10/23 21:50:08| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.8578s]
+30/10/23 21:50:09| ERROR: Configuration imdb_1prevs failed. Exception: 'NoneType' object has no attribute 'groupby'
+----------------------------------------------------------------------------------------------------
+30/10/23 21:50:57| INFO: dataset imdb
+30/10/23 21:51:07| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:51:25| INFO: ref finished [took 17.0426s]
+30/10/23 21:51:31| INFO: atc_mc finished [took 23.5734s]
+30/10/23 21:51:31| INFO: atc_ne finished [took 23.5276s]
+30/10/23 21:51:31| INFO: Dataset sample 0.50 of dataset imdb finished [took 24.8200s]
+----------------------------------------------------------------------------------------------------
+30/10/23 21:55:21| INFO: dataset imdb
+30/10/23 21:55:27| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:55:37| INFO: ref finished [took 8.8453s]
+30/10/23 21:55:40| INFO: atc_mc finished [took 11.5585s]
+30/10/23 21:55:40| INFO: atc_ne finished [took 11.5871s]
+30/10/23 21:55:40| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.8416s]
+30/10/23 21:55:41| ERROR: Configuration imdb_1prevs failed. Exception: 'DatasetReport' object has no attribute 'fit_scores'
+----------------------------------------------------------------------------------------------------
+30/10/23 21:57:00| INFO: dataset imdb
+30/10/23 21:57:06| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:57:16| INFO: ref finished [took 8.5540s]
+30/10/23 21:57:19| INFO: atc_mc finished [took 11.4482s]
+30/10/23 21:57:19| INFO: atc_ne finished [took 11.5399s]
+30/10/23 21:57:19| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.7681s]
+30/10/23 21:57:20| ERROR: Configuration imdb_1prevs failed. Exception: 'DatasetReport' object has no attribute 'fit_scores'
+----------------------------------------------------------------------------------------------------
+30/10/23 21:57:38| INFO: dataset imdb
+30/10/23 21:57:45| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 21:57:55| INFO: ref finished [took 8.7982s]
+30/10/23 21:57:58| INFO: atc_mc finished [took 11.4787s]
+30/10/23 21:57:58| INFO: atc_ne finished [took 11.5419s]
+30/10/23 21:57:58| INFO: Dataset sample 0.50 of dataset imdb finished [took 12.8803s]
+----------------------------------------------------------------------------------------------------
+30/10/23 22:00:05| INFO: dataset imdb
+30/10/23 22:00:12| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 22:00:21| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 22:00:22| INFO: ref finished [took 10.0983s]
+30/10/23 22:00:25| INFO: atc_mc finished [took 13.0928s]
+30/10/23 22:00:26| INFO: atc_ne finished [took 13.1088s]
+30/10/23 22:00:34| INFO: mul_sld finished [took 22.3228s]
+30/10/23 22:00:34| INFO: Dataset sample 0.90 of dataset imdb finished [took 22.7020s]
+30/10/23 22:00:34| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 22:00:46| INFO: ref finished [took 10.5937s]
+30/10/23 22:00:49| INFO: atc_mc finished [took 13.5008s]
+30/10/23 22:00:49| INFO: atc_ne finished [took 13.7521s]
+30/10/23 22:01:00| INFO: mul_sld finished [took 25.0319s]
+30/10/23 22:01:06| INFO: mul_sld_bcts finished [took 31.0525s]
+30/10/23 22:01:06| INFO: Dataset sample 0.80 of dataset imdb finished [took 31.7700s]
+30/10/23 22:01:06| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 22:01:17| INFO: ref finished [took 10.6316s]
+30/10/23 22:01:21| INFO: atc_ne finished [took 14.1054s]
+30/10/23 22:01:21| INFO: atc_mc finished [took 14.4357s]
+30/10/23 22:01:33| INFO: mul_sld finished [took 26.6800s]
+30/10/23 22:01:41| INFO: mul_sld_bcts finished [took 34.4745s]
+30/10/23 22:01:41| INFO: Dataset sample 0.50 of dataset imdb finished [took 35.1450s]
+30/10/23 22:01:41| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 22:01:53| INFO: ref finished [took 10.7413s]
+30/10/23 22:01:56| INFO: atc_ne finished [took 13.5169s]
+30/10/23 22:01:56| INFO: atc_mc finished [took 13.5849s]
+30/10/23 22:02:11| INFO: mul_sld_bcts finished [took 29.3981s]
+30/10/23 22:02:12| INFO: mul_sld finished [took 30.6705s]
+30/10/23 22:02:12| INFO: Dataset sample 0.20 of dataset imdb finished [took 31.2089s]
+30/10/23 22:02:12| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 22:02:22| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 22:02:24| INFO: ref finished [took 10.3435s]
+30/10/23 22:02:26| INFO: atc_mc finished [took 13.0763s]
+30/10/23 22:02:27| INFO: atc_ne finished [took 13.2013s]
+30/10/23 22:02:32| INFO: mul_sld finished [took 19.2237s]
+30/10/23 22:02:32| INFO: Dataset sample 0.10 of dataset imdb finished [took 19.7097s]
+----------------------------------------------------------------------------------------------------
+30/10/23 22:07:59| INFO: dataset imdb
+30/10/23 22:08:07| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 22:08:10| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:08:11| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:08:11| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:08:11| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+30/10/23 22:08:18| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 22:08:20| INFO: ref finished [took 11.3765s]
+30/10/23 22:08:23| INFO: atc_mc finished [took 14.2141s]
+30/10/23 22:08:23| INFO: atc_ne finished [took 14.0568s]
+30/10/23 22:08:31| INFO: mul_sld finished [took 23.9496s]
+30/10/23 22:08:31| INFO: Dataset sample 0.90 of dataset imdb finished [took 24.5121s]
+30/10/23 22:08:31| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 22:08:48| INFO: ref finished [took 14.8939s]
+30/10/23 22:08:52| INFO: atc_mc finished [took 18.5014s]
+30/10/23 22:08:52| INFO: atc_ne finished [took 18.4609s]
+30/10/23 22:09:05| INFO: mul_sld finished [took 32.9898s]
+30/10/23 22:09:12| INFO: mul_sld_bcts finished [took 39.3492s]
+30/10/23 22:11:48| INFO: bin_sld_bcts finished [took 195.8293s]
+30/10/23 22:11:49| INFO: bin_sld finished [took 196.6861s]
+30/10/23 22:12:44| INFO: mul_sld_gs finished [took 250.9835s]
+30/10/23 22:16:16| INFO: bin_sld_gs finished [took 462.9748s]
+30/10/23 22:16:16| INFO: Dataset sample 0.80 of dataset imdb finished [took 464.4318s]
+30/10/23 22:16:16| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 22:16:33| INFO: ref finished [took 15.2921s]
+30/10/23 22:16:37| INFO: atc_mc finished [took 18.9592s]
+30/10/23 22:16:37| INFO: atc_ne finished [took 19.1317s]
+30/10/23 22:16:50| INFO: mul_sld finished [took 33.4304s]
+30/10/23 22:16:59| INFO: mul_sld_bcts finished [took 42.3496s]
+30/10/23 22:19:33| INFO: bin_sld finished [took 196.1571s]
+30/10/23 22:19:36| INFO: bin_sld_bcts finished [took 199.7857s]
+30/10/23 22:20:39| INFO: mul_sld_gs finished [took 261.6674s]
+30/10/23 22:23:46| INFO: bin_sld_gs finished [took 449.3788s]
+30/10/23 22:23:46| INFO: Dataset sample 0.50 of dataset imdb finished [took 450.7045s]
+30/10/23 22:23:46| INFO: Dataset sample 0.20 of dataset imdb started
+30/10/23 22:24:05| INFO: ref finished [took 16.4122s]
+30/10/23 22:24:09| INFO: atc_mc finished [took 20.4920s]
+30/10/23 22:24:09| INFO: atc_ne finished [took 20.3723s]
+30/10/23 22:24:28| INFO: mul_sld_bcts finished [took 40.3400s]
+30/10/23 22:24:30| INFO: mul_sld finished [took 43.2311s]
+30/10/23 22:27:16| INFO: bin_sld_bcts finished [took 208.6113s]
+30/10/23 22:27:21| INFO: bin_sld finished [took 214.1596s]
+30/10/23 22:28:17| INFO: mul_sld_gs finished [took 269.1075s]
+30/10/23 22:34:19| INFO: bin_sld_gs finished [took 630.9727s]
+30/10/23 22:34:19| INFO: Dataset sample 0.20 of dataset imdb finished [took 632.2728s]
+30/10/23 22:34:19| INFO: Dataset sample 0.10 of dataset imdb started
+30/10/23 22:34:23| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+30/10/23 22:34:23| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+30/10/23 22:34:26| WARNING: Method bin_sld_bcts failed. Exception: Cannot have number of splits n_splits=5 greater than the number of samples: n_samples=4.
+30/10/23 22:34:31| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 22:34:34| INFO: ref finished [took 13.7988s]
+30/10/23 22:34:37| INFO: atc_mc finished [took 16.7490s]
+30/10/23 22:34:38| INFO: atc_ne finished [took 16.7307s]
+30/10/23 22:34:43| INFO: mul_sld finished [took 23.6079s]
+30/10/23 22:36:42| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+30/10/23 22:36:42| INFO: Dataset sample 0.10 of dataset imdb finished [took 143.1097s]
+----------------------------------------------------------------------------------------------------
+30/10/23 22:49:25| INFO: dataset imdb
+30/10/23 22:49:37| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 22:49:42| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+30/10/23 22:49:43| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:49:43| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:49:43| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:49:51| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 22:50:02| INFO: ref finished [took 22.5398s]
+30/10/23 22:50:09| INFO: atc_mc finished [took 29.3095s]
+30/10/23 22:50:09| INFO: atc_ne finished [took 29.2984s]
+30/10/23 22:50:16| INFO: mul_sld finished [took 37.6287s]
+30/10/23 22:50:16| INFO: Dataset sample 0.90 of dataset imdb finished [took 38.3452s]
+----------------------------------------------------------------------------------------------------
+30/10/23 22:53:57| INFO: dataset imdb
+30/10/23 22:54:09| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 22:54:13| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+30/10/23 22:54:14| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:54:15| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:54:15| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 22:54:22| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 22:54:33| INFO: ref finished [took 22.4225s]
+30/10/23 22:54:40| INFO: atc_ne finished [took 29.0085s]
+30/10/23 22:54:41| INFO: atc_mc finished [took 29.6620s]
+30/10/23 22:54:48| INFO: mul_sld finished [took 37.9580s]
+30/10/23 22:54:48| INFO: Dataset sample 0.90 of dataset imdb finished [took 38.6632s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:02:33| INFO: dataset imdb
+30/10/23 23:02:45| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 23:02:50| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+30/10/23 23:02:51| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 23:02:52| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 23:02:52| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 23:02:59| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 23:03:10| INFO: ref finished [took 23.4021s]
+30/10/23 23:03:17| INFO: atc_mc finished [took 30.1849s]
+30/10/23 23:03:18| INFO: atc_ne finished [took 30.4116s]
+30/10/23 23:03:25| INFO: mul_sld finished [took 38.6513s]
+30/10/23 23:03:25| INFO: Dataset sample 0.90 of dataset imdb finished [took 39.3497s]
+30/10/23 23:07:32| INFO: Dataset sample 0.80 of dataset imdb started
+----------------------------------------------------------------------------------------------------
+30/10/23 23:08:15| INFO: dataset imdb
+30/10/23 23:08:26| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:08:51| INFO: ref finished [took 23.6855s]
+30/10/23 23:08:59| INFO: atc_mc finished [took 31.1520s]
+30/10/23 23:08:59| INFO: atc_ne finished [took 31.1659s]
+30/10/23 23:09:10| INFO: mul_sld finished [took 42.2066s]
+30/10/23 23:09:21| INFO: mul_sld_bcts finished [took 52.9631s]
+30/10/23 23:09:21| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.5286s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:14:11| INFO: dataset imdb
+30/10/23 23:14:22| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:14:47| INFO: ref finished [took 22.8152s]
+30/10/23 23:14:55| INFO: atc_mc finished [took 31.2100s]
+30/10/23 23:14:55| INFO: atc_ne finished [took 31.2325s]
+30/10/23 23:15:06| INFO: mul_sld finished [took 42.5389s]
+30/10/23 23:15:16| INFO: mul_sld_bcts finished [took 52.7119s]
+30/10/23 23:15:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.2106s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:16:16| INFO: dataset imdb
+30/10/23 23:16:27| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:16:51| INFO: ref finished [took 22.6482s]
+30/10/23 23:17:00| INFO: atc_ne finished [took 30.5701s]
+30/10/23 23:17:00| INFO: atc_mc finished [took 30.9988s]
+30/10/23 23:17:10| INFO: mul_sld finished [took 41.9572s]
+30/10/23 23:17:21| INFO: mul_sld_bcts finished [took 52.6091s]
+30/10/23 23:17:21| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.1182s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:20:27| INFO: dataset imdb
+30/10/23 23:20:38| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:21:02| INFO: ref finished [took 22.7779s]
+30/10/23 23:21:10| INFO: atc_mc finished [took 30.4191s]
+30/10/23 23:21:10| INFO: atc_ne finished [took 30.8097s]
+30/10/23 23:21:20| INFO: mul_sld finished [took 41.5927s]
+30/10/23 23:21:32| INFO: mul_sld_bcts finished [took 52.6374s]
+30/10/23 23:21:32| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.1125s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:24:11| INFO: dataset imdb
+30/10/23 23:24:22| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:24:46| INFO: ref finished [took 23.2007s]
+30/10/23 23:24:54| INFO: atc_ne finished [took 30.9437s]
+30/10/23 23:24:55| INFO: atc_mc finished [took 31.6008s]
+30/10/23 23:25:05| INFO: mul_sld finished [took 42.0673s]
+30/10/23 23:25:16| INFO: mul_sld_bcts finished [took 52.6228s]
+30/10/23 23:25:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.0611s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:33:01| INFO: dataset imdb
+30/10/23 23:33:11| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:33:36| INFO: ref finished [took 22.9215s]
+30/10/23 23:33:44| INFO: atc_mc finished [took 30.5897s]
+30/10/23 23:33:44| INFO: atc_ne finished [took 30.4788s]
+30/10/23 23:33:55| INFO: mul_sld finished [took 42.0598s]
+30/10/23 23:34:05| INFO: mul_sld_bcts finished [took 52.1772s]
+30/10/23 23:34:05| INFO: Dataset sample 0.50 of dataset imdb finished [took 53.6878s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:38:11| INFO: dataset imdb
+30/10/23 23:38:22| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:38:47| INFO: ref finished [took 22.8046s]
+30/10/23 23:38:56| INFO: atc_mc finished [took 31.5660s]
+30/10/23 23:38:56| INFO: atc_ne finished [took 31.5269s]
+30/10/23 23:39:06| INFO: mul_sld finished [took 42.2553s]
+30/10/23 23:39:16| INFO: mul_sld_bcts finished [took 52.2602s]
+30/10/23 23:39:16| INFO: Dataset sample 0.50 of dataset imdb finished [took 53.7890s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:46:40| INFO: dataset imdb
+30/10/23 23:46:51| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:47:16| INFO: ref finished [took 22.8069s]
+30/10/23 23:47:24| INFO: atc_mc finished [took 30.7916s]
+30/10/23 23:47:24| INFO: atc_ne finished [took 30.8668s]
+30/10/23 23:47:35| INFO: mul_sld finished [took 42.2809s]
+30/10/23 23:47:45| INFO: mul_sld_bcts finished [took 52.5498s]
+30/10/23 23:47:45| INFO: Dataset sample 0.50 of dataset imdb finished [took 54.0424s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:50:43| INFO: dataset imdb
+30/10/23 23:50:50| INFO: Dataset sample 0.50 of dataset imdb started
+30/10/23 23:51:04| INFO: ref finished [took 12.0863s]
+30/10/23 23:51:07| INFO: atc_ne finished [took 15.0218s]
+30/10/23 23:51:08| INFO: atc_mc finished [took 15.7900s]
+30/10/23 23:51:20| INFO: mul_sld finished [took 28.7221s]
+30/10/23 23:51:31| INFO: mul_sld_bcts finished [took 39.4698s]
+30/10/23 23:51:31| INFO: Dataset sample 0.50 of dataset imdb finished [took 40.8506s]
+----------------------------------------------------------------------------------------------------
+30/10/23 23:52:29| INFO: dataset imdb
+30/10/23 23:52:37| INFO: Dataset sample 0.90 of dataset imdb started
+30/10/23 23:52:40| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 23:52:41| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 23:52:41| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+30/10/23 23:52:41| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+30/10/23 23:52:48| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+30/10/23 23:52:50| INFO: ref finished [took 12.4800s]
+30/10/23 23:52:53| INFO: atc_mc finished [took 15.1770s]
+30/10/23 23:52:54| INFO: atc_ne finished [took 15.2184s]
+30/10/23 23:53:02| INFO: mul_sld finished [took 24.9402s]
+30/10/23 23:53:02| INFO: Dataset sample 0.90 of dataset imdb finished [took 25.4588s]
+30/10/23 23:53:02| INFO: Dataset sample 0.80 of dataset imdb started
+30/10/23 23:53:20| INFO: ref finished [took 16.3699s]
+30/10/23 23:53:25| INFO: atc_ne finished [took 20.5069s]
+30/10/23 23:53:25| INFO: atc_mc finished [took 20.7398s]
+30/10/23 23:53:38| INFO: mul_sld finished [took 35.3572s]
+30/10/23 23:53:45| INFO: mul_sld_bcts finished [took 41.8712s]
+30/10/23 23:56:35| INFO: bin_sld finished [took 212.1758s]
+30/10/23 23:56:36| INFO: bin_sld_bcts finished [took 213.3641s]
+30/10/23 23:57:38| INFO: mul_sld_gs finished [took 274.6360s]
+31/10/23 00:01:13| INFO: bin_sld_gs finished [took 490.0221s]
+31/10/23 00:01:13| INFO: Dataset sample 0.80 of dataset imdb finished [took 491.4099s]
+31/10/23 00:01:13| INFO: Dataset sample 0.50 of dataset imdb started
+31/10/23 00:01:32| INFO: ref finished [took 17.1003s]
+31/10/23 00:01:37| INFO: atc_ne finished [took 21.2159s]
+31/10/23 00:01:37| INFO: atc_mc finished [took 21.6794s]
+31/10/23 00:01:51| INFO: mul_sld finished [took 37.3507s]
+31/10/23 00:02:01| INFO: mul_sld_bcts finished [took 46.7227s]
+31/10/23 00:04:46| INFO: bin_sld finished [took 211.9902s]
+31/10/23 00:04:48| INFO: bin_sld_bcts finished [took 213.3398s]
+31/10/23 00:05:55| INFO: mul_sld_gs finished [took 279.4401s]
+31/10/23 00:08:56| INFO: bin_sld_gs finished [took 461.6571s]
+31/10/23 00:08:56| INFO: Dataset sample 0.50 of dataset imdb finished [took 462.8616s]
+31/10/23 00:08:56| INFO: Dataset sample 0.20 of dataset imdb started
+31/10/23 00:09:15| INFO: ref finished [took 17.3643s]
+31/10/23 00:09:20| INFO: atc_mc finished [took 21.0373s]
+31/10/23 00:09:20| INFO: atc_ne finished [took 21.2599s]
+31/10/23 00:09:38| INFO: mul_sld_bcts finished [took 41.0473s]
+31/10/23 00:09:41| INFO: mul_sld finished [took 43.7800s]
+31/10/23 00:12:30| INFO: bin_sld_bcts finished [took 212.8639s]
+31/10/23 00:12:32| INFO: bin_sld finished [took 215.5704s]
+31/10/23 00:13:29| INFO: mul_sld_gs finished [took 270.7454s]
+31/10/23 00:19:19| INFO: bin_sld_gs finished [took 621.7089s]
+31/10/23 00:19:19| INFO: Dataset sample 0.20 of dataset imdb finished [took 623.1501s]
+31/10/23 00:19:19| INFO: Dataset sample 0.10 of dataset imdb started
+31/10/23 00:19:24| WARNING: Method mul_sld_gs failed. Exception: a must be greater than 0 unless no samples are taken
+31/10/23 00:19:24| WARNING: Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+31/10/23 00:19:26| WARNING: Method bin_sld_bcts failed. Exception: Cannot have number of splits n_splits=5 greater than the number of samples: n_samples=4.
+31/10/23 00:19:31| WARNING: Method mul_sld_bcts failed. Exception: index 3 is out of bounds for axis 0 with size 3
+31/10/23 00:19:35| INFO: ref finished [took 13.7926s]
+31/10/23 00:19:38| INFO: atc_mc finished [took 16.8128s]
+31/10/23 00:19:39| INFO: atc_ne finished [took 16.9032s]
+31/10/23 00:19:44| INFO: mul_sld finished [took 23.7188s]
+31/10/23 00:21:43| WARNING: Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+31/10/23 00:21:43| INFO: Dataset sample 0.10 of dataset imdb finished [took 143.1001s]
+----------------------------------------------------------------------------------------------------
+31/10/23 01:36:56| INFO: dataset imdb
+31/10/23 01:37:04| INFO: Dataset sample 0.90 of dataset imdb started
+31/10/23 01:37:13| WARNING: Method bin_sld_bcts failed. Exception: fun: nan
+ hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
+ jac: array([ 1.06687127, -0.00373246, 0.00373246])
+ message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
+ nfev: 53
+ nit: 34
+ njev: 53
+ status: 2
+ success: False
+ x: array([ 0.11536329, -12.93833991, 12.93833991])
+31/10/23 01:37:24| INFO: ref finished [took 15.9844s]
+31/10/23 01:37:28| INFO: atc_mc finished [took 19.7000s]
+31/10/23 01:37:28| INFO: atc_ne finished [took 19.4612s]
+31/10/23 01:37:39| INFO: mul_sld finished [took 33.2999s]
+31/10/23 01:37:49| INFO: mul_sld_bcts finished [took 43.1402s]
+31/10/23 01:40:23| INFO: bin_sld finished [took 197.7518s]
+31/10/23 01:41:23| INFO: mul_sld_gs finished [took 256.4496s]
+31/10/23 01:42:49| INFO: bin_sld_gs finished [took 342.7515s]
+31/10/23 01:42:49| INFO: Dataset sample 0.90 of dataset imdb finished [took 344.8637s]
+31/10/23 01:42:49| INFO: Dataset sample 0.50 of dataset imdb started
+31/10/23 01:43:10| INFO: ref finished [took 17.6503s]
+31/10/23 01:43:15| INFO: atc_mc finished [took 21.9510s]
+31/10/23 01:43:15| INFO: atc_ne finished [took 21.5680s]
+31/10/23 01:43:29| INFO: mul_sld finished [took 38.2515s]
+31/10/23 01:43:41| INFO: mul_sld_bcts finished [took 48.9560s]
+31/10/23 01:46:29| INFO: bin_sld_bcts finished [took 217.8464s]
+31/10/23 01:46:29| INFO: bin_sld finished [took 218.6211s]
+31/10/23 01:47:51| INFO: mul_sld_gs finished [took 298.6694s]
+31/10/23 01:50:25| INFO: bin_sld_gs finished [took 452.8300s]
+31/10/23 01:50:25| INFO: Dataset sample 0.50 of dataset imdb finished [took 455.3596s]
+31/10/23 01:50:28| ERROR: Configuration imdb_2prevs failed. Exception: could not broadcast input array from shape (2100,7) into shape (2100,)
+----------------------------------------------------------------------------------------------------
+31/10/23 02:13:21| INFO: dataset imdb
+31/10/23 02:13:29| INFO: Dataset sample 0.90 of dataset imdb started
+31/10/23 02:13:37| WARNING: Method bin_sld_bcts failed. Exception: fun: nan
+ hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
+ jac: array([ 1.06687127, -0.00373246, 0.00373246])
+ message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
+ nfev: 53
+ nit: 34
+ njev: 53
+ status: 2
+ success: False
+ x: array([ 0.11536329, -12.93833991, 12.93833991])
+31/10/23 02:13:48| INFO: ref finished [took 16.5509s]
+31/10/23 02:13:52| INFO: atc_mc finished [took 20.3138s]
+31/10/23 02:13:52| INFO: atc_ne finished [took 20.1191s]
+31/10/23 02:14:02| INFO: mul_sld finished [took 32.5158s]
+31/10/23 02:14:12| INFO: mul_sld_bcts finished [took 42.0654s]
+31/10/23 02:16:44| INFO: bin_sld finished [took 193.9189s]
+31/10/23 02:17:44| INFO: mul_sld_gs finished [took 252.9066s]
+31/10/23 02:19:11| INFO: bin_sld_gs finished [took 339.9813s]
+31/10/23 02:19:11| INFO: Dataset sample 0.90 of dataset imdb finished [took 341.6967s]
+31/10/23 02:19:11| INFO: Dataset sample 0.50 of dataset imdb started
+31/10/23 02:19:30| INFO: ref finished [took 16.1334s]
+31/10/23 02:19:35| INFO: atc_mc finished [took 20.5691s]
+31/10/23 02:19:35| INFO: atc_ne finished [took 20.0126s]
+31/10/23 02:19:49| INFO: mul_sld finished [took 36.4597s]
+31/10/23 02:20:02| INFO: mul_sld_bcts finished [took 48.7131s]
+31/10/23 02:22:38| INFO: bin_sld finished [took 205.8577s]
+31/10/23 02:22:41| INFO: bin_sld_bcts finished [took 208.1999s]
+31/10/23 02:23:58| INFO: mul_sld_gs finished [took 284.9247s]
+31/10/23 02:26:26| INFO: bin_sld_gs finished [took 432.5665s]
+31/10/23 02:26:26| INFO: Dataset sample 0.50 of dataset imdb finished [took 435.0679s]
+----------------------------------------------------------------------------------------------------
+31/10/23 03:05:44| INFO: dataset rcv1_CCAT
+31/10/23 03:05:49| INFO: Dataset sample 0.90 of dataset rcv1_CCAT started
+31/10/23 03:06:59| INFO: kfcv finished [took 59.0143s]
+31/10/23 03:06:59| INFO: ref finished [took 56.9074s]
+31/10/23 03:07:03| INFO: doc_feat finished [took 49.0683s]
+31/10/23 03:07:05| INFO: atc_mc finished [took 59.3988s]
+31/10/23 03:07:07| INFO: atc_ne finished [took 58.0283s]
+31/10/23 03:07:09| INFO: mul_sld finished [took 76.8284s]
+31/10/23 03:07:19| INFO: mul_sld_bcts finished [took 84.0129s]
+31/10/23 03:09:51| INFO: bin_sld_bcts finished [took 237.9395s]
+31/10/23 03:09:53| INFO: bin_sld finished [took 242.1415s]
+31/10/23 03:10:13| INFO: mul_sld_gs finished [took 255.3743s]
+31/10/23 03:13:59| INFO: bin_sld_gs finished [took 483.0217s]
+31/10/23 03:13:59| INFO: Dataset sample 0.90 of dataset rcv1_CCAT finished [took 489.9328s]
+31/10/23 03:13:59| INFO: Dataset sample 0.80 of dataset rcv1_CCAT started
+31/10/23 03:15:04| INFO: ref finished [took 53.0703s]
+31/10/23 03:15:05| INFO: kfcv finished [took 55.9779s]
+31/10/23 03:15:05| INFO: doc_feat finished [took 48.1315s]
+31/10/23 03:15:10| INFO: atc_mc finished [took 56.8062s]
+31/10/23 03:15:11| INFO: atc_ne finished [took 55.9933s]
+31/10/23 03:15:20| INFO: mul_sld finished [took 77.2840s]
+31/10/23 03:15:25| INFO: mul_sld_bcts finished [took 80.0502s]
+31/10/23 03:17:55| INFO: bin_sld finished [took 233.0173s]
+31/10/23 03:17:55| INFO: bin_sld_bcts finished [took 231.2358s]
+31/10/23 03:18:59| INFO: mul_sld_gs finished [took 291.7573s]
+31/10/23 03:21:50| INFO: bin_sld_gs finished [took 463.8743s]
+31/10/23 03:21:50| INFO: Dataset sample 0.80 of dataset rcv1_CCAT finished [took 470.4706s]
+31/10/23 03:21:50| INFO: Dataset sample 0.70 of dataset rcv1_CCAT started
+31/10/23 03:22:52| INFO: doc_feat finished [took 46.9563s]
+31/10/23 03:22:53| INFO: ref finished [took 52.8185s]
+31/10/23 03:22:54| INFO: kfcv finished [took 55.3202s]
+31/10/23 03:22:57| INFO: atc_mc finished [took 55.1482s]
+31/10/23 03:22:58| INFO: atc_ne finished [took 54.7420s]
+31/10/23 03:23:09| INFO: mul_sld finished [took 76.8111s]
+31/10/23 03:23:14| INFO: mul_sld_bcts finished [took 80.0460s]
+31/10/23 03:25:43| INFO: bin_sld finished [took 231.7146s]
+31/10/23 03:25:44| INFO: bin_sld_bcts finished [took 230.9954s]
+31/10/23 03:26:53| INFO: mul_sld_gs finished [took 296.5824s]
+31/10/23 03:29:12| INFO: bin_sld_gs finished [took 437.2666s]
+31/10/23 03:29:12| INFO: Dataset sample 0.70 of dataset rcv1_CCAT finished [took 442.6584s]
+31/10/23 03:29:12| INFO: Dataset sample 0.60 of dataset rcv1_CCAT started
+31/10/23 03:30:14| INFO: doc_feat finished [took 47.2841s]
+31/10/23 03:30:15| INFO: ref finished [took 52.5819s]
+31/10/23 03:30:16| INFO: kfcv finished [took 54.9735s]
+31/10/23 03:30:19| INFO: atc_mc finished [took 55.5994s]
+31/10/23 03:30:20| INFO: atc_ne finished [took 55.0062s]
+31/10/23 03:30:30| INFO: mul_sld finished [took 75.3263s]
+31/10/23 03:30:37| INFO: mul_sld_bcts finished [took 80.4052s]
+31/10/23 03:33:04| INFO: bin_sld finished [took 229.9416s]
+31/10/23 03:33:05| INFO: bin_sld_bcts finished [took 229.0971s]
+31/10/23 03:34:12| INFO: mul_sld_gs finished [took 292.9916s]
+31/10/23 03:37:15| INFO: bin_sld_gs finished [took 477.2157s]
+31/10/23 03:37:15| INFO: Dataset sample 0.60 of dataset rcv1_CCAT finished [took 482.5150s]
+31/10/23 03:37:15| INFO: Dataset sample 0.50 of dataset rcv1_CCAT started
+31/10/23 03:38:17| INFO: doc_feat finished [took 47.6798s]
+31/10/23 03:38:17| INFO: ref finished [took 52.2283s]
+31/10/23 03:38:18| INFO: kfcv finished [took 54.3535s]
+31/10/23 03:38:22| INFO: atc_mc finished [took 55.4316s]
+31/10/23 03:38:23| INFO: atc_ne finished [took 55.3697s]
+31/10/23 03:38:32| INFO: mul_sld finished [took 74.3762s]
+31/10/23 03:38:39| INFO: mul_sld_bcts finished [took 79.7216s]
+31/10/23 03:41:05| INFO: bin_sld finished [took 228.4963s]
+31/10/23 03:41:08| INFO: bin_sld_bcts finished [took 230.0901s]
+31/10/23 03:42:09| INFO: mul_sld_gs finished [took 287.8477s]
+31/10/23 03:45:08| INFO: bin_sld_gs finished [took 467.2633s]
+31/10/23 03:45:08| INFO: Dataset sample 0.50 of dataset rcv1_CCAT finished [took 472.6090s]
+31/10/23 03:45:08| INFO: Dataset sample 0.40 of dataset rcv1_CCAT started
+31/10/23 03:46:08| INFO: doc_feat finished [took 47.0674s]
+31/10/23 03:46:09| INFO: ref finished [took 51.5844s]
+31/10/23 03:46:09| INFO: kfcv finished [took 53.6481s]
+31/10/23 03:46:14| INFO: atc_mc finished [took 55.3679s]
+31/10/23 03:46:14| INFO: atc_ne finished [took 54.6174s]
+31/10/23 03:46:21| INFO: mul_sld finished [took 71.5925s]
+31/10/23 03:46:29| INFO: mul_sld_bcts finished [took 77.5938s]
+31/10/23 03:48:55| INFO: bin_sld finished [took 226.3217s]
+31/10/23 03:48:57| INFO: bin_sld_bcts finished [took 226.5561s]
+31/10/23 03:50:04| INFO: mul_sld_gs finished [took 289.8958s]
+31/10/23 03:53:13| INFO: bin_sld_gs finished [took 479.9650s]
+31/10/23 03:53:13| INFO: Dataset sample 0.40 of dataset rcv1_CCAT finished [took 485.0438s]
+31/10/23 03:53:13| INFO: Dataset sample 0.30 of dataset rcv1_CCAT started
+31/10/23 03:54:15| INFO: doc_feat finished [took 47.1959s]
+31/10/23 03:54:16| INFO: ref finished [took 52.7452s]
+31/10/23 03:54:17| INFO: kfcv finished [took 55.3715s]
+31/10/23 03:54:20| INFO: atc_mc finished [took 55.5749s]
+31/10/23 03:54:21| INFO: atc_ne finished [took 54.8719s]
+31/10/23 03:54:29| INFO: mul_sld finished [took 74.1932s]
+31/10/23 03:54:37| INFO: mul_sld_bcts finished [took 80.1150s]
+31/10/23 03:57:01| INFO: bin_sld finished [took 227.2338s]
+31/10/23 03:57:06| INFO: bin_sld_bcts finished [took 229.7342s]
+31/10/23 03:58:13| INFO: mul_sld_gs finished [took 293.4750s]
+31/10/23 04:00:50| INFO: bin_sld_gs finished [took 451.3322s]
+31/10/23 04:00:50| INFO: Dataset sample 0.30 of dataset rcv1_CCAT finished [took 456.9583s]
+31/10/23 04:00:50| INFO: Dataset sample 0.20 of dataset rcv1_CCAT started
+31/10/23 04:01:54| INFO: doc_feat finished [took 48.9670s]
+31/10/23 04:01:54| INFO: ref finished [took 54.3281s]
+31/10/23 04:01:55| INFO: kfcv finished [took 57.0798s]
+31/10/23 04:01:59| INFO: atc_mc finished [took 57.5663s]
+31/10/23 04:02:00| INFO: atc_ne finished [took 57.1756s]
+31/10/23 04:02:07| INFO: mul_sld finished [took 74.8552s]
+31/10/23 04:02:14| INFO: mul_sld_bcts finished [took 79.8097s]
+31/10/23 04:04:43| INFO: bin_sld finished [took 231.6926s]
+31/10/23 04:04:43| INFO: bin_sld_bcts finished [took 229.9267s]
+31/10/23 04:05:23| INFO: mul_sld_gs finished [took 266.8226s]
+31/10/23 04:08:36| INFO: bin_sld_gs finished [took 460.9384s]
+31/10/23 04:08:36| INFO: Dataset sample 0.20 of dataset rcv1_CCAT finished [took 466.5653s]
+31/10/23 04:08:36| INFO: Dataset sample 0.10 of dataset rcv1_CCAT started
+31/10/23 04:08:46| WARNING: Method mul_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+31/10/23 04:08:46| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+31/10/23 04:08:55| WARNING: Method mul_sld_bcts failed. Exception: fun: nan
+ hess_inv: <5x5 LbfgsInvHessProduct with dtype=float64>
+ jac: array([nan, nan, nan, nan, nan])
+ message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
+ nfev: 21
+ nit: 0
+ njev: 21
+ status: 2
+ success: False
+ x: array([1., 0., 0., 0., 0.])
+31/10/23 04:09:33| INFO: doc_feat finished [took 42.6167s]
+31/10/23 04:09:33| INFO: ref finished [took 46.6961s]
+31/10/23 04:09:33| INFO: kfcv finished [took 48.7570s]
+31/10/23 04:09:37| INFO: atc_mc finished [took 49.6198s]
+31/10/23 04:09:38| INFO: atc_ne finished [took 49.1195s]
+31/10/23 04:09:42| INFO: mul_sld finished [took 63.1364s]
+31/10/23 04:11:02| WARNING: Method bin_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+31/10/23 04:12:05| INFO: bin_sld finished [took 207.4063s]
+31/10/23 04:12:05| INFO: Dataset sample 0.10 of dataset rcv1_CCAT finished [took 208.7423s]
+31/10/23 04:12:16| ERROR: Configuration rcv1_CCAT_9prevs failed. Exception: 'DatasetReport' object has no attribute 'fit_scores'
+----------------------------------------------------------------------------------------------------
+31/10/23 11:30:20| INFO: dataset rcv1_CCAT
+31/10/23 11:30:26| INFO: Dataset sample 0.90 of dataset rcv1_CCAT started
+31/10/23 11:31:32| INFO: doc_feat finished [took 48.1486s]
+31/10/23 11:31:32| INFO: ref finished [took 53.9235s]
+31/10/23 11:31:33| INFO: kfcv finished [took 56.4175s]
+31/10/23 11:31:37| INFO: atc_mc finished [took 57.2963s]
+31/10/23 11:31:39| INFO: atc_ne finished [took 56.1470s]
+31/10/23 11:31:43| INFO: mul_sld finished [took 74.0703s]
+31/10/23 11:31:50| INFO: mul_sld_bcts finished [took 78.8253s]
+31/10/23 11:34:16| INFO: bin_sld_bcts finished [took 225.7409s]
+31/10/23 11:34:18| INFO: bin_sld finished [took 229.9705s]
+31/10/23 11:34:42| INFO: mul_sld_gs finished [took 247.4756s]
+31/10/23 11:38:30| INFO: bin_sld_gs finished [took 477.2173s]
+31/10/23 11:38:30| INFO: Dataset sample 0.90 of dataset rcv1_CCAT finished [took 483.7632s]
+31/10/23 11:38:30| INFO: Dataset sample 0.80 of dataset rcv1_CCAT started
+31/10/23 11:39:32| INFO: doc_feat finished [took 47.0343s]
+31/10/23 11:39:33| INFO: ref finished [took 52.5674s]
+31/10/23 11:39:33| INFO: kfcv finished [took 54.5521s]
+31/10/23 11:39:38| INFO: atc_mc finished [took 55.5394s]
+31/10/23 11:39:38| INFO: atc_ne finished [took 54.9616s]
+31/10/23 11:39:48| INFO: mul_sld finished [took 75.9068s]
+31/10/23 11:39:53| INFO: mul_sld_bcts finished [took 78.1581s]
+31/10/23 11:42:22| INFO: bin_sld finished [took 230.5536s]
+31/10/23 11:42:23| INFO: bin_sld_bcts finished [took 229.2262s]
+31/10/23 11:43:29| INFO: mul_sld_gs finished [took 291.7013s]
+31/10/23 11:46:14| INFO: bin_sld_gs finished [took 457.9059s]
+31/10/23 11:46:14| INFO: Dataset sample 0.80 of dataset rcv1_CCAT finished [took 463.5174s]
+31/10/23 11:46:14| INFO: Dataset sample 0.70 of dataset rcv1_CCAT started
+31/10/23 11:47:17| INFO: doc_feat finished [took 46.4490s]
+31/10/23 11:47:17| INFO: ref finished [took 52.6852s]
+31/10/23 11:47:17| INFO: kfcv finished [took 55.0158s]
+31/10/23 11:47:21| INFO: atc_mc finished [took 55.4861s]
+31/10/23 11:47:22| INFO: atc_ne finished [took 54.9236s]
+31/10/23 11:47:32| INFO: mul_sld finished [took 75.5717s]
+31/10/23 11:47:38| INFO: mul_sld_bcts finished [took 80.0893s]
+31/10/23 11:50:02| INFO: bin_sld finished [took 226.8402s]
+31/10/23 11:50:05| INFO: bin_sld_bcts finished [took 227.7311s]
+31/10/23 11:51:15| INFO: mul_sld_gs finished [took 294.0087s]
+31/10/23 11:53:36| INFO: bin_sld_gs finished [took 436.3031s]
+31/10/23 11:53:36| INFO: Dataset sample 0.70 of dataset rcv1_CCAT finished [took 441.8200s]
+31/10/23 11:53:36| INFO: Dataset sample 0.60 of dataset rcv1_CCAT started
+31/10/23 11:54:37| INFO: doc_feat finished [took 47.1550s]
+31/10/23 11:54:38| INFO: ref finished [took 52.2980s]
+31/10/23 11:54:39| INFO: kfcv finished [took 54.5489s]
+31/10/23 11:54:42| INFO: atc_mc finished [took 55.2076s]
+31/10/23 11:54:43| INFO: atc_ne finished [took 54.6137s]
+31/10/23 11:54:53| INFO: mul_sld finished [took 74.8407s]
+31/10/23 11:54:59| INFO: mul_sld_bcts finished [took 79.4977s]
+31/10/23 11:57:24| INFO: bin_sld finished [took 226.9209s]
+31/10/23 11:57:26| INFO: bin_sld_bcts finished [took 227.3112s]
+31/10/23 11:58:29| INFO: mul_sld_gs finished [took 286.1947s]
+31/10/23 12:01:41| INFO: bin_sld_gs finished [took 479.8610s]
+31/10/23 12:01:41| INFO: Dataset sample 0.60 of dataset rcv1_CCAT finished [took 485.3472s]
+31/10/23 12:01:41| INFO: Dataset sample 0.50 of dataset rcv1_CCAT started
+31/10/23 12:02:42| INFO: doc_feat finished [took 46.7340s]
+31/10/23 12:02:42| INFO: ref finished [took 51.5482s]
+31/10/23 12:02:43| INFO: kfcv finished [took 53.9559s]
+31/10/23 12:02:47| INFO: atc_mc finished [took 54.7558s]
+31/10/23 12:02:48| INFO: atc_ne finished [took 54.5216s]
+31/10/23 12:02:57| INFO: mul_sld finished [took 73.4013s]
+31/10/23 12:03:04| INFO: mul_sld_bcts finished [took 78.9197s]
+31/10/23 12:05:30| INFO: bin_sld finished [took 227.3887s]
+31/10/23 12:05:31| INFO: bin_sld_bcts finished [took 226.6540s]
+31/10/23 12:06:37| INFO: mul_sld_gs finished [took 289.2631s]
+31/10/23 12:09:30| INFO: bin_sld_gs finished [took 463.2754s]
+31/10/23 12:09:30| INFO: Dataset sample 0.50 of dataset rcv1_CCAT finished [took 468.6356s]
+31/10/23 12:09:30| INFO: Dataset sample 0.40 of dataset rcv1_CCAT started
+31/10/23 12:10:30| INFO: doc_feat finished [took 47.0178s]
+31/10/23 12:10:31| INFO: ref finished [took 51.8808s]
+31/10/23 12:10:31| INFO: kfcv finished [took 53.6165s]
+31/10/23 12:10:36| INFO: atc_mc finished [took 55.8052s]
+31/10/23 12:10:36| INFO: atc_ne finished [took 55.0541s]
+31/10/23 12:10:44| INFO: mul_sld finished [took 72.1431s]
+31/10/23 12:10:52| INFO: mul_sld_bcts finished [took 78.0435s]
+31/10/23 12:13:18| INFO: bin_sld finished [took 227.6364s]
+31/10/23 12:13:20| INFO: bin_sld_bcts finished [took 227.4485s]
+31/10/23 12:14:23| INFO: mul_sld_gs finished [took 287.2824s]
+31/10/23 12:17:20| INFO: bin_sld_gs finished [took 465.4084s]
+31/10/23 12:17:20| INFO: Dataset sample 0.40 of dataset rcv1_CCAT finished [took 470.5362s]
+31/10/23 12:17:20| INFO: Dataset sample 0.30 of dataset rcv1_CCAT started
+31/10/23 12:18:22| INFO: doc_feat finished [took 46.7203s]
+31/10/23 12:18:24| INFO: ref finished [took 52.8941s]
+31/10/23 12:18:24| INFO: kfcv finished [took 55.1602s]
+31/10/23 12:18:27| INFO: atc_mc finished [took 55.1296s]
+31/10/23 12:18:29| INFO: atc_ne finished [took 54.8176s]
+31/10/23 12:18:36| INFO: mul_sld finished [took 73.6368s]
+31/10/23 12:18:44| INFO: mul_sld_bcts finished [took 79.2444s]
+31/10/23 12:21:09| INFO: bin_sld finished [took 227.4633s]
+31/10/23 12:21:11| INFO: bin_sld_bcts finished [took 227.8848s]
+31/10/23 12:22:18| INFO: mul_sld_gs finished [took 290.8750s]
+31/10/23 12:25:01| INFO: bin_sld_gs finished [took 455.0492s]
+31/10/23 12:25:01| INFO: Dataset sample 0.30 of dataset rcv1_CCAT finished [took 460.7077s]
+31/10/23 12:25:01| INFO: Dataset sample 0.20 of dataset rcv1_CCAT started
+31/10/23 12:26:04| INFO: doc_feat finished [took 48.7419s]
+31/10/23 12:26:05| INFO: ref finished [took 53.9956s]
+31/10/23 12:26:06| INFO: kfcv finished [took 56.7159s]
+31/10/23 12:26:10| INFO: atc_mc finished [took 57.0141s]
+31/10/23 12:26:11| INFO: atc_ne finished [took 56.6235s]
+31/10/23 12:26:18| INFO: mul_sld finished [took 74.9361s]
+31/10/23 12:26:24| INFO: mul_sld_bcts finished [took 78.6411s]
+31/10/23 12:28:51| INFO: bin_sld finished [took 228.5964s]
+31/10/23 12:28:51| INFO: bin_sld_bcts finished [took 226.9077s]
+31/10/23 12:29:34| INFO: mul_sld_gs finished [took 265.9319s]
+31/10/23 12:32:39| INFO: bin_sld_gs finished [took 452.9439s]
+31/10/23 12:32:39| INFO: Dataset sample 0.20 of dataset rcv1_CCAT finished [took 458.4924s]
+31/10/23 12:32:39| INFO: Dataset sample 0.10 of dataset rcv1_CCAT started
+31/10/23 12:32:49| WARNING: Method mul_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+31/10/23 12:32:49| WARNING: Method bin_sld_bcts failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+31/10/23 12:32:57| WARNING: Method mul_sld_bcts failed. Exception: fun: nan
+ hess_inv: <5x5 LbfgsInvHessProduct with dtype=float64>
+ jac: array([nan, nan, nan, nan, nan])
+ message: 'ABNORMAL_TERMINATION_IN_LNSRCH'
+ nfev: 21
+ nit: 0
+ njev: 21
+ status: 2
+ success: False
+ x: array([1., 0., 0., 0., 0.])
+31/10/23 12:33:33| INFO: doc_feat finished [took 40.8855s]
+31/10/23 12:33:34| INFO: ref finished [took 44.7933s]
+31/10/23 12:33:34| INFO: kfcv finished [took 47.0146s]
+31/10/23 12:33:38| INFO: atc_mc finished [took 47.7008s]
+31/10/23 12:33:39| INFO: atc_ne finished [took 47.4664s]
+31/10/23 12:33:42| INFO: mul_sld finished [took 60.5341s]
+31/10/23 12:35:06| WARNING: Method bin_sld_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+31/10/23 12:36:11| INFO: bin_sld finished [took 210.5128s]
+31/10/23 12:36:11| INFO: Dataset sample 0.10 of dataset rcv1_CCAT finished [took 211.7476s]
+----------------------------------------------------------------------------------------------------
+31/10/23 13:07:34| INFO: dataset imdb_2prevs
+31/10/23 13:07:41| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 13:07:55| INFO: ref finished [took 12.2932s]
+31/10/23 13:07:58| INFO: atc_mc finished [took 15.8781s]
+31/10/23 13:07:58| INFO: atc_ne finished [took 15.8256s]
+31/10/23 13:08:08| INFO: mul_sld finished [took 25.6841s]
+31/10/23 13:08:18| INFO: mul_sld_bcts finished [took 35.3498s]
+31/10/23 13:08:18| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 36.3540s]
+31/10/23 13:08:18| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 13:08:32| INFO: ref finished [took 12.8011s]
+31/10/23 13:08:36| INFO: atc_mc finished [took 16.7266s]
+31/10/23 13:08:36| INFO: atc_ne finished [took 16.9577s]
+31/10/23 13:08:49| INFO: mul_sld finished [took 30.1948s]
+31/10/23 13:09:00| INFO: mul_sld_bcts finished [took 41.0998s]
+31/10/23 13:09:00| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 42.6008s]
+31/10/23 13:09:00| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
+----------------------------------------------------------------------------------------------------
+31/10/23 13:10:27| INFO: dataset imdb_2prevs
+31/10/23 13:10:34| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 13:10:47| INFO: ref finished [took 11.6569s]
+31/10/23 13:10:51| INFO: atc_mc finished [took 15.6380s]
+31/10/23 13:10:51| INFO: atc_ne finished [took 15.5430s]
+31/10/23 13:11:00| INFO: mul_sld finished [took 24.9236s]
+31/10/23 13:11:10| INFO: mul_sld_bcts finished [took 34.5252s]
+31/10/23 13:11:10| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 35.4874s]
+31/10/23 13:11:10| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 13:11:23| INFO: ref finished [took 11.5602s]
+31/10/23 13:11:26| INFO: atc_ne finished [took 14.3888s]
+31/10/23 13:11:26| INFO: atc_mc finished [took 14.5643s]
+31/10/23 13:11:39| INFO: mul_sld finished [took 27.8023s]
+31/10/23 13:11:51| INFO: mul_sld_bcts finished [took 39.2892s]
+31/10/23 13:11:51| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.6914s]
+31/10/23 13:11:51| DEBUG: ['COMP_ESTIMATORS', 'DATASET_DIR_UPDATE', 'DATASET_NAME', 'DATASET_N_PREVS', 'DATASET_PREVS', 'DATASET_TARGET', 'METRICS', 'OUT_DIR', 'OUT_DIR_NAME', 'PLOT_DIR_NAME', 'PLOT_ESTIMATORS', 'PLOT_OUT_DIR', 'PLOT_STDEV', 'PROTOCOL_N_PREVS', 'PROTOCOL_REPEATS', 'SAMPLE_SIZE', '__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__slotnames__', '__str__', '__subclasshook__', '__weakref__', '_current_conf', '_default', '_environ__getdict', '_environ__setdict', '_instance', '_keys', 'confs', 'exec', 'get_confs', 'get_plot_confs', 'load_conf', 'plot_confs']
+31/10/23 13:11:51| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
+----------------------------------------------------------------------------------------------------
+31/10/23 13:12:56| INFO: dataset imdb_2prevs
+31/10/23 13:13:03| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 13:13:15| INFO: ref finished [took 11.2578s]
+31/10/23 13:13:19| INFO: atc_mc finished [took 14.7895s]
+31/10/23 13:13:19| INFO: atc_ne finished [took 14.8637s]
+31/10/23 13:13:28| INFO: mul_sld finished [took 24.2622s]
+31/10/23 13:13:38| INFO: mul_sld_bcts finished [took 34.0592s]
+31/10/23 13:13:38| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.9907s]
+31/10/23 13:13:38| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 13:13:52| INFO: ref finished [took 12.2334s]
+31/10/23 13:13:56| INFO: atc_ne finished [took 16.1148s]
+31/10/23 13:13:56| INFO: atc_mc finished [took 16.4135s]
+31/10/23 13:14:10| INFO: mul_sld finished [took 30.7003s]
+31/10/23 13:14:21| INFO: mul_sld_bcts finished [took 41.5915s]
+31/10/23 13:14:21| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 43.0339s]
+31/10/23 13:14:21| ERROR: estimate comparison failed. Exceprion: 'environ' object has no attribute '__getdict'
+----------------------------------------------------------------------------------------------------
+31/10/23 14:05:25| ERROR: estimate comparison failed. Exceprion: 'environ' object has no attribute '_current_conf'
+----------------------------------------------------------------------------------------------------
+31/10/23 14:06:00| INFO: dataset imdb_2prevs
+31/10/23 14:06:07| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:06:19| INFO: ref finished [took 10.8776s]
+31/10/23 14:06:23| INFO: atc_ne finished [took 14.0744s]
+31/10/23 14:06:23| INFO: atc_mc finished [took 14.4000s]
+31/10/23 14:06:33| INFO: mul_sld finished [took 24.5149s]
+31/10/23 14:06:42| INFO: mul_sld_bcts finished [took 33.9116s]
+31/10/23 14:06:42| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.8416s]
+31/10/23 14:06:42| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:06:55| INFO: ref finished [took 11.2125s]
+31/10/23 14:06:59| INFO: atc_ne finished [took 14.9235s]
+31/10/23 14:06:59| INFO: atc_mc finished [took 15.1623s]
+31/10/23 14:07:12| INFO: mul_sld finished [took 28.3463s]
+31/10/23 14:07:23| INFO: mul_sld_bcts finished [took 39.0377s]
+31/10/23 14:07:23| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.4312s]
+31/10/23 14:07:23| ERROR: estimate comparison failed. Exceprion: 'environ' object has no attribute '__getdict'
+----------------------------------------------------------------------------------------------------
+31/10/23 14:09:14| INFO: dataset imdb_2prevs
+31/10/23 14:09:22| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:09:33| INFO: ref finished [took 10.6213s]
+31/10/23 14:09:37| INFO: atc_mc finished [took 14.2004s]
+31/10/23 14:09:37| INFO: atc_ne finished [took 14.2574s]
+31/10/23 14:09:46| INFO: mul_sld finished [took 23.8084s]
+31/10/23 14:09:56| INFO: mul_sld_bcts finished [took 33.4634s]
+31/10/23 14:09:56| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.4023s]
+31/10/23 14:09:56| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:10:09| INFO: ref finished [took 11.0452s]
+31/10/23 14:10:12| INFO: atc_mc finished [took 14.0363s]
+31/10/23 14:10:12| INFO: atc_ne finished [took 14.2492s]
+31/10/23 14:10:25| INFO: mul_sld finished [took 27.1464s]
+31/10/23 14:10:35| INFO: mul_sld_bcts finished [took 37.7957s]
+31/10/23 14:10:35| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 39.1750s]
+31/10/23 14:10:35| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
+----------------------------------------------------------------------------------------------------
+31/10/23 14:14:00| INFO: dataset imdb_2prevs
+31/10/23 14:14:07| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:14:19| INFO: ref finished [took 11.0176s]
+31/10/23 14:14:22| INFO: atc_mc finished [took 14.0422s]
+31/10/23 14:14:23| INFO: atc_ne finished [took 14.2169s]
+31/10/23 14:14:31| INFO: mul_sld finished [took 23.7014s]
+31/10/23 14:14:42| INFO: mul_sld_bcts finished [took 33.7536s]
+31/10/23 14:14:42| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.7003s]
+31/10/23 14:14:42| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:14:54| INFO: ref finished [took 11.0187s]
+31/10/23 14:14:57| INFO: atc_mc finished [took 14.0175s]
+31/10/23 14:14:58| INFO: atc_ne finished [took 14.4154s]
+31/10/23 14:15:10| INFO: mul_sld finished [took 27.5946s]
+31/10/23 14:15:21| INFO: mul_sld_bcts finished [took 38.0464s]
+31/10/23 14:15:21| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 39.4594s]
+31/10/23 14:15:21| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_mc', 'mul_sld', 'atc_ne', 'mul_sld_bcts', 'ref'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': None, 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': None, 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
+31/10/23 14:15:21| ERROR: estimate comparison failed. Exceprion: unsupported operand type(s) for /: 'NoneType' and 'str'
+----------------------------------------------------------------------------------------------------
+31/10/23 14:30:59| INFO: dataset imdb_2prevs
+31/10/23 14:31:10| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:31:33| INFO: ref finished [took 22.2885s]
+31/10/23 14:31:41| INFO: atc_mc finished [took 29.8328s]
+31/10/23 14:31:41| INFO: atc_ne finished [took 30.1421s]
+31/10/23 14:31:46| INFO: mul_sld finished [took 35.8373s]
+31/10/23 14:31:57| INFO: mul_sld_bcts finished [took 46.5130s]
+31/10/23 14:31:57| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 47.5379s]
+31/10/23 14:31:57| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:32:24| INFO: ref finished [took 24.3912s]
+31/10/23 14:32:31| INFO: atc_mc finished [took 31.2488s]
+31/10/23 14:32:31| INFO: atc_ne finished [took 31.5120s]
+31/10/23 14:32:43| INFO: mul_sld finished [took 44.6372s]
+31/10/23 14:32:54| INFO: mul_sld_bcts finished [took 54.5749s]
+31/10/23 14:32:54| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 56.2358s]
+31/10/23 14:32:54| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_ne', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
+31/10/23 14:32:58| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_ne', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
+----------------------------------------------------------------------------------------------------
+31/10/23 14:37:38| INFO: dataset imdb_2prevs
+31/10/23 14:37:45| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:37:58| INFO: ref finished [took 11.4397s]
+31/10/23 14:38:01| INFO: atc_mc finished [took 14.6411s]
+31/10/23 14:38:01| INFO: atc_ne finished [took 14.8218s]
+31/10/23 14:38:11| INFO: mul_sld finished [took 24.4862s]
+31/10/23 14:38:20| INFO: mul_sld_bcts finished [took 33.9900s]
+31/10/23 14:38:20| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 34.9816s]
+31/10/23 14:38:20| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:38:33| INFO: ref finished [took 11.3787s]
+31/10/23 14:38:36| INFO: atc_mc finished [took 14.4366s]
+31/10/23 14:38:36| INFO: atc_ne finished [took 14.3365s]
+31/10/23 14:38:50| INFO: mul_sld finished [took 28.1585s]
+31/10/23 14:39:00| INFO: mul_sld_bcts finished [took 38.5508s]
+31/10/23 14:39:00| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.0193s]
+31/10/23 14:39:00| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld', 'ref', 'mul_sld_bcts', 'atc_mc'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
+31/10/23 14:39:03| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld', 'ref', 'mul_sld_bcts', 'atc_mc'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
+----------------------------------------------------------------------------------------------------
+31/10/23 14:44:15| INFO: dataset imdb_2prevs
+31/10/23 14:44:22| INFO: Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:44:35| INFO: ref finished [took 11.5902s]
+31/10/23 14:44:38| INFO: atc_mc finished [took 14.7915s]
+31/10/23 14:44:39| INFO: atc_ne finished [took 14.8611s]
+31/10/23 14:44:48| INFO: mul_sld finished [took 24.7670s]
+31/10/23 14:44:58| INFO: mul_sld_bcts finished [took 34.3171s]
+31/10/23 14:44:58| INFO: Dataset sample 0.10 of dataset imdb_2prevs finished [took 35.3088s]
+31/10/23 14:44:58| INFO: Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:45:11| INFO: ref finished [took 11.8887s]
+31/10/23 14:45:15| INFO: atc_mc finished [took 15.2624s]
+31/10/23 14:45:15| INFO: atc_ne finished [took 15.2085s]
+31/10/23 14:45:28| INFO: mul_sld finished [took 28.5408s]
+31/10/23 14:45:38| INFO: mul_sld_bcts finished [took 38.9976s]
+31/10/23 14:45:38| INFO: Dataset sample 0.50 of dataset imdb_2prevs finished [took 40.5854s]
+31/10/23 14:45:38| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
+31/10/23 14:45:41| DEBUG: {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['atc_ne', 'mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
+----------------------------------------------------------------------------------------------------
+31/10/23 14:55:18| INFO dataset imdb_2prevs
+31/10/23 14:55:26| INFO Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 14:55:37| INFO ref finished [took 10.1990s]
+31/10/23 14:55:40| INFO atc_mc finished [took 13.4778s]
+31/10/23 14:55:41| INFO atc_ne finished [took 13.5559s]
+31/10/23 14:55:50| INFO mul_sld finished [took 23.0450s]
+31/10/23 14:55:59| INFO mul_sld_bcts finished [took 32.4582s]
+31/10/23 14:55:59| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 33.3679s]
+31/10/23 14:55:59| INFO Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 14:56:11| INFO ref finished [took 10.3415s]
+31/10/23 14:56:14| INFO atc_mc finished [took 13.4638s]
+31/10/23 14:56:14| INFO atc_ne finished [took 13.4791s]
+31/10/23 14:56:27| INFO mul_sld finished [took 26.3298s]
+31/10/23 14:56:38| INFO mul_sld_bcts finished [took 37.2449s]
+31/10/23 14:56:38| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 38.6430s]
+31/10/23 14:56:38| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld', 'atc_ne'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
+31/10/23 14:56:41| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['mul_sld_bcts', 'atc_mc', 'ref', 'mul_sld', 'atc_ne'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
+----------------------------------------------------------------------------------------------------
+31/10/23 15:00:19| INFO dataset imdb_2prevs
+31/10/23 15:00:26| INFO Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 15:00:38| INFO ref finished [took 10.7099s]
+31/10/23 15:00:41| INFO atc_ne finished [took 13.7392s]
+31/10/23 15:00:41| INFO atc_mc finished [took 13.9108s]
+31/10/23 15:00:50| INFO mul_sld finished [took 23.3628s]
+31/10/23 15:01:00| INFO mul_sld_bcts finished [took 33.0440s]
+31/10/23 15:01:00| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 33.9805s]
+31/10/23 15:01:00| INFO Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 15:01:12| INFO ref finished [took 10.7020s]
+31/10/23 15:01:15| INFO atc_mc finished [took 13.9521s]
+31/10/23 15:01:15| INFO atc_ne finished [took 13.8623s]
+31/10/23 15:01:28| INFO mul_sld finished [took 26.8476s]
+31/10/23 15:01:39| INFO mul_sld_bcts finished [took 37.4291s]
+31/10/23 15:01:39| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 38.8721s]
+31/10/23 15:01:39| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['ref', 'atc_mc', 'mul_sld', 'atc_ne', 'mul_sld_bcts'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': True}
+31/10/23 15:01:42| DEBUG {'DATASET_NAME': 'imdb', 'DATASET_TARGET': None, 'METRICS': ['acc'], 'COMP_ESTIMATORS': ['ref', 'atc_mc', 'mul_sld', 'atc_ne', 'mul_sld_bcts'], 'DATASET_N_PREVS': 5, 'DATASET_PREVS': [0.5, 0.1], 'OUT_DIR_NAME': 'output', 'OUT_DIR': WindowsPath('output/imdb_2prevs'), 'PLOT_DIR_NAME': 'plot', 'PLOT_OUT_DIR': WindowsPath('output/imdb_2prevs/plot'), 'DATASET_DIR_UPDATE': False, 'PROTOCOL_N_PREVS': 21, 'PROTOCOL_REPEATS': 100, 'SAMPLE_SIZE': 1000, 'PLOT_ESTIMATORS': ['mul_sld_bcts', 'mul_sld', 'ref', 'atc_mc', 'atc_ne'], 'PLOT_STDEV': False}
+----------------------------------------------------------------------------------------------------
+31/10/23 15:02:43| INFO dataset imdb_2prevs
+31/10/23 15:02:50| INFO Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 15:03:02| INFO ref finished [took 10.5528s]
+31/10/23 15:03:05| INFO atc_mc finished [took 13.7838s]
+31/10/23 15:03:05| INFO atc_ne finished [took 13.6736s]
+31/10/23 15:03:14| INFO mul_sld finished [took 23.2705s]
+31/10/23 15:03:24| INFO mul_sld_bcts finished [took 32.8493s]
+31/10/23 15:03:24| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 33.7917s]
+31/10/23 15:03:24| INFO Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 15:03:36| INFO ref finished [took 10.4338s]
+31/10/23 15:03:39| INFO atc_mc finished [took 13.5140s]
+31/10/23 15:03:39| INFO atc_ne finished [took 13.5920s]
+31/10/23 15:03:52| INFO mul_sld finished [took 26.7677s]
+31/10/23 15:04:03| INFO mul_sld_bcts finished [took 37.2882s]
+31/10/23 15:04:03| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 38.7014s]
+----------------------------------------------------------------------------------------------------
+31/10/23 17:01:56| INFO dataset imdb_2prevs
+31/10/23 17:02:03| INFO Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 17:02:16| INFO ref finished [took 11.7260s]
+31/10/23 17:02:19| INFO atc_mc finished [took 14.9332s]
+31/10/23 17:02:20| INFO atc_ne finished [took 14.9267s]
+31/10/23 17:02:29| INFO mul_sld finished [took 25.0825s]
+31/10/23 17:02:39| INFO mul_sld_bcts finished [took 35.1456s]
+31/10/23 17:02:39| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 36.1167s]
+31/10/23 17:02:39| INFO Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 17:02:53| INFO ref finished [took 12.1990s]
+31/10/23 17:02:57| INFO atc_mc finished [took 15.9130s]
+31/10/23 17:02:57| INFO atc_ne finished [took 15.8122s]
+31/10/23 17:03:10| INFO mul_sld finished [took 29.0681s]
+31/10/23 17:03:21| INFO mul_sld_bcts finished [took 40.0346s]
+31/10/23 17:03:21| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 41.6137s]
+----------------------------------------------------------------------------------------------------
+31/10/23 17:04:35| INFO dataset imdb_2prevs
+31/10/23 17:04:42| INFO Dataset sample 0.10 of dataset imdb_2prevs started
+31/10/23 17:04:56| INFO ref finished [took 11.5027s]
+31/10/23 17:05:00| INFO atc_mc finished [took 15.1600s]
+31/10/23 17:05:00| INFO atc_ne finished [took 15.0072s]
+31/10/23 17:05:09| INFO mul_sld finished [took 24.7931s]
+31/10/23 17:05:19| INFO mul_sld_bcts finished [took 34.6305s]
+31/10/23 17:05:19| INFO Dataset sample 0.10 of dataset imdb_2prevs finished [took 37.1778s]
+31/10/23 17:05:19| INFO Dataset sample 0.50 of dataset imdb_2prevs started
+31/10/23 17:05:33| INFO ref finished [took 12.2649s]
+31/10/23 17:05:36| INFO atc_mc finished [took 15.5987s]
+31/10/23 17:05:37| INFO atc_ne finished [took 15.8214s]
+31/10/23 17:05:50| INFO mul_sld finished [took 29.3523s]
+31/10/23 17:06:00| INFO mul_sld_bcts finished [took 39.8376s]
+31/10/23 17:06:00| INFO Dataset sample 0.50 of dataset imdb_2prevs finished [took 41.2888s]
+----------------------------------------------------------------------------------------------------
+31/10/23 20:19:37| INFO dataset imdb_1prevs
+31/10/23 20:19:48| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+31/10/23 20:20:07| INFO ref finished [took 17.4125s]
+----------------------------------------------------------------------------------------------------
+31/10/23 20:20:50| INFO dataset imdb_1prevs
+31/10/23 20:21:01| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+31/10/23 20:21:19| INFO ref finished [took 17.0717s]
+----------------------------------------------------------------------------------------------------
+31/10/23 20:22:05| INFO dataset imdb_1prevs
+31/10/23 20:22:15| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+31/10/23 20:22:35| INFO ref finished [took 18.4752s]
+----------------------------------------------------------------------------------------------------
+31/10/23 20:23:38| INFO dataset imdb_1prevs
+31/10/23 20:23:48| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+31/10/23 20:24:08| INFO ref finished [took 18.3216s]
+----------------------------------------------------------------------------------------------------
+01/11/23 13:07:19| INFO dataset imdb_1prevs
+01/11/23 13:07:27| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+01/11/23 13:07:27| ERROR Evaluation over imdb_1prevs failed. Exception: 'Invalid estimator: estimator mul_sld_gs does not exist'
+01/11/23 13:07:27| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
+----------------------------------------------------------------------------------------------------
+03/11/23 20:54:19| INFO dataset rcv1_CCAT_9prevs
+03/11/23 20:54:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+03/11/23 20:54:28| WARNING Method mul_sld_gs failed. Exception: Invalid parameter 'quantifier' for estimator EMQ(classifier=LogisticRegression()). Valid parameters are: ['classifier', 'exact_train_prev', 'recalib'].
+03/11/23 20:54:29| WARNING Method mul_sld failed. Exception: evaluation_report() got an unexpected keyword argument 'protocor'
+03/11/23 20:54:30| WARNING Method bin_sld_gs failed. Exception: Invalid parameter 'quantifier' for estimator EMQ(classifier=LogisticRegression()). Valid parameters are: ['classifier', 'exact_train_prev', 'recalib'].
+03/11/23 20:55:09| INFO ref finished [took 38.5179s]
+----------------------------------------------------------------------------------------------------
+03/11/23 21:28:36| INFO dataset rcv1_CCAT_9prevs
+03/11/23 21:28:41| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+03/11/23 21:28:45| WARNING Method mul_sld failed. Exception: evaluation_report() got an unexpected keyword argument 'protocor'
+----------------------------------------------------------------------------------------------------
+03/11/23 21:31:03| INFO dataset rcv1_CCAT_9prevs
+03/11/23 21:31:08| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+03/11/23 21:31:59| INFO ref finished [took 45.6616s]
+03/11/23 21:32:03| INFO atc_mc finished [took 48.4360s]
+03/11/23 21:32:07| INFO atc_ne finished [took 51.0515s]
+03/11/23 21:32:23| INFO mul_sld finished [took 72.9229s]
+03/11/23 21:34:43| INFO bin_sld finished [took 213.9538s]
+03/11/23 21:36:27| INFO mul_sld_gs finished [took 314.9357s]
+03/11/23 21:40:50| INFO bin_sld_gs finished [took 579.2530s]
+03/11/23 21:40:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 582.5876s]
+03/11/23 21:40:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+03/11/23 21:41:39| INFO ref finished [took 43.7409s]
+03/11/23 21:41:43| INFO atc_mc finished [took 46.4580s]
+03/11/23 21:41:44| INFO atc_ne finished [took 46.4267s]
+03/11/23 21:41:54| INFO mul_sld finished [took 61.3005s]
+03/11/23 21:44:18| INFO bin_sld finished [took 206.3680s]
+03/11/23 21:45:59| INFO mul_sld_gs finished [took 304.4726s]
+03/11/23 21:50:33| INFO bin_sld_gs finished [took 579.3455s]
+03/11/23 21:50:33| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 582.4808s]
+03/11/23 21:50:33| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+03/11/23 21:51:22| INFO ref finished [took 43.6853s]
+03/11/23 21:51:26| INFO atc_mc finished [took 47.1366s]
+03/11/23 21:51:30| INFO atc_ne finished [took 49.4868s]
+03/11/23 21:51:34| INFO mul_sld finished [took 59.0964s]
+03/11/23 21:53:59| INFO bin_sld finished [took 205.0248s]
+03/11/23 21:55:50| INFO mul_sld_gs finished [took 312.5630s]
+03/11/23 22:00:27| INFO bin_sld_gs finished [took 591.1460s]
+03/11/23 22:00:27| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 594.3163s]
+03/11/23 22:00:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+03/11/23 22:01:15| INFO ref finished [took 43.3806s]
+03/11/23 22:01:19| INFO atc_mc finished [took 46.6674s]
+03/11/23 22:01:21| INFO atc_ne finished [took 47.1220s]
+03/11/23 22:01:28| INFO mul_sld finished [took 58.6799s]
+03/11/23 22:03:53| INFO bin_sld finished [took 204.7659s]
+03/11/23 22:05:39| INFO mul_sld_gs finished [took 307.8811s]
+03/11/23 22:10:32| INFO bin_sld_gs finished [took 601.9995s]
+03/11/23 22:10:32| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 604.8406s]
+03/11/23 22:10:32| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+03/11/23 22:11:20| INFO ref finished [took 42.8256s]
+03/11/23 22:11:25| INFO atc_mc finished [took 46.9203s]
+03/11/23 22:11:28| INFO atc_ne finished [took 49.3042s]
+03/11/23 22:11:34| INFO mul_sld finished [took 60.2744s]
+03/11/23 22:13:59| INFO bin_sld finished [took 205.7078s]
+03/11/23 22:15:45| INFO mul_sld_gs finished [took 309.0888s]
+03/11/23 22:20:32| INFO bin_sld_gs finished [took 596.5102s]
+03/11/23 22:20:32| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 599.5067s]
+03/11/23 22:20:32| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+03/11/23 22:21:20| INFO ref finished [took 43.1698s]
+03/11/23 22:21:24| INFO atc_mc finished [took 46.5768s]
+03/11/23 22:21:25| INFO atc_ne finished [took 46.3408s]
+03/11/23 22:21:34| INFO mul_sld finished [took 60.8070s]
+03/11/23 22:23:58| INFO bin_sld finished [took 205.3362s]
+03/11/23 22:25:44| INFO mul_sld_gs finished [took 308.1859s]
+03/11/23 22:30:44| INFO bin_sld_gs finished [took 609.5468s]
+03/11/23 22:30:44| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 612.5803s]
+03/11/23 22:30:44| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+03/11/23 22:31:32| INFO ref finished [took 43.2949s]
+03/11/23 22:31:37| INFO atc_mc finished [took 46.3686s]
+03/11/23 22:31:40| INFO atc_ne finished [took 49.2242s]
+03/11/23 22:31:47| INFO mul_sld finished [took 60.9437s]
+03/11/23 22:34:11| INFO bin_sld finished [took 205.9299s]
+03/11/23 22:35:56| INFO mul_sld_gs finished [took 308.2738s]
+03/11/23 22:40:36| INFO bin_sld_gs finished [took 588.7918s]
+03/11/23 22:40:36| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 591.8830s]
+03/11/23 22:40:36| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+03/11/23 22:41:24| INFO ref finished [took 43.3321s]
+03/11/23 22:41:29| INFO atc_mc finished [took 46.8041s]
+03/11/23 22:41:29| INFO atc_ne finished [took 46.5810s]
+03/11/23 22:41:38| INFO mul_sld finished [took 60.2962s]
+03/11/23 22:44:07| INFO bin_sld finished [took 209.6435s]
+03/11/23 22:45:44| INFO mul_sld_gs finished [took 304.4809s]
+03/11/23 22:50:39| INFO bin_sld_gs finished [took 599.5588s]
+03/11/23 22:50:39| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 602.5720s]
+03/11/23 22:50:39| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+03/11/23 22:51:26| INFO ref finished [took 42.4313s]
+03/11/23 22:51:30| INFO atc_mc finished [took 45.5261s]
+03/11/23 22:51:34| INFO atc_ne finished [took 48.4488s]
+03/11/23 22:51:47| INFO mul_sld finished [took 66.4801s]
+03/11/23 22:54:08| INFO bin_sld finished [took 208.4272s]
+03/11/23 22:55:49| INFO mul_sld_gs finished [took 306.4505s]
+03/11/23 23:00:15| INFO bin_sld_gs finished [took 573.7761s]
+03/11/23 23:00:15| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 576.7586s]
+----------------------------------------------------------------------------------------------------
+03/11/23 23:33:15| INFO dataset imdb_1prevs
+03/11/23 23:33:22| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+03/11/23 23:33:22| ERROR Evaluation over imdb_1prevs failed. Exception: 'function' object is not iterable
+03/11/23 23:33:22| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
+----------------------------------------------------------------------------------------------------
+03/11/23 23:34:15| INFO dataset imdb_1prevs
+03/11/23 23:34:23| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+03/11/23 23:34:35| INFO atc_mc finished [took 11.5081s]
+03/11/23 23:34:45| INFO ref finished [took 8.7754s]
+03/11/23 23:34:47| INFO mul_sld finished [took 22.9651s]
+03/11/23 23:34:47| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 23.9721s]
+03/11/23 23:34:47| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: 'ref'
+----------------------------------------------------------------------------------------------------
+03/11/23 23:36:10| INFO dataset imdb_1prevs
+03/11/23 23:36:30| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+03/11/23 23:38:02| INFO atc_mc finished [took 56.2957s]
+03/11/23 23:38:03| INFO mul_sld finished [took 57.6237s]
+03/11/23 23:38:40| INFO ref finished [took 37.7811s]
+03/11/23 23:38:40| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 130.9031s]
+03/11/23 23:38:42| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: 'ref'
+----------------------------------------------------------------------------------------------------
+03/11/23 23:39:32| INFO dataset imdb_1prevs
+03/11/23 23:39:42| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+03/11/23 23:40:08| INFO atc_mc finished [took 24.7110s]
+03/11/23 23:40:23| INFO mul_sld finished [took 40.2345s]
+03/11/23 23:40:26| INFO ref finished [took 17.8417s]
+03/11/23 23:40:26| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 44.8087s]
+----------------------------------------------------------------------------------------------------
+03/11/23 23:41:18| INFO dataset imdb_1prevs
+03/11/23 23:41:28| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+03/11/23 23:41:54| INFO atc_mc finished [took 24.0569s]
+03/11/23 23:42:03| INFO mul_sld finished [took 33.3390s]
+03/11/23 23:42:12| INFO ref finished [took 16.9551s]
+03/11/23 23:42:12| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 43.2484s]
+----------------------------------------------------------------------------------------------------
+04/11/23 00:03:17| ERROR Evaluation over imdb_1prevs failed. Exception: CompEstimatorName_.__init__() missing 1 required positional argument: 'ce'
+04/11/23 00:03:17| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
+----------------------------------------------------------------------------------------------------
+04/11/23 00:03:50| ERROR Evaluation over imdb_1prevs failed. Exception: 'CompEstimator' object has no attribute '_CompEstimatorName___get'
+04/11/23 00:03:50| ERROR Failed while saving configuration imdb_debug of imdb_1prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
+----------------------------------------------------------------------------------------------------
+04/11/23 00:04:42| INFO dataset imdb_1prevs
+04/11/23 00:04:53| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+04/11/23 00:05:13| INFO ref finished [took 19.2363s]
+04/11/23 00:05:20| INFO atc_mc finished [took 26.4278s]
+04/11/23 00:05:29| INFO mul_sld finished [took 35.3110s]
+04/11/23 00:05:29| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 36.4422s]
+----------------------------------------------------------------------------------------------------
+04/11/23 00:19:43| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:19:49| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:19:53| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+04/11/23 00:19:55| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+04/11/23 00:19:57| WARNING Method bin_pacc failed. Exception: PACC.__init__() got an unexpected keyword argument 'recalib'
+04/11/23 00:19:59| WARNING Method mul_pacc failed. Exception: PACC.__init__() got an unexpected keyword argument 'recalib'
+04/11/23 00:20:00| WARNING Method bin_pacc_gs failed. Exception: Invalid parameter 'recalib' for estimator PACC(classifier=LogisticRegression(), n_jobs=1). Valid parameters are: ['classifier', 'n_jobs', 'val_split'].
+04/11/23 00:20:01| WARNING Method mul_pacc_gs failed. Exception: Invalid parameter 'recalib' for estimator PACC(classifier=LogisticRegression(), n_jobs=1). Valid parameters are: ['classifier', 'n_jobs', 'val_split'].
+----------------------------------------------------------------------------------------------------
+04/11/23 00:22:45| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:22:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:22:54| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+04/11/23 00:22:55| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+----------------------------------------------------------------------------------------------------
+04/11/23 00:28:11| INFO dataset rcv1_CCAT_9prevs
+----------------------------------------------------------------------------------------------------
+04/11/23 00:29:39| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:29:45| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:29:49| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+04/11/23 00:29:51| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+04/11/23 00:30:39| WARNING Method mul_pacc_gs failed. Exception: evaluation_report() got an unexpected keyword argument 'method_name'
+04/11/23 00:31:00| INFO ref finished [took 60.5788s]
+04/11/23 00:31:09| INFO atc_mc finished [took 64.6156s]
+04/11/23 00:31:09| INFO mul_pacc finished [took 75.1821s]
+04/11/23 00:31:12| INFO atc_ne finished [took 62.8665s]
+04/11/23 00:31:24| INFO mul_sld finished [took 96.8624s]
+----------------------------------------------------------------------------------------------------
+04/11/23 00:33:26| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:33:31| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:33:35| WARNING Method bin_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+04/11/23 00:33:37| WARNING Method mul_sld_qgs failed. Exception: X has 47236 features, but LogisticRegression is expecting 47238 features as input.
+----------------------------------------------------------------------------------------------------
+04/11/23 00:38:42| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:38:48| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:38:51| WARNING Method bin_sld_qgs failed. Exception: ExtendedCollection.extend_collection() missing 1 required positional argument: 'pred_proba'
+04/11/23 00:38:52| WARNING Method mul_sld_qgs failed. Exception: ExtendedCollection.extend_collection() missing 1 required positional argument: 'pred_proba'
+04/11/23 00:39:41| WARNING Method mul_pacc_gs failed. Exception: evaluation_report() got an unexpected keyword argument 'method_name'
+----------------------------------------------------------------------------------------------------
+04/11/23 00:46:33| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:46:39| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:46:40| WARNING Method bin_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:41| WARNING Method mul_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:42| WARNING Method bin_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
+04/11/23 00:46:43| WARNING Method mul_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
+04/11/23 00:46:44| WARNING Method bin_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:45| WARNING Method mul_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:46| WARNING Method bin_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:47| WARNING Method mul_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:47| WARNING Method bin_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:46:48| WARNING Method mul_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:27| INFO ref finished [took 37.5294s]
+04/11/23 00:47:31| INFO atc_mc finished [took 40.5777s]
+04/11/23 00:47:32| INFO atc_ne finished [took 40.7565s]
+04/11/23 00:47:32| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 52.8106s]
+04/11/23 00:47:32| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:47:33| WARNING Method bin_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:34| WARNING Method mul_sld failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:35| WARNING Method bin_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
+04/11/23 00:47:36| WARNING Method mul_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
+04/11/23 00:47:37| WARNING Method bin_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:38| WARNING Method mul_sld_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:39| WARNING Method bin_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:39| WARNING Method mul_pacc failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:40| WARNING Method bin_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+04/11/23 00:47:41| WARNING Method mul_pacc_gs failed. Exception: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+----------------------------------------------------------------------------------------------------
+04/11/23 00:48:05| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:48:10| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:48:13| WARNING Method bin_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
+04/11/23 00:48:14| WARNING Method mul_sld_qgs failed. Exception: 'LogisticRegression' object has no attribute 'pred_proba'
+----------------------------------------------------------------------------------------------------
+04/11/23 00:49:18| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:49:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:49:27| WARNING Method bin_sld_qgs failed. Exception: GridSearchQ.__init__() missing 1 required positional argument: 'model'
+04/11/23 00:49:28| WARNING Method mul_sld_qgs failed. Exception: X has 47238 features, but LogisticRegression is expecting 47236 features as input.
+----------------------------------------------------------------------------------------------------
+04/11/23 00:51:27| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:51:32| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:51:36| WARNING Method bin_sld_qgs failed. Exception: X has 47238 features, but LogisticRegression is expecting 47236 features as input.
+04/11/23 00:51:37| WARNING Method mul_sld_qgs failed. Exception: X has 47238 features, but LogisticRegression is expecting 47236 features as input.
+----------------------------------------------------------------------------------------------------
+04/11/23 00:54:47| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:54:53| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 00:54:57| WARNING Method bin_sld_qgs failed. Exception: a must be greater than 0 unless no samples are taken
+04/11/23 00:54:58| WARNING Method mul_sld_qgs failed. Exception: a must be greater than 0 unless no samples are taken
+----------------------------------------------------------------------------------------------------
+04/11/23 00:58:47| INFO dataset rcv1_CCAT_9prevs
+04/11/23 00:58:52| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 01:00:04| INFO ref finished [took 61.6328s]
+04/11/23 01:00:11| INFO atc_mc finished [took 65.4916s]
+04/11/23 01:00:13| INFO atc_ne finished [took 63.2288s]
+04/11/23 01:00:14| INFO mul_pacc finished [took 75.5101s]
+04/11/23 01:00:30| INFO mul_sld finished [took 96.6656s]
+04/11/23 01:00:41| INFO mul_pacc_gs finished [took 99.7211s]
+04/11/23 01:03:02| INFO bin_pacc finished [took 244.6260s]
+04/11/23 01:03:07| INFO bin_sld finished [took 254.3478s]
+04/11/23 01:04:51| INFO mul_sld_gs finished [took 354.7477s]
+04/11/23 01:05:02| INFO bin_pacc_gs finished [took 362.1808s]
+04/11/23 01:09:24| INFO bin_sld_gs finished [took 628.6714s]
+04/11/23 01:09:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 631.8421s]
+04/11/23 01:09:24| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+04/11/23 01:10:39| INFO ref finished [took 63.5158s]
+04/11/23 01:10:44| INFO atc_mc finished [took 66.4279s]
+04/11/23 01:10:46| INFO mul_pacc finished [took 75.3281s]
+04/11/23 01:10:47| INFO atc_ne finished [took 67.5374s]
+04/11/23 01:10:52| INFO mul_sld finished [took 86.6592s]
+04/11/23 01:11:19| INFO mul_pacc_gs finished [took 104.6374s]
+04/11/23 01:13:58| INFO bin_sld finished [took 273.4932s]
+04/11/23 01:14:01| INFO bin_pacc finished [took 271.3481s]
+04/11/23 01:15:42| INFO mul_sld_gs finished [took 374.2416s]
+04/11/23 01:16:01| INFO bin_pacc_gs finished [took 388.0839s]
+04/11/23 01:20:29| INFO bin_sld_gs finished [took 661.9729s]
+04/11/23 01:20:29| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 665.2874s]
+04/11/23 01:20:29| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+04/11/23 01:21:46| INFO ref finished [took 63.8544s]
+04/11/23 01:21:50| INFO atc_mc finished [took 66.6917s]
+04/11/23 01:21:52| INFO atc_ne finished [took 65.0860s]
+04/11/23 01:21:53| INFO mul_pacc finished [took 77.2630s]
+04/11/23 01:21:55| INFO mul_sld finished [took 83.3146s]
+04/11/23 01:22:23| INFO mul_pacc_gs finished [took 102.3761s]
+04/11/23 01:24:47| INFO bin_pacc finished [took 252.0964s]
+04/11/23 01:24:49| INFO bin_sld finished [took 258.6998s]
+04/11/23 01:26:37| INFO mul_sld_gs finished [took 363.7500s]
+04/11/23 01:26:49| INFO bin_pacc_gs finished [took 370.5817s]
+04/11/23 01:31:27| INFO bin_sld_gs finished [took 654.3921s]
+04/11/23 01:31:27| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 658.0041s]
+04/11/23 01:31:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+04/11/23 01:32:33| INFO ref finished [took 55.7749s]
+04/11/23 01:32:38| INFO atc_mc finished [took 59.4190s]
+04/11/23 01:32:40| INFO atc_ne finished [took 59.5155s]
+04/11/23 01:32:42| INFO mul_pacc finished [took 68.8994s]
+04/11/23 01:32:44| INFO mul_sld finished [took 74.6470s]
+04/11/23 01:33:09| INFO mul_pacc_gs finished [took 92.6473s]
+04/11/23 01:35:32| INFO bin_pacc finished [took 239.7541s]
+04/11/23 01:35:34| INFO bin_sld finished [took 245.7504s]
+04/11/23 01:37:19| INFO mul_sld_gs finished [took 348.1188s]
+04/11/23 01:37:30| INFO bin_pacc_gs finished [took 355.4729s]
+04/11/23 01:42:07| INFO bin_sld_gs finished [took 636.8598s]
+04/11/23 01:42:07| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 639.9201s]
+04/11/23 01:42:07| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+04/11/23 01:43:14| INFO ref finished [took 56.1531s]
+04/11/23 01:43:19| INFO atc_mc finished [took 59.7473s]
+04/11/23 01:43:20| INFO atc_ne finished [took 59.0606s]
+04/11/23 01:43:23| INFO mul_pacc finished [took 69.4266s]
+04/11/23 01:43:25| INFO mul_sld finished [took 76.3328s]
+04/11/23 01:43:49| INFO mul_pacc_gs finished [took 92.3926s]
+04/11/23 01:46:05| INFO bin_pacc finished [took 233.1877s]
+04/11/23 01:46:08| INFO bin_sld finished [took 239.8757s]
+04/11/23 01:47:51| INFO mul_sld_gs finished [took 339.5911s]
+04/11/23 01:48:00| INFO bin_pacc_gs finished [took 345.7788s]
+04/11/23 01:52:44| INFO bin_sld_gs finished [took 633.8407s]
+04/11/23 01:52:44| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 637.0648s]
+04/11/23 01:52:44| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+04/11/23 01:53:52| INFO ref finished [took 57.4958s]
+04/11/23 01:53:57| INFO atc_mc finished [took 60.9998s]
+04/11/23 01:53:58| INFO atc_ne finished [took 60.4847s]
+04/11/23 01:54:01| INFO mul_pacc finished [took 70.5216s]
+04/11/23 01:54:04| INFO mul_sld finished [took 78.2910s]
+04/11/23 01:54:27| INFO mul_pacc_gs finished [took 94.4726s]
+04/11/23 01:56:48| INFO bin_pacc finished [took 238.5969s]
+04/11/23 01:56:50| INFO bin_sld finished [took 244.5679s]
+04/11/23 01:58:31| INFO mul_sld_gs finished [took 342.4843s]
+04/11/23 01:58:44| INFO bin_pacc_gs finished [took 352.8264s]
+04/11/23 02:03:32| INFO bin_sld_gs finished [took 644.7046s]
+04/11/23 02:03:32| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 647.8055s]
+04/11/23 02:03:32| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+04/11/23 02:04:37| INFO ref finished [took 55.4488s]
+04/11/23 02:04:42| INFO atc_mc finished [took 59.2634s]
+04/11/23 02:04:44| INFO atc_ne finished [took 59.1371s]
+04/11/23 02:04:46| INFO mul_pacc finished [took 68.0960s]
+04/11/23 02:04:50| INFO mul_sld finished [took 76.4282s]
+04/11/23 02:05:12| INFO mul_pacc_gs finished [took 91.7735s]
+04/11/23 02:07:30| INFO bin_pacc finished [took 232.7650s]
+04/11/23 02:07:36| INFO bin_sld finished [took 242.4077s]
+04/11/23 02:09:14| INFO mul_sld_gs finished [took 338.1418s]
+04/11/23 02:09:26| INFO bin_pacc_gs finished [took 347.2033s]
+04/11/23 02:13:59| INFO bin_sld_gs finished [took 624.6098s]
+04/11/23 02:13:59| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 627.7979s]
+04/11/23 02:13:59| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+04/11/23 02:15:05| INFO ref finished [took 55.1962s]
+04/11/23 02:15:10| INFO atc_mc finished [took 59.0907s]
+04/11/23 02:15:11| INFO atc_ne finished [took 59.1531s]
+04/11/23 02:15:13| INFO mul_pacc finished [took 67.6705s]
+04/11/23 02:15:17| INFO mul_sld finished [took 75.4559s]
+04/11/23 02:15:41| INFO mul_pacc_gs finished [took 92.4901s]
+04/11/23 02:17:59| INFO bin_pacc finished [took 233.8600s]
+04/11/23 02:18:04| INFO bin_sld finished [took 243.2382s]
+04/11/23 02:19:40| INFO mul_sld_gs finished [took 336.0961s]
+04/11/23 02:19:51| INFO bin_pacc_gs finished [took 344.4075s]
+04/11/23 02:24:30| INFO bin_sld_gs finished [took 627.6209s]
+04/11/23 02:24:30| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 630.8251s]
+04/11/23 02:24:30| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+04/11/23 02:25:35| INFO ref finished [took 54.8513s]
+04/11/23 02:25:40| INFO atc_mc finished [took 58.8528s]
+04/11/23 02:25:41| INFO atc_ne finished [took 58.6035s]
+04/11/23 02:25:43| INFO mul_pacc finished [took 66.9030s]
+04/11/23 02:25:57| INFO mul_sld finished [took 84.2072s]
+04/11/23 02:26:10| INFO mul_pacc_gs finished [took 91.0973s]
+04/11/23 02:28:31| INFO bin_pacc finished [took 235.7331s]
+04/11/23 02:28:35| INFO bin_sld finished [took 243.6260s]
+04/11/23 02:30:09| INFO mul_sld_gs finished [took 334.4842s]
+04/11/23 02:30:22| INFO bin_pacc_gs finished [took 344.6874s]
+04/11/23 02:34:46| INFO bin_sld_gs finished [took 612.1219s]
+04/11/23 02:34:46| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 615.2004s]
+----------------------------------------------------------------------------------------------------
+04/11/23 02:57:35| INFO dataset rcv1_CCAT_9prevs
+04/11/23 02:57:39| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 02:57:47| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 02:58:59| INFO ref finished [took 64.5948s]
+04/11/23 02:59:06| INFO atc_mc finished [took 69.5808s]
+04/11/23 02:59:12| INFO mul_pacc finished [took 82.8518s]
+04/11/23 02:59:13| INFO atc_ne finished [took 72.1303s]
+04/11/23 02:59:26| INFO mul_sld finished [took 103.4201s]
+04/11/23 02:59:30| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+04/11/23 02:59:41| INFO mul_pacc_gs finished [took 109.4672s]
+04/11/23 03:01:59| INFO bin_pacc finished [took 251.3945s]
+04/11/23 03:02:02| INFO bin_sld finished [took 260.0226s]
+04/11/23 03:03:35| INFO mul_sld_gs finished [took 350.1705s]
+04/11/23 03:03:48| INFO bin_pacc_gs finished [took 357.9668s]
+04/11/23 03:07:59| INFO bin_sld_gs finished [took 615.8087s]
+04/11/23 03:07:59| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 620.4985s]
+04/11/23 03:07:59| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+04/11/23 03:08:06| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 03:09:17| INFO ref finished [took 64.4692s]
+04/11/23 03:09:25| INFO atc_mc finished [took 71.3766s]
+04/11/23 03:09:27| INFO atc_ne finished [took 71.0947s]
+04/11/23 03:09:28| INFO mul_pacc finished [took 80.0201s]
+04/11/23 03:09:31| INFO mul_sld finished [took 89.4295s]
+04/11/23 03:09:55| INFO mul_pacc_gs finished [took 104.7292s]
+04/11/23 03:12:25| INFO bin_sld finished [took 263.6824s]
+04/11/23 03:12:25| INFO bin_pacc finished [took 258.6502s]
+04/11/23 03:14:01| INFO mul_sld_gs finished [took 357.3344s]
+04/11/23 03:14:14| INFO bin_sld_gsq finished [took 369.1636s]
+04/11/23 03:14:22| INFO bin_pacc_gs finished [took 372.8646s]
+04/11/23 03:18:40| INFO bin_sld_gs finished [took 636.9190s]
+04/11/23 03:18:40| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 640.2322s]
+04/11/23 03:18:40| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+04/11/23 03:18:46| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 03:19:58| INFO ref finished [took 65.9462s]
+04/11/23 03:20:02| INFO atc_mc finished [took 68.5710s]
+04/11/23 03:20:04| INFO atc_ne finished [took 68.9466s]
+04/11/23 03:20:06| INFO mul_pacc finished [took 77.9039s]
+04/11/23 03:20:06| INFO mul_sld finished [took 84.0917s]
+04/11/23 03:20:37| INFO mul_pacc_gs finished [took 106.2536s]
+04/11/23 03:23:04| INFO bin_pacc finished [took 257.4211s]
+04/11/23 03:23:05| INFO bin_sld finished [took 264.3442s]
+04/11/23 03:24:49| INFO mul_sld_gs finished [took 365.1691s]
+04/11/23 03:25:01| INFO bin_pacc_gs finished [took 371.9184s]
+04/11/23 03:25:02| INFO bin_sld_gsq finished [took 377.0442s]
+04/11/23 03:29:37| INFO bin_sld_gs finished [took 654.0366s]
+04/11/23 03:29:37| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 657.0840s]
+04/11/23 03:29:37| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+04/11/23 03:29:42| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 03:30:51| INFO ref finished [took 62.7217s]
+04/11/23 03:30:58| INFO atc_mc finished [took 67.8613s]
+04/11/23 03:31:00| INFO atc_ne finished [took 68.5026s]
+04/11/23 03:31:03| INFO mul_sld finished [took 83.8857s]
+04/11/23 03:31:03| INFO mul_pacc finished [took 78.6340s]
+04/11/23 03:31:30| INFO mul_pacc_gs finished [took 103.4683s]
+04/11/23 03:34:00| INFO bin_sld finished [took 262.4457s]
+04/11/23 03:34:02| INFO bin_pacc finished [took 258.2247s]
+04/11/23 03:35:44| INFO mul_sld_gs finished [took 363.8135s]
+04/11/23 03:35:58| INFO bin_pacc_gs finished [took 372.0485s]
+04/11/23 03:36:05| INFO bin_sld_gsq finished [took 382.9585s]
+04/11/23 03:40:39| INFO bin_sld_gs finished [took 659.6222s]
+04/11/23 03:40:39| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 662.5763s]
+04/11/23 03:40:39| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+04/11/23 03:40:45| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 03:41:56| INFO ref finished [took 64.5923s]
+04/11/23 03:42:01| INFO atc_mc finished [took 68.0148s]
+04/11/23 03:42:03| INFO atc_ne finished [took 68.3119s]
+04/11/23 03:42:04| INFO mul_pacc finished [took 76.9397s]
+04/11/23 03:42:07| INFO mul_sld finished [took 85.5363s]
+04/11/23 03:42:34| INFO mul_pacc_gs finished [took 103.4448s]
+04/11/23 03:45:01| INFO bin_sld finished [took 260.0814s]
+04/11/23 03:45:03| INFO bin_pacc finished [took 256.9386s]
+04/11/23 03:46:45| INFO mul_sld_gs finished [took 361.5910s]
+04/11/23 03:47:01| INFO bin_pacc_gs finished [took 371.9657s]
+04/11/23 03:47:13| INFO bin_sld_gsq finished [took 388.2498s]
+04/11/23 03:51:40| INFO bin_sld_gs finished [took 657.4008s]
+04/11/23 03:51:40| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 660.5115s]
+04/11/23 03:51:40| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+04/11/23 03:51:46| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 03:52:54| INFO ref finished [took 61.9225s]
+04/11/23 03:53:00| INFO atc_mc finished [took 66.3156s]
+04/11/23 03:53:02| INFO atc_ne finished [took 66.5025s]
+04/11/23 03:53:04| INFO mul_pacc finished [took 75.8808s]
+04/11/23 03:53:06| INFO mul_sld finished [took 84.3204s]
+04/11/23 03:53:33| INFO mul_pacc_gs finished [took 102.5763s]
+04/11/23 03:56:04| INFO bin_sld finished [took 263.2781s]
+04/11/23 03:56:04| INFO bin_pacc finished [took 257.7298s]
+04/11/23 03:57:44| INFO mul_sld_gs finished [took 359.7910s]
+04/11/23 03:58:00| INFO bin_pacc_gs finished [took 371.3848s]
+04/11/23 03:58:11| INFO bin_sld_gsq finished [took 386.0904s]
+04/11/23 04:02:50| INFO bin_sld_gs finished [took 667.6623s]
+04/11/23 04:02:50| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 670.7255s]
+04/11/23 04:02:50| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+04/11/23 04:02:57| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 04:04:05| INFO ref finished [took 62.3256s]
+04/11/23 04:04:13| INFO atc_mc finished [took 68.9525s]
+04/11/23 04:04:15| INFO atc_ne finished [took 68.8750s]
+04/11/23 04:04:16| INFO mul_pacc finished [took 77.5049s]
+04/11/23 04:04:19| INFO mul_sld finished [took 86.0694s]
+04/11/23 04:04:45| INFO mul_pacc_gs finished [took 103.3513s]
+04/11/23 04:07:15| INFO bin_pacc finished [took 257.6456s]
+04/11/23 04:07:16| INFO bin_sld finished [took 263.9914s]
+04/11/23 04:08:55| INFO mul_sld_gs finished [took 360.5634s]
+04/11/23 04:09:12| INFO bin_pacc_gs finished [took 372.2665s]
+04/11/23 04:09:18| INFO bin_sld_gsq finished [took 381.8311s]
+04/11/23 04:13:39| INFO bin_sld_gs finished [took 645.3599s]
+04/11/23 04:13:39| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 648.5328s]
+04/11/23 04:13:39| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+04/11/23 04:13:45| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 04:14:51| INFO ref finished [took 59.8110s]
+04/11/23 04:14:58| INFO atc_mc finished [took 65.2666s]
+04/11/23 04:14:59| INFO atc_ne finished [took 64.5173s]
+04/11/23 04:15:01| INFO mul_pacc finished [took 73.8332s]
+04/11/23 04:15:04| INFO mul_sld finished [took 82.3509s]
+04/11/23 04:15:29| INFO mul_pacc_gs finished [took 99.3541s]
+04/11/23 04:18:00| INFO bin_pacc finished [took 254.3308s]
+04/11/23 04:18:03| INFO bin_sld finished [took 262.3008s]
+04/11/23 04:19:40| INFO mul_sld_gs finished [took 357.1229s]
+04/11/23 04:19:57| INFO bin_pacc_gs finished [took 368.4516s]
+04/11/23 04:20:03| INFO bin_sld_gsq finished [took 378.7658s]
+04/11/23 04:24:37| INFO bin_sld_gs finished [took 655.1931s]
+04/11/23 04:24:37| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 658.3505s]
+04/11/23 04:24:37| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+04/11/23 04:24:43| WARNING Method mul_sld_gsq failed. Exception: MultiClassAccuracyEstimator.__init__() got an unexpected keyword argument 'param_grid'
+04/11/23 04:25:49| INFO ref finished [took 59.4546s]
+04/11/23 04:25:55| INFO atc_mc finished [took 63.5805s]
+04/11/23 04:25:58| INFO atc_ne finished [took 63.2985s]
+04/11/23 04:25:58| INFO mul_pacc finished [took 72.5198s]
+04/11/23 04:26:11| INFO mul_sld finished [took 91.7136s]
+04/11/23 04:26:27| INFO mul_pacc_gs finished [took 98.8722s]
+04/11/23 04:28:57| INFO bin_pacc finished [took 252.8144s]
+04/11/23 04:29:02| INFO bin_sld finished [took 263.8013s]
+04/11/23 04:30:35| INFO mul_sld_gs finished [took 353.3693s]
+04/11/23 04:30:51| INFO bin_sld_gsq finished [took 368.8564s]
+04/11/23 04:30:54| INFO bin_pacc_gs finished [took 367.5592s]
+04/11/23 04:35:11| INFO bin_sld_gs finished [took 630.6700s]
+04/11/23 04:35:11| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 633.7494s]
+----------------------------------------------------------------------------------------------------
+04/11/23 19:09:42| INFO dataset rcv1_CCAT_9prevs
+04/11/23 19:09:47| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:10:28| INFO ref finished [took 36.0351s]
+04/11/23 19:10:32| INFO atc_mc finished [took 38.9507s]
+04/11/23 19:10:35| INFO mulmc_sld finished [took 43.7869s]
+04/11/23 19:10:50| INFO mul_sld finished [took 60.8007s]
+04/11/23 19:10:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 62.9600s]
+04/11/23 19:10:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:11:29| INFO ref finished [took 36.3632s]
+04/11/23 19:11:34| INFO atc_mc finished [took 39.5928s]
+04/11/23 19:11:36| INFO mulmc_sld finished [took 44.2915s]
+04/11/23 19:11:44| INFO mul_sld finished [took 52.6727s]
+04/11/23 19:11:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 54.0362s]
+04/11/23 19:11:44| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:12:24| INFO ref finished [took 36.4303s]
+04/11/23 19:12:27| INFO atc_mc finished [took 39.2329s]
+04/11/23 19:12:30| INFO mulmc_sld finished [took 43.6247s]
+04/11/23 19:12:36| INFO mul_sld finished [took 50.2041s]
+04/11/23 19:12:36| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 51.6412s]
+04/11/23 19:12:36| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:13:16| INFO ref finished [took 36.7551s]
+04/11/23 19:13:19| INFO atc_mc finished [took 39.2806s]
+04/11/23 19:13:21| INFO mulmc_sld finished [took 43.6120s]
+04/11/23 19:13:27| INFO mul_sld finished [took 50.4446s]
+04/11/23 19:13:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 51.6672s]
+04/11/23 19:13:27| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:14:07| INFO ref finished [took 35.8789s]
+04/11/23 19:14:11| INFO atc_mc finished [took 39.2168s]
+04/11/23 19:14:13| INFO mulmc_sld finished [took 43.4580s]
+04/11/23 19:14:20| INFO mul_sld finished [took 51.2902s]
+04/11/23 19:14:20| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 52.6303s]
+04/11/23 19:14:20| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:15:00| INFO ref finished [took 36.3735s]
+04/11/23 19:15:04| INFO atc_mc finished [took 39.7035s]
+04/11/23 19:15:06| INFO mulmc_sld finished [took 43.6364s]
+04/11/23 19:15:13| INFO mul_sld finished [took 52.0138s]
+04/11/23 19:15:13| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 53.3303s]
+04/11/23 19:15:13| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:15:54| INFO ref finished [took 37.3366s]
+04/11/23 19:15:57| INFO atc_mc finished [took 39.8921s]
+04/11/23 19:16:00| INFO mulmc_sld finished [took 44.5159s]
+04/11/23 19:16:08| INFO mul_sld finished [took 53.0806s]
+04/11/23 19:16:08| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 54.4117s]
+04/11/23 19:16:08| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:16:47| INFO ref finished [took 35.7800s]
+04/11/23 19:16:50| INFO atc_mc finished [took 38.4484s]
+04/11/23 19:16:53| INFO mulmc_sld finished [took 42.7405s]
+04/11/23 19:17:01| INFO mul_sld finished [took 51.5556s]
+04/11/23 19:17:01| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 52.9684s]
+04/11/23 19:17:01| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:17:39| INFO ref finished [took 35.0919s]
+04/11/23 19:17:43| INFO atc_mc finished [took 38.1718s]
+04/11/23 19:17:45| INFO mulmc_sld finished [took 42.4413s]
+04/11/23 19:17:59| INFO mul_sld finished [took 57.0766s]
+04/11/23 19:17:59| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 58.3668s]
+----------------------------------------------------------------------------------------------------
+04/11/23 19:42:38| INFO dataset rcv1_CCAT_9prevs
+04/11/23 19:42:43| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:43:27| INFO ref finished [took 38.7664s]
+04/11/23 19:43:31| INFO atc_mc finished [took 42.4000s]
+04/11/23 19:43:33| INFO mulmc_sld finished [took 47.0913s]
+04/11/23 19:43:34| INFO binmc_sld finished [took 47.1675s]
+04/11/23 19:43:49| INFO mul_sld finished [took 64.1382s]
+04/11/23 19:46:00| INFO bin_sld finished [took 195.9822s]
+04/11/23 19:46:00| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 197.2916s]
+04/11/23 19:46:00| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:46:44| INFO ref finished [took 38.5976s]
+04/11/23 19:46:48| INFO atc_mc finished [took 41.9465s]
+04/11/23 19:46:49| INFO mulmc_sld finished [took 46.2205s]
+04/11/23 19:46:51| INFO binmc_sld finished [took 46.7475s]
+04/11/23 19:46:58| INFO mul_sld finished [took 56.3552s]
+04/11/23 19:49:14| INFO bin_sld finished [took 193.2923s]
+04/11/23 19:49:14| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 194.6251s]
+04/11/23 19:49:14| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:49:58| INFO ref finished [took 38.3754s]
+04/11/23 19:50:02| INFO atc_mc finished [took 41.0091s]
+04/11/23 19:50:03| INFO mulmc_sld finished [took 45.6205s]
+04/11/23 19:50:05| INFO binmc_sld finished [took 46.1852s]
+04/11/23 19:50:10| INFO mul_sld finished [took 52.9704s]
+04/11/23 19:52:27| INFO bin_sld finished [took 190.6101s]
+04/11/23 19:52:27| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 192.0378s]
+04/11/23 19:52:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:53:10| INFO ref finished [took 38.4467s]
+04/11/23 19:53:13| INFO atc_mc finished [took 41.2602s]
+04/11/23 19:53:15| INFO mulmc_sld finished [took 45.7496s]
+04/11/23 19:53:16| INFO binmc_sld finished [took 45.5531s]
+04/11/23 19:53:21| INFO mul_sld finished [took 52.5067s]
+04/11/23 19:55:38| INFO bin_sld finished [took 190.7744s]
+04/11/23 19:55:38| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 191.9715s]
+04/11/23 19:55:39| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:56:21| INFO ref finished [took 37.9420s]
+04/11/23 19:56:26| INFO atc_mc finished [took 41.2056s]
+04/11/23 19:56:27| INFO mulmc_sld finished [took 45.7577s]
+04/11/23 19:56:28| INFO binmc_sld finished [took 45.6411s]
+04/11/23 19:56:34| INFO mul_sld finished [took 53.5219s]
+04/11/23 19:58:51| INFO bin_sld finished [took 191.1772s]
+04/11/23 19:58:51| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 192.4566s]
+04/11/23 19:58:51| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+04/11/23 19:59:34| INFO ref finished [took 37.8604s]
+04/11/23 19:59:38| INFO atc_mc finished [took 41.0334s]
+04/11/23 19:59:39| INFO mulmc_sld finished [took 45.1999s]
+04/11/23 19:59:40| INFO binmc_sld finished [took 45.4846s]
+04/11/23 19:59:47| INFO mul_sld finished [took 54.3166s]
+04/11/23 20:02:04| INFO bin_sld finished [took 191.4002s]
+04/11/23 20:02:04| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 192.6275s]
+04/11/23 20:02:04| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+04/11/23 20:02:48| INFO ref finished [took 38.8313s]
+04/11/23 20:02:52| INFO atc_mc finished [took 42.1162s]
+04/11/23 20:02:54| INFO mulmc_sld finished [took 47.0413s]
+04/11/23 20:02:55| INFO binmc_sld finished [took 46.8891s]
+04/11/23 20:03:02| INFO mul_sld finished [took 55.8821s]
+04/11/23 20:05:19| INFO bin_sld finished [took 193.7571s]
+04/11/23 20:05:19| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 195.2404s]
+04/11/23 20:05:19| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+04/11/23 20:06:03| INFO ref finished [took 38.7982s]
+04/11/23 20:06:06| INFO atc_mc finished [took 41.6213s]
+04/11/23 20:06:08| INFO mulmc_sld finished [took 46.2646s]
+04/11/23 20:06:09| INFO binmc_sld finished [took 46.2453s]
+04/11/23 20:06:16| INFO mul_sld finished [took 54.8621s]
+04/11/23 20:08:35| INFO bin_sld finished [took 194.5226s]
+04/11/23 20:08:35| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 195.9251s]
+04/11/23 20:08:35| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+04/11/23 20:09:18| INFO ref finished [took 38.3873s]
+04/11/23 20:09:22| INFO atc_mc finished [took 41.2537s]
+04/11/23 20:09:24| INFO mulmc_sld finished [took 46.2211s]
+04/11/23 20:09:25| INFO binmc_sld finished [took 46.6421s]
+04/11/23 20:09:38| INFO mul_sld finished [took 60.9539s]
+04/11/23 20:11:51| INFO bin_sld finished [took 195.1888s]
+04/11/23 20:11:51| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 196.4776s]
+----------------------------------------------------------------------------------------------------
+04/11/23 20:56:32| INFO dataset rcv1_CCAT_9prevs
+04/11/23 20:56:37| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+04/11/23 20:57:33| INFO ref finished [took 49.2697s]
+04/11/23 20:57:38| INFO atc_mc finished [took 53.2068s]
+04/11/23 20:57:39| INFO mulmc_sld finished [took 58.6224s]
+04/11/23 20:58:59| INFO mulmc_sld_gs finished [took 136.0930s]
+04/11/23 21:00:30| INFO binmc_sld finished [took 230.3290s]
+04/11/23 21:02:12| INFO mul_sld_gs finished [took 333.4899s]
+04/11/23 21:06:49| INFO bin_sld_gs finished [took 610.5751s]
+04/11/23 21:06:54| INFO binmc_sld_gs finished [took 612.8900s]
+04/11/23 21:06:55| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 617.6873s]
+04/11/23 21:06:55| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+04/11/23 21:07:52| INFO ref finished [took 49.8077s]
+04/11/23 21:07:56| INFO atc_mc finished [took 53.3303s]
+04/11/23 21:07:57| INFO mulmc_sld finished [took 58.9345s]
+04/11/23 21:09:17| INFO mulmc_sld_gs finished [took 136.5258s]
+04/11/23 21:10:51| INFO binmc_sld finished [took 233.4049s]
+04/11/23 21:12:35| INFO mul_sld_gs finished [took 338.2751s]
+04/11/23 21:17:38| INFO bin_sld_gs finished [took 641.8524s]
+04/11/23 21:18:19| INFO binmc_sld_gs finished [took 679.9471s]
+04/11/23 21:18:19| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 684.7098s]
+04/11/23 21:18:19| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+04/11/23 21:19:24| INFO ref finished [took 55.3767s]
+04/11/23 21:19:28| INFO mulmc_sld finished [took 64.2789s]
+04/11/23 21:19:29| INFO atc_mc finished [took 59.5610s]
+04/11/23 21:20:57| INFO mulmc_sld_gs finished [took 150.1392s]
+04/11/23 21:22:36| INFO binmc_sld finished [took 253.0960s]
+04/11/23 21:24:16| INFO mul_sld_gs finished [took 354.6283s]
+04/11/23 21:29:15| INFO bin_sld_gs finished [took 654.3325s]
+04/11/23 21:29:50| INFO binmc_sld_gs finished [took 684.5074s]
+04/11/23 21:29:50| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 690.4897s]
+04/11/23 21:29:50| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+04/11/23 21:30:45| INFO ref finished [took 48.2647s]
+04/11/23 21:30:51| INFO atc_mc finished [took 52.2724s]
+04/11/23 21:30:51| INFO mulmc_sld finished [took 57.5142s]
+04/11/23 21:32:07| INFO mulmc_sld_gs finished [took 131.4908s]
+04/11/23 21:33:38| INFO binmc_sld finished [took 224.9620s]
+04/11/23 21:35:22| INFO mul_sld_gs finished [took 329.9053s]
+04/11/23 21:40:25| INFO bin_sld_gs finished [took 634.4342s]
+04/11/23 21:41:08| INFO binmc_sld_gs finished [took 673.6071s]
+04/11/23 21:41:08| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 678.4725s]
+04/11/23 21:41:08| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+04/11/23 21:42:03| INFO ref finished [took 47.4381s]
+04/11/23 21:42:08| INFO atc_mc finished [took 51.3566s]
+04/11/23 21:42:09| INFO mulmc_sld finished [took 56.6180s]
+04/11/23 21:43:23| INFO mulmc_sld_gs finished [took 128.6413s]
+04/11/23 21:44:54| INFO binmc_sld finished [took 222.7951s]
+04/11/23 21:46:39| INFO mul_sld_gs finished [took 328.8118s]
+04/11/23 21:51:37| INFO bin_sld_gs finished [took 627.4937s]
+04/11/23 21:52:17| INFO binmc_sld_gs finished [took 663.8116s]
+04/11/23 21:52:17| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 668.8948s]
+04/11/23 21:52:17| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+04/11/23 21:53:12| INFO ref finished [took 47.6269s]
+04/11/23 21:53:16| INFO atc_mc finished [took 51.1109s]
+04/11/23 21:53:17| INFO mulmc_sld finished [took 56.5728s]
+04/11/23 21:54:31| INFO mulmc_sld_gs finished [took 128.0358s]
+04/11/23 21:56:00| INFO binmc_sld finished [took 220.0811s]
+04/11/23 21:57:46| INFO mul_sld_gs finished [took 327.0856s]
+04/11/23 22:02:58| INFO bin_sld_gs finished [took 639.3432s]
+04/11/23 22:03:48| INFO binmc_sld_gs finished [took 686.2326s]
+04/11/23 22:03:48| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 690.9677s]
+04/11/23 22:03:48| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+04/11/23 22:04:42| INFO ref finished [took 47.2804s]
+04/11/23 22:04:48| INFO atc_mc finished [took 51.6888s]
+04/11/23 22:04:48| INFO mulmc_sld finished [took 56.1465s]
+04/11/23 22:06:06| INFO mulmc_sld_gs finished [took 132.4278s]
+04/11/23 22:07:33| INFO binmc_sld finished [took 221.9299s]
+04/11/23 22:09:19| INFO mul_sld_gs finished [took 329.1446s]
+04/11/23 22:14:09| INFO bin_sld_gs finished [took 619.3584s]
+04/11/23 22:14:32| INFO binmc_sld_gs finished [took 638.7326s]
+04/11/23 22:14:32| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 643.6278s]
+04/11/23 22:14:32| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+04/11/23 22:15:26| INFO ref finished [took 47.3139s]
+04/11/23 22:15:30| INFO atc_mc finished [took 50.8602s]
+04/11/23 22:15:32| INFO mulmc_sld finished [took 56.5107s]
+04/11/23 22:16:47| INFO mulmc_sld_gs finished [took 129.5292s]
+04/11/23 22:18:22| INFO binmc_sld finished [took 226.9238s]
+04/11/23 22:20:02| INFO mul_sld_gs finished [took 327.7014s]
+04/11/23 22:24:57| INFO bin_sld_gs finished [took 624.4254s]
+04/11/23 22:25:13| INFO binmc_sld_gs finished [took 636.2675s]
+04/11/23 22:25:13| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 641.0382s]
+04/11/23 22:25:13| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+04/11/23 22:26:07| INFO ref finished [took 47.3224s]
+04/11/23 22:26:12| INFO atc_mc finished [took 51.1828s]
+04/11/23 22:26:13| INFO mulmc_sld finished [took 56.6133s]
+04/11/23 22:27:30| INFO mulmc_sld_gs finished [took 131.3662s]
+04/11/23 22:29:05| INFO binmc_sld finished [took 229.3002s]
+04/11/23 22:30:38| INFO mul_sld_gs finished [took 323.5271s]
+04/11/23 22:35:21| INFO bin_sld_gs finished [took 606.6430s]
+04/11/23 22:35:30| INFO binmc_sld_gs finished [took 612.5966s]
+04/11/23 22:35:30| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 617.3109s]
+----------------------------------------------------------------------------------------------------
+04/11/23 22:49:37| ERROR Evaluation over rcv1_CCAT_3prevs failed. Exception: 'Invalid estimator: estimator binmc_sld_gs does not exist'
+04/11/23 22:49:37| ERROR Failed while saving configuration rcv1_CCAT_debug of rcv1_CCAT_3prevs. Exception: cannot access local variable 'dr' where it is not associated with a value
+----------------------------------------------------------------------------------------------------
+04/11/23 22:50:07| INFO dataset rcv1_CCAT_3prevs
+04/11/23 22:50:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+----------------------------------------------------------------------------------------------------
+04/11/23 22:55:55| INFO dataset rcv1_CCAT_3prevs
+04/11/23 22:55:59| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 22:56:48| INFO ref finished [took 44.4275s]
+----------------------------------------------------------------------------------------------------
+04/11/23 22:56:59| INFO dataset rcv1_CCAT_3prevs
+04/11/23 22:57:03| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 22:57:09| WARNING Method mul_sld_gs failed. Exception: '>=' not supported between instances of 'TypeError' and 'int'
+04/11/23 22:57:17| WARNING Method bin_sld_gs failed. Exception: '>=' not supported between instances of 'TypeError' and 'int'
+----------------------------------------------------------------------------------------------------
+04/11/23 22:58:04| INFO dataset rcv1_CCAT_3prevs
+04/11/23 22:58:09| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 22:58:58| INFO ref finished [took 43.7541s]
+04/11/23 22:59:05| INFO atc_mc finished [took 50.0628s]
+----------------------------------------------------------------------------------------------------
+04/11/23 23:01:22| INFO dataset rcv1_CCAT_3prevs
+04/11/23 23:01:27| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 23:02:16| INFO ref finished [took 43.9765s]
+04/11/23 23:02:23| INFO atc_mc finished [took 50.5568s]
+----------------------------------------------------------------------------------------------------
+04/11/23 23:09:33| INFO dataset rcv1_CCAT_3prevs
+04/11/23 23:09:37| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 23:09:38| WARNING Method binmc_sld failed. Exception: classifier and pred_proba cannot be both None
+04/11/23 23:09:39| WARNING Method mulmc_sld failed. Exception: classifier and pred_proba cannot be both None
+04/11/23 23:09:40| WARNING Method bin_sld_gs failed. Exception: no combination of hyperparameters seem to work
+04/11/23 23:09:41| WARNING Method mul_sld_gs failed. Exception: no combination of hyperparameters seem to work
+----------------------------------------------------------------------------------------------------
+04/11/23 23:10:23| INFO dataset rcv1_CCAT_3prevs
+04/11/23 23:10:28| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 23:11:15| INFO ref finished [took 42.4887s]
+04/11/23 23:11:20| INFO atc_mc finished [took 45.6262s]
+04/11/23 23:11:21| INFO mulmc_sld finished [took 50.9790s]
+04/11/23 23:13:57| INFO binmc_sld finished [took 208.3159s]
+----------------------------------------------------------------------------------------------------
+04/11/23 23:16:22| INFO dataset rcv1_CCAT_3prevs
+04/11/23 23:16:26| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+04/11/23 23:17:12| INFO ref finished [took 40.5978s]
+04/11/23 23:17:16| INFO atc_mc finished [took 43.6933s]
+04/11/23 23:17:17| INFO mulmc_sld finished [took 49.0808s]
+04/11/23 23:19:53| INFO binmc_sld finished [took 205.5731s]
+04/11/23 23:22:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00672) [took 354.1411s]
+04/11/23 23:23:05| INFO mul_sld_gs finished [took 394.8240s]
+04/11/23 23:30:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00891) [took 852.1465s]
+04/11/23 23:33:44| INFO bin_sld_gs finished [took 1035.2071s]
+04/11/23 23:33:44| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs finished [took 1038.1845s]
+04/11/23 23:33:44| INFO Dataset sample 0.50 of dataset rcv1_CCAT_3prevs started
+04/11/23 23:34:33| INFO ref finished [took 43.6409s]
+04/11/23 23:34:37| INFO atc_mc finished [took 46.7818s]
+04/11/23 23:34:38| INFO mulmc_sld finished [took 51.3459s]
+04/11/23 23:37:15| INFO binmc_sld finished [took 209.5746s]
+04/11/23 23:39:48| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00553) [took 359.3210s]
+04/11/23 23:40:28| INFO mul_sld_gs finished [took 399.5320s]
+04/11/23 23:48:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': None} (score=0.01058) [took 855.1289s]
+04/11/23 23:51:06| INFO bin_sld_gs finished [took 1038.6344s]
+04/11/23 23:51:06| INFO Dataset sample 0.50 of dataset rcv1_CCAT_3prevs finished [took 1041.6478s]
+04/11/23 23:51:06| INFO Dataset sample 0.60 of dataset rcv1_CCAT_3prevs started
+04/11/23 23:51:51| INFO ref finished [took 40.0694s]
+04/11/23 23:51:55| INFO atc_mc finished [took 42.4882s]
+04/11/23 23:51:56| INFO mulmc_sld finished [took 47.7936s]
+04/11/23 23:54:29| INFO binmc_sld finished [took 201.3777s]
+04/11/23 23:57:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00429) [took 352.7820s]
+04/11/23 23:57:43| INFO mul_sld_gs finished [took 392.5201s]
+05/11/23 00:05:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.00552) [took 851.9361s]
+05/11/23 00:08:24| INFO bin_sld_gs finished [took 1034.7353s]
+05/11/23 00:08:24| INFO Dataset sample 0.60 of dataset rcv1_CCAT_3prevs finished [took 1037.8033s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:11:07| INFO dataset rcv1_CCAT_3prevs
+05/11/23 00:11:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_3prevs started
+----------------------------------------------------------------------------------------------------
+05/11/23 00:28:39| INFO dataset imdb_3prevs
+05/11/23 00:28:46| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 00:28:55| INFO ref finished [took 8.7347s]
+05/11/23 00:28:58| INFO atc_mc finished [took 11.6376s]
+05/11/23 00:28:59| INFO mulmc_sld finished [took 13.5476s]
+05/11/23 00:28:59| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 13.9513s]
+05/11/23 00:28:59| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 00:29:09| INFO ref finished [took 8.7049s]
+05/11/23 00:29:12| INFO atc_mc finished [took 11.6170s]
+05/11/23 00:29:14| INFO mulmc_sld finished [took 13.7416s]
+05/11/23 00:29:14| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.2842s]
+05/11/23 00:29:14| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 00:29:23| INFO ref finished [took 8.6894s]
+05/11/23 00:29:26| INFO atc_mc finished [took 11.5275s]
+05/11/23 00:29:28| INFO mulmc_sld finished [took 13.6977s]
+05/11/23 00:29:28| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.2742s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:34:12| INFO dataset imdb_3prevs
+05/11/23 00:34:22| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 00:34:41| INFO ref finished [took 17.6558s]
+05/11/23 00:34:46| INFO mulmc_sld finished [took 22.9646s]
+05/11/23 00:34:48| INFO atc_mc finished [took 24.5871s]
+05/11/23 00:34:48| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 25.3179s]
+05/11/23 00:34:48| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 00:35:05| INFO ref finished [took 17.2188s]
+05/11/23 00:35:10| INFO mulmc_sld finished [took 22.2420s]
+05/11/23 00:35:12| INFO atc_mc finished [took 23.9752s]
+05/11/23 00:35:12| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 24.7688s]
+05/11/23 00:35:12| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 00:35:33| INFO ref finished [took 20.0731s]
+05/11/23 00:35:38| INFO mulmc_sld finished [took 24.8736s]
+05/11/23 00:35:40| INFO atc_mc finished [took 27.0318s]
+05/11/23 00:35:40| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 27.8108s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:39:57| INFO dataset imdb_1prevs
+05/11/23 00:40:07| INFO Dataset sample 0.50 of dataset imdb_1prevs started
+05/11/23 00:40:26| INFO ref finished [took 17.4863s]
+05/11/23 00:40:31| INFO mulmc_sld finished [took 22.5384s]
+05/11/23 00:40:33| INFO atc_mc finished [took 24.2747s]
+05/11/23 00:40:33| INFO Dataset sample 0.50 of dataset imdb_1prevs finished [took 25.6430s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:41:36| INFO dataset imdb_2prevs
+05/11/23 00:41:46| INFO Dataset sample 0.20 of dataset imdb_2prevs started
+05/11/23 00:42:05| INFO ref finished [took 17.6637s]
+05/11/23 00:42:10| INFO mulmc_sld finished [took 22.6956s]
+05/11/23 00:42:11| INFO atc_mc finished [took 24.3529s]
+05/11/23 00:42:11| INFO Dataset sample 0.20 of dataset imdb_2prevs finished [took 25.0708s]
+05/11/23 00:42:11| INFO Dataset sample 0.80 of dataset imdb_2prevs started
+05/11/23 00:42:29| INFO ref finished [took 17.2818s]
+05/11/23 00:42:34| INFO mulmc_sld finished [took 22.4054s]
+05/11/23 00:42:36| INFO atc_mc finished [took 23.9392s]
+05/11/23 00:42:36| INFO Dataset sample 0.80 of dataset imdb_2prevs finished [took 24.7193s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:45:54| INFO dataset imdb_2prevs
+05/11/23 00:46:04| INFO Dataset sample 0.20 of dataset imdb_2prevs started
+05/11/23 00:46:22| INFO ref finished [took 17.2217s]
+05/11/23 00:46:27| INFO mulmc_sld finished [took 22.2712s]
+05/11/23 00:46:28| INFO atc_mc finished [took 23.7770s]
+05/11/23 00:46:28| INFO Dataset sample 0.20 of dataset imdb_2prevs finished [took 24.5092s]
+05/11/23 00:46:28| INFO Dataset sample 0.80 of dataset imdb_2prevs started
+05/11/23 00:46:46| INFO ref finished [took 17.1303s]
+05/11/23 00:46:51| INFO mulmc_sld finished [took 22.5084s]
+05/11/23 00:46:53| INFO atc_mc finished [took 23.9160s]
+05/11/23 00:46:53| INFO Dataset sample 0.80 of dataset imdb_2prevs finished [took 24.6992s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:51:06| INFO dataset imdb_2prevs
+05/11/23 00:51:16| INFO Dataset sample 0.20 of dataset imdb_2prevs started
+05/11/23 00:51:33| INFO ref finished [took 17.0670s]
+05/11/23 00:51:38| INFO mulmc_sld finished [took 22.3141s]
+05/11/23 00:51:40| INFO atc_mc finished [took 23.7219s]
+05/11/23 00:51:40| INFO Dataset sample 0.20 of dataset imdb_2prevs finished [took 24.4385s]
+05/11/23 00:51:40| INFO Dataset sample 0.80 of dataset imdb_2prevs started
+05/11/23 00:51:58| INFO ref finished [took 17.1894s]
+05/11/23 00:52:03| INFO mulmc_sld finished [took 22.4247s]
+05/11/23 00:52:04| INFO atc_mc finished [took 23.6032s]
+05/11/23 00:52:04| INFO Dataset sample 0.80 of dataset imdb_2prevs finished [took 24.3674s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:53:32| INFO dataset imdb_3prevs
+05/11/23 00:53:39| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 00:53:48| INFO ref finished [took 8.8062s]
+05/11/23 00:53:51| INFO atc_mc finished [took 11.7173s]
+05/11/23 00:53:53| INFO mulmc_sld finished [took 13.8761s]
+05/11/23 00:53:53| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 14.3147s]
+05/11/23 00:53:53| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 00:54:03| INFO ref finished [took 8.9071s]
+05/11/23 00:54:06| INFO atc_mc finished [took 11.7005s]
+05/11/23 00:54:08| INFO mulmc_sld finished [took 13.6266s]
+05/11/23 00:54:08| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.1625s]
+05/11/23 00:54:08| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 00:54:17| INFO ref finished [took 8.7680s]
+05/11/23 00:54:20| INFO atc_mc finished [took 11.4957s]
+05/11/23 00:54:22| INFO mulmc_sld finished [took 13.5719s]
+05/11/23 00:54:22| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.1564s]
+----------------------------------------------------------------------------------------------------
+05/11/23 00:57:53| INFO dataset imdb_3prevs
+05/11/23 00:57:59| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 00:58:08| INFO ref finished [took 8.7497s]
+05/11/23 00:58:12| INFO atc_mc finished [took 11.6903s]
+05/11/23 00:58:13| INFO mulmc_sld finished [took 13.6731s]
+05/11/23 00:58:13| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 14.1073s]
+05/11/23 00:58:13| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 00:58:23| INFO ref finished [took 8.7718s]
+05/11/23 00:58:26| INFO atc_mc finished [took 11.7653s]
+05/11/23 00:58:28| INFO mulmc_sld finished [took 13.9184s]
+05/11/23 00:58:28| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.4270s]
+05/11/23 00:58:28| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 00:58:37| INFO ref finished [took 8.8129s]
+05/11/23 00:58:40| INFO atc_mc finished [took 11.7267s]
+05/11/23 00:58:42| INFO mulmc_sld finished [took 13.6726s]
+05/11/23 00:58:42| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.2387s]
+----------------------------------------------------------------------------------------------------
+05/11/23 01:04:04| INFO dataset imdb_3prevs
+05/11/23 01:04:10| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 01:04:20| INFO ref finished [took 8.7879s]
+05/11/23 01:04:23| INFO atc_mc finished [took 11.8757s]
+05/11/23 01:04:25| INFO mulmc_sld finished [took 13.8698s]
+05/11/23 01:04:25| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 14.2927s]
+05/11/23 01:04:25| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 01:04:34| INFO ref finished [took 8.9200s]
+05/11/23 01:04:37| INFO atc_mc finished [took 11.9555s]
+05/11/23 01:04:39| INFO mulmc_sld finished [took 13.9860s]
+05/11/23 01:04:39| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 14.5339s]
+05/11/23 01:04:39| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 01:04:49| INFO ref finished [took 8.8757s]
+05/11/23 01:04:52| INFO atc_mc finished [took 11.8222s]
+05/11/23 01:04:53| INFO mulmc_sld finished [took 13.7034s]
+05/11/23 01:04:53| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 14.2710s]
+----------------------------------------------------------------------------------------------------
+05/11/23 01:08:05| INFO dataset rcv1_CCAT_9prevs
+05/11/23 01:08:09| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 01:08:55| INFO ref finished [took 40.9427s]
+05/11/23 01:09:00| INFO atc_mc finished [took 44.2152s]
+05/11/23 01:09:01| INFO mulmc_sld finished [took 49.6089s]
+05/11/23 01:11:38| INFO bin_sld finished [took 207.5917s]
+05/11/23 01:13:47| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00663) [took 333.7044s]
+05/11/23 01:14:30| INFO mul_sld_gs finished [took 376.3503s]
+05/11/23 01:20:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00619) [took 751.2730s]
+05/11/23 01:23:45| INFO bin_sld_gs finished [took 932.2941s]
+05/11/23 01:23:45| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 935.3228s]
+05/11/23 01:23:45| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 01:24:30| INFO ref finished [took 39.9821s]
+05/11/23 01:24:34| INFO atc_mc finished [took 43.3585s]
+05/11/23 01:24:36| INFO mulmc_sld finished [took 48.6404s]
+05/11/23 01:27:08| INFO bin_sld finished [took 202.3970s]
+05/11/23 01:29:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00699) [took 328.6883s]
+05/11/23 01:30:00| INFO mul_sld_gs finished [took 371.2150s]
+05/11/23 01:36:40| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00780) [took 771.8150s]
+05/11/23 01:39:44| INFO bin_sld_gs finished [took 956.5831s]
+05/11/23 01:39:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 959.5214s]
+05/11/23 01:39:44| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 01:40:38| INFO ref finished [took 46.9727s]
+05/11/23 01:40:42| INFO atc_mc finished [took 49.6456s]
+05/11/23 01:40:43| INFO mulmc_sld finished [took 55.1784s]
+05/11/23 01:43:16| INFO bin_sld finished [took 209.5653s]
+05/11/23 01:45:30| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00720) [took 340.0613s]
+05/11/23 01:46:09| INFO mul_sld_gs finished [took 379.3695s]
+05/11/23 01:53:22| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00810) [took 813.3118s]
+05/11/23 01:56:25| INFO bin_sld_gs finished [took 996.4380s]
+05/11/23 01:56:25| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1000.8297s]
+05/11/23 01:56:25| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 01:57:11| INFO ref finished [took 40.2515s]
+05/11/23 01:57:15| INFO atc_mc finished [took 43.5348s]
+05/11/23 01:57:15| INFO mulmc_sld finished [took 48.1622s]
+05/11/23 01:59:46| INFO bin_sld finished [took 200.0955s]
+05/11/23 02:02:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00644) [took 331.2368s]
+05/11/23 02:02:40| INFO mul_sld_gs finished [took 370.8879s]
+05/11/23 02:10:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.01269) [took 813.7272s]
+05/11/23 02:13:04| INFO bin_sld_gs finished [took 995.6098s]
+05/11/23 02:13:04| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 998.5647s]
+05/11/23 02:13:04| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+05/11/23 02:13:50| INFO ref finished [took 41.4181s]
+05/11/23 02:13:55| INFO atc_mc finished [took 44.8414s]
+05/11/23 02:13:55| INFO mulmc_sld finished [took 49.5767s]
+05/11/23 02:16:27| INFO bin_sld finished [took 201.8696s]
+05/11/23 02:18:33| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00636) [took 325.5401s]
+05/11/23 02:19:17| INFO mul_sld_gs finished [took 368.9682s]
+05/11/23 02:26:26| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00670) [took 799.7618s]
+05/11/23 02:29:29| INFO bin_sld_gs finished [took 982.2921s]
+05/11/23 02:29:29| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 985.2925s]
+05/11/23 02:29:29| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+05/11/23 02:30:14| INFO ref finished [took 40.3341s]
+05/11/23 02:30:18| INFO atc_mc finished [took 43.3032s]
+05/11/23 02:30:19| INFO mulmc_sld finished [took 47.8507s]
+05/11/23 02:32:51| INFO bin_sld finished [took 200.9647s]
+05/11/23 02:34:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00596) [took 321.5172s]
+05/11/23 02:35:33| INFO mul_sld_gs finished [took 360.5222s]
+05/11/23 02:43:22| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.00544) [took 829.7314s]
+05/11/23 02:46:23| INFO bin_sld_gs finished [took 1011.3917s]
+05/11/23 02:46:23| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1014.2514s]
+05/11/23 02:46:23| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+05/11/23 02:47:09| INFO ref finished [took 40.4272s]
+05/11/23 02:47:13| INFO atc_mc finished [took 43.8966s]
+05/11/23 02:47:14| INFO mulmc_sld finished [took 48.4437s]
+05/11/23 02:49:47| INFO bin_sld finished [took 202.6013s]
+05/11/23 02:51:57| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00653) [took 329.4236s]
+05/11/23 02:52:36| INFO mul_sld_gs finished [took 368.7426s]
+05/11/23 02:59:51| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01370) [took 804.3215s]
+05/11/23 03:02:54| INFO bin_sld_gs finished [took 987.5377s]
+05/11/23 03:02:54| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 990.4607s]
+05/11/23 03:02:54| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+05/11/23 03:03:40| INFO ref finished [took 41.5104s]
+05/11/23 03:03:44| INFO atc_mc finished [took 44.1770s]
+05/11/23 03:03:46| INFO mulmc_sld finished [took 49.7176s]
+05/11/23 03:06:27| INFO bin_sld finished [took 211.4985s]
+05/11/23 03:08:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00822) [took 334.7029s]
+05/11/23 03:09:16| INFO mul_sld_gs finished [took 377.8219s]
+05/11/23 03:16:22| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.00984) [took 805.4146s]
+05/11/23 03:19:28| INFO bin_sld_gs finished [took 991.0520s]
+05/11/23 03:19:28| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 994.1016s]
+05/11/23 03:19:28| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+05/11/23 03:20:18| INFO ref finished [took 44.1663s]
+05/11/23 03:20:22| INFO atc_mc finished [took 47.3231s]
+05/11/23 03:20:23| INFO mulmc_sld finished [took 53.1243s]
+05/11/23 03:23:10| INFO bin_sld finished [took 220.4921s]
+05/11/23 03:25:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00811) [took 338.9143s]
+05/11/23 03:25:56| INFO mul_sld_gs finished [took 383.9350s]
+05/11/23 03:32:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': None} (score=0.00954) [took 792.6190s]
+05/11/23 03:35:44| INFO bin_sld_gs finished [took 973.2397s]
+05/11/23 03:35:44| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 976.4502s]
+05/11/23 03:35:57| INFO dataset imbd_9prevs
+05/11/23 03:35:57| ERROR Evaluation over imbd_9prevs failed. Exception: 'imbd'
+----------------------------------------------------------------------------------------------------
+05/11/23 09:42:24| INFO dataset imdb_9prevs
+05/11/23 09:42:30| INFO Dataset sample 0.10 of dataset imdb_9prevs started
+05/11/23 09:42:44| INFO ref finished [took 10.6450s]
+05/11/23 09:42:47| INFO atc_mc finished [took 13.9369s]
+05/11/23 09:42:49| INFO mulmc_sld finished [took 16.6526s]
+05/11/23 09:42:56| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+05/11/23 09:45:26| INFO bin_sld finished [took 173.8798s]
+05/11/23 09:47:18| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.03792) [took 285.1339s]
+05/11/23 09:47:33| INFO mul_sld_gs finished [took 300.3243s]
+05/11/23 09:47:33| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 302.7180s]
+05/11/23 09:47:33| INFO Dataset sample 0.20 of dataset imdb_9prevs started
+05/11/23 09:47:46| INFO ref finished [took 12.0501s]
+05/11/23 09:47:50| INFO atc_mc finished [took 15.0907s]
+05/11/23 09:47:52| INFO mulmc_sld finished [took 17.8502s]
+05/11/23 09:50:42| INFO bin_sld finished [took 188.2533s]
+05/11/23 09:53:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.01067) [took 328.6088s]
+05/11/23 09:53:19| INFO mul_sld_gs finished [took 345.1926s]
+05/11/23 10:00:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00923) [took 798.1316s]
+05/11/23 10:03:34| INFO bin_sld_gs finished [took 960.1696s]
+05/11/23 10:03:34| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 960.9823s]
+05/11/23 10:03:34| INFO Dataset sample 0.30 of dataset imdb_9prevs started
+05/11/23 10:03:46| INFO ref finished [took 10.8585s]
+05/11/23 10:03:49| INFO atc_mc finished [took 13.6836s]
+05/11/23 10:03:51| INFO mulmc_sld finished [took 15.8085s]
+05/11/23 10:06:39| INFO bin_sld finished [took 183.7435s]
+05/11/23 10:09:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00707) [took 326.5308s]
+05/11/23 10:09:15| INFO mul_sld_gs finished [took 339.3412s]
+05/11/23 10:16:51| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01094) [took 796.0895s]
+05/11/23 10:19:27| INFO bin_sld_gs finished [took 952.0793s]
+05/11/23 10:19:27| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 953.0580s]
+05/11/23 10:19:27| INFO Dataset sample 0.40 of dataset imdb_9prevs started
+05/11/23 10:19:39| INFO ref finished [took 10.8707s]
+05/11/23 10:19:42| INFO atc_mc finished [took 13.9089s]
+05/11/23 10:19:44| INFO mulmc_sld finished [took 15.9994s]
+05/11/23 10:22:17| INFO bin_sld finished [took 168.9998s]
+05/11/23 10:24:35| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00999) [took 306.5297s]
+05/11/23 10:24:47| INFO mul_sld_gs finished [took 318.6584s]
+05/11/23 10:32:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.01176) [took 782.7189s]
+05/11/23 10:35:07| INFO bin_sld_gs finished [took 939.3830s]
+05/11/23 10:35:07| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 940.2365s]
+05/11/23 10:35:07| INFO Dataset sample 0.50 of dataset imdb_9prevs started
+05/11/23 10:35:19| INFO ref finished [took 10.1160s]
+05/11/23 10:35:22| INFO atc_mc finished [took 13.6292s]
+05/11/23 10:35:24| INFO mulmc_sld finished [took 15.7949s]
+05/11/23 10:38:04| INFO bin_sld finished [took 176.0746s]
+05/11/23 10:40:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01008) [took 319.8045s]
+05/11/23 10:40:45| INFO mul_sld_gs finished [took 336.8792s]
+05/11/23 10:48:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00942) [took 802.9266s]
+05/11/23 10:51:09| INFO bin_sld_gs finished [took 961.0002s]
+05/11/23 10:51:09| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 961.8311s]
+05/11/23 10:51:09| INFO Dataset sample 0.60 of dataset imdb_9prevs started
+05/11/23 10:51:21| INFO ref finished [took 10.7059s]
+05/11/23 10:51:24| INFO atc_mc finished [took 13.8934s]
+05/11/23 10:51:26| INFO mulmc_sld finished [took 16.0295s]
+05/11/23 10:54:09| INFO bin_sld finished [took 179.1806s]
+05/11/23 10:56:31| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00906) [took 320.5350s]
+05/11/23 10:56:45| INFO mul_sld_gs finished [took 334.5485s]
+05/11/23 11:04:55| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': None} (score=0.01228) [took 824.5702s]
+05/11/23 11:07:33| INFO bin_sld_gs finished [took 983.3806s]
+05/11/23 11:07:33| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 984.1981s]
+05/11/23 11:07:34| INFO Dataset sample 0.70 of dataset imdb_9prevs started
+05/11/23 11:07:45| INFO ref finished [took 10.7034s]
+05/11/23 11:07:49| INFO atc_mc finished [took 14.0668s]
+05/11/23 11:07:51| INFO mulmc_sld finished [took 16.2499s]
+----------------------------------------------------------------------------------------------------
+05/11/23 11:09:19| INFO dataset rcv1_CCAT_9prevs
+05/11/23 11:09:24| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+----------------------------------------------------------------------------------------------------
+05/11/23 11:10:40| INFO dataset rcv1_CCAT_9prevs
+05/11/23 11:10:44| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:11:21| INFO ref finished [took 34.7944s]
+05/11/23 11:11:25| INFO atc_mc finished [took 37.6168s]
+05/11/23 11:11:36| INFO mulmc_sld finished [took 51.0883s]
+05/11/23 11:11:36| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 52.3442s]
+05/11/23 11:11:36| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:12:14| INFO ref finished [took 35.0033s]
+05/11/23 11:12:17| INFO atc_mc finished [took 37.7761s]
+05/11/23 11:12:24| INFO mulmc_sld finished [took 46.2195s]
+05/11/23 11:12:24| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 47.5446s]
+05/11/23 11:12:24| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:13:01| INFO ref finished [took 35.1077s]
+05/11/23 11:13:05| INFO atc_mc finished [took 37.7889s]
+05/11/23 11:13:12| INFO mulmc_sld finished [took 46.6515s]
+05/11/23 11:13:12| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 48.0359s]
+05/11/23 11:13:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:13:49| INFO ref finished [took 35.0214s]
+05/11/23 11:13:53| INFO atc_mc finished [took 37.9480s]
+05/11/23 11:14:00| INFO mulmc_sld finished [took 46.4140s]
+05/11/23 11:14:00| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 47.5164s]
+05/11/23 11:14:00| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:14:37| INFO ref finished [took 35.2699s]
+05/11/23 11:14:41| INFO atc_mc finished [took 37.9490s]
+05/11/23 11:14:49| INFO mulmc_sld finished [took 47.7005s]
+05/11/23 11:14:49| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 49.0189s]
+05/11/23 11:14:49| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:15:26| INFO ref finished [took 35.2350s]
+05/11/23 11:15:30| INFO atc_mc finished [took 38.6364s]
+05/11/23 11:15:39| INFO mulmc_sld finished [took 48.8860s]
+05/11/23 11:15:39| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 50.1097s]
+05/11/23 11:15:39| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:16:16| INFO ref finished [took 35.0322s]
+05/11/23 11:16:20| INFO atc_mc finished [took 38.4809s]
+05/11/23 11:16:29| INFO mulmc_sld finished [took 48.6466s]
+05/11/23 11:16:29| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 50.0372s]
+05/11/23 11:16:29| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:17:06| INFO ref finished [took 35.2988s]
+05/11/23 11:17:10| INFO atc_mc finished [took 38.3390s]
+05/11/23 11:17:18| INFO mulmc_sld finished [took 47.8829s]
+05/11/23 11:17:18| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 49.2700s]
+05/11/23 11:17:18| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:17:56| INFO ref finished [took 35.2614s]
+05/11/23 11:17:59| INFO atc_mc finished [took 38.1131s]
+05/11/23 11:18:08| INFO mulmc_sld finished [took 49.0925s]
+05/11/23 11:18:09| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 50.4765s]
+----------------------------------------------------------------------------------------------------
+05/11/23 11:26:35| INFO dataset rcv1_CCAT_9prevs
+05/11/23 11:26:39| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:27:17| INFO ref finished [took 35.3305s]
+05/11/23 11:27:21| INFO atc_mc finished [took 37.9469s]
+05/11/23 11:27:28| INFO mulmc_sld finished [took 46.9769s]
+05/11/23 11:27:28| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 48.3022s]
+05/11/23 11:27:28| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:28:05| INFO ref finished [took 35.2459s]
+05/11/23 11:28:09| INFO atc_mc finished [took 38.1660s]
+05/11/23 11:28:15| INFO mulmc_sld finished [took 46.3832s]
+05/11/23 11:28:15| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 47.7328s]
+05/11/23 11:28:15| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:28:53| INFO ref finished [took 35.4919s]
+05/11/23 11:28:57| INFO atc_mc finished [took 38.1023s]
+05/11/23 11:29:03| INFO mulmc_sld finished [took 46.4657s]
+05/11/23 11:29:03| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 47.8578s]
+05/11/23 11:29:03| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:29:41| INFO ref finished [took 35.3209s]
+05/11/23 11:29:45| INFO atc_mc finished [took 38.3693s]
+05/11/23 11:29:51| INFO mulmc_sld finished [took 46.5707s]
+05/11/23 11:29:51| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 47.7036s]
+05/11/23 11:29:51| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:30:28| INFO ref finished [took 35.0276s]
+05/11/23 11:30:32| INFO atc_mc finished [took 38.1508s]
+05/11/23 11:30:40| INFO mulmc_sld finished [took 47.6215s]
+05/11/23 11:30:40| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 48.9244s]
+05/11/23 11:30:40| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:31:17| INFO ref finished [took 35.3308s]
+05/11/23 11:31:21| INFO atc_mc finished [took 38.0629s]
+05/11/23 11:31:29| INFO mulmc_sld finished [took 47.8783s]
+05/11/23 11:31:29| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 49.1655s]
+05/11/23 11:31:29| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:32:07| INFO ref finished [took 35.1485s]
+05/11/23 11:32:10| INFO atc_mc finished [took 38.1974s]
+05/11/23 11:32:18| INFO mulmc_sld finished [took 47.6056s]
+05/11/23 11:32:18| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 48.9545s]
+05/11/23 11:32:18| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:32:56| INFO ref finished [took 35.1879s]
+05/11/23 11:32:59| INFO atc_mc finished [took 38.1684s]
+05/11/23 11:33:07| INFO mulmc_sld finished [took 47.5635s]
+05/11/23 11:33:07| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 48.9364s]
+05/11/23 11:33:07| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+05/11/23 11:33:45| INFO ref finished [took 35.5855s]
+05/11/23 11:33:48| INFO atc_mc finished [took 38.1206s]
+05/11/23 11:33:54| INFO mulmc_sld finished [took 45.1957s]
+05/11/23 11:33:54| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 46.5129s]
+----------------------------------------------------------------------------------------------------
+05/11/23 12:02:53| INFO dataset rcv1_CCAT_9prevs
+05/11/23 12:02:58| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:03:01| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
+05/11/23 12:03:37| INFO ref finished [took 34.9513s]
+05/11/23 12:03:41| INFO atc_mc finished [took 37.7710s]
+05/11/23 12:03:47| INFO mulmc_sld finished [took 47.2144s]
+05/11/23 12:03:56| INFO mul_sld finished [took 56.8347s]
+05/11/23 12:03:56| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 58.1052s]
+05/11/23 12:03:56| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:03:59| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
+05/11/23 12:04:36| INFO ref finished [took 35.5921s]
+05/11/23 12:04:40| INFO atc_mc finished [took 38.4587s]
+05/11/23 12:04:46| INFO mulmc_sld finished [took 47.5756s]
+05/11/23 12:04:47| INFO mul_sld finished [took 50.0690s]
+05/11/23 12:04:47| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 51.3609s]
+05/11/23 12:04:47| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:04:50| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
+05/11/23 12:05:28| INFO ref finished [took 36.0399s]
+05/11/23 12:05:31| INFO atc_mc finished [took 38.9414s]
+05/11/23 12:05:38| INFO mulmc_sld finished [took 48.4594s]
+05/11/23 12:05:38| INFO mul_sld finished [took 49.4355s]
+05/11/23 12:05:38| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 50.7799s]
+05/11/23 12:05:38| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:05:41| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
+----------------------------------------------------------------------------------------------------
+05/11/23 12:06:13| INFO dataset rcv1_CCAT_9prevs
+05/11/23 12:06:18| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:07:03| INFO ref finished [took 41.7793s]
+05/11/23 12:07:10| INFO atc_mc finished [took 48.0537s]
+05/11/23 12:07:38| WARNING Method mulne_sld failed. Exception: axis 1 is out of bounds for array of dimension 1
+----------------------------------------------------------------------------------------------------
+05/11/23 12:08:00| INFO dataset rcv1_CCAT_9prevs
+05/11/23 12:08:04| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:08:47| INFO ref finished [took 37.5352s]
+05/11/23 12:08:50| INFO atc_mc finished [took 40.2843s]
+05/11/23 12:08:55| INFO mulne_sld finished [took 47.4558s]
+05/11/23 12:08:56| INFO mulmc_sld finished [took 49.8247s]
+05/11/23 12:09:05| INFO mul_sld finished [took 59.5033s]
+05/11/23 12:09:05| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 60.7605s]
+05/11/23 12:09:05| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:09:47| INFO ref finished [took 37.4891s]
+05/11/23 12:09:52| INFO atc_mc finished [took 40.9763s]
+05/11/23 12:09:58| INFO mulmc_sld finished [took 50.3687s]
+05/11/23 12:09:59| INFO mulne_sld finished [took 50.8494s]
+05/11/23 12:10:00| INFO mul_sld finished [took 53.7955s]
+05/11/23 12:10:00| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 55.1095s]
+05/11/23 12:10:00| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:10:44| INFO ref finished [took 39.3665s]
+05/11/23 12:10:49| INFO atc_mc finished [took 43.1884s]
+05/11/23 12:10:55| INFO mul_sld finished [took 53.2533s]
+05/11/23 12:10:55| INFO mulmc_sld finished [took 52.6179s]
+05/11/23 12:10:56| INFO mulne_sld finished [took 52.7117s]
+05/11/23 12:10:56| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 56.0058s]
+05/11/23 12:10:56| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:11:40| INFO ref finished [took 39.1357s]
+05/11/23 12:11:44| INFO atc_mc finished [took 42.7168s]
+05/11/23 12:11:50| INFO mul_sld finished [took 53.1250s]
+05/11/23 12:11:51| INFO mulmc_sld finished [took 52.6875s]
+05/11/23 12:11:51| INFO mulne_sld finished [took 51.9871s]
+05/11/23 12:11:51| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 55.0715s]
+05/11/23 12:11:51| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:12:34| INFO ref finished [took 38.0624s]
+05/11/23 12:12:38| INFO atc_mc finished [took 40.9414s]
+05/11/23 12:12:45| INFO mul_sld finished [took 52.0220s]
+05/11/23 12:12:46| INFO mulmc_sld finished [took 52.0904s]
+05/11/23 12:12:47| INFO mulne_sld finished [took 52.2011s]
+05/11/23 12:12:47| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 55.6901s]
+05/11/23 12:12:47| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:13:29| INFO ref finished [took 37.9734s]
+05/11/23 12:13:34| INFO atc_mc finished [took 41.4316s]
+05/11/23 12:13:41| INFO mulmc_sld finished [took 51.9276s]
+05/11/23 12:13:42| INFO mul_sld finished [took 53.8232s]
+05/11/23 12:13:43| INFO mulne_sld finished [took 52.4359s]
+05/11/23 12:13:43| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 55.5737s]
+05/11/23 12:13:43| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:14:25| INFO ref finished [took 38.1687s]
+05/11/23 12:14:29| INFO atc_mc finished [took 40.6142s]
+05/11/23 12:14:37| INFO mulmc_sld finished [took 52.4191s]
+05/11/23 12:14:38| INFO mul_sld finished [took 53.7962s]
+05/11/23 12:14:38| INFO mulne_sld finished [took 52.1544s]
+05/11/23 12:14:38| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 55.4465s]
+05/11/23 12:14:38| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:15:21| INFO ref finished [took 38.4494s]
+05/11/23 12:15:25| INFO atc_mc finished [took 40.9944s]
+05/11/23 12:15:32| INFO mulmc_sld finished [took 51.8551s]
+05/11/23 12:15:33| INFO mul_sld finished [took 53.4409s]
+05/11/23 12:15:33| INFO mulne_sld finished [took 51.7256s]
+05/11/23 12:15:33| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 55.1132s]
+05/11/23 12:15:33| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:16:16| INFO ref finished [took 38.2838s]
+05/11/23 12:16:20| INFO atc_mc finished [took 41.3532s]
+05/11/23 12:16:24| INFO mulmc_sld finished [took 49.1257s]
+05/11/23 12:16:26| INFO mulne_sld finished [took 49.8205s]
+05/11/23 12:16:34| INFO mul_sld finished [took 59.1323s]
+05/11/23 12:16:34| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 60.4191s]
+----------------------------------------------------------------------------------------------------
+05/11/23 12:23:45| INFO dataset rcv1_CCAT_9prevs
+05/11/23 12:23:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:24:32| INFO ref finished [took 38.5638s]
+05/11/23 12:24:36| INFO atc_mc finished [took 41.5043s]
+05/11/23 12:27:13| INFO binmc_sld finished [took 201.7673s]
+05/11/23 12:27:14| INFO bin_sld finished [took 203.3515s]
+05/11/23 12:27:17| INFO binne_sld finished [took 204.1403s]
+05/11/23 12:27:17| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 207.1212s]
+05/11/23 12:27:17| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:27:59| INFO ref finished [took 37.8990s]
+05/11/23 12:28:02| INFO atc_mc finished [took 40.1947s]
+05/11/23 12:30:36| INFO bin_sld finished [took 197.7408s]
+05/11/23 12:30:37| INFO binne_sld finished [took 197.0819s]
+05/11/23 12:30:37| INFO binmc_sld finished [took 198.5545s]
+05/11/23 12:30:37| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 200.7762s]
+05/11/23 12:30:37| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:31:19| INFO ref finished [took 37.3749s]
+05/11/23 12:31:23| INFO atc_mc finished [took 40.9120s]
+05/11/23 12:33:54| INFO binmc_sld finished [took 194.5722s]
+05/11/23 12:33:55| INFO bin_sld finished [took 195.8961s]
+05/11/23 12:33:56| INFO binne_sld finished [took 194.9605s]
+05/11/23 12:33:56| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 198.1296s]
+05/11/23 12:33:56| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:34:37| INFO ref finished [took 37.5561s]
+05/11/23 12:34:40| INFO atc_mc finished [took 40.3775s]
+05/11/23 12:37:09| INFO bin_sld finished [took 192.3652s]
+05/11/23 12:37:12| INFO binne_sld finished [took 193.4666s]
+05/11/23 12:37:12| INFO binmc_sld finished [took 194.3499s]
+05/11/23 12:37:12| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 196.3675s]
+05/11/23 12:37:12| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:37:53| INFO ref finished [took 36.5043s]
+05/11/23 12:37:57| INFO atc_mc finished [took 40.0038s]
+05/11/23 12:40:26| INFO bin_sld finished [took 192.4518s]
+05/11/23 12:40:26| INFO binne_sld finished [took 191.2727s]
+05/11/23 12:40:26| INFO binmc_sld finished [took 192.3339s]
+05/11/23 12:40:26| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 194.5333s]
+05/11/23 12:40:27| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:41:07| INFO ref finished [took 36.6809s]
+05/11/23 12:41:11| INFO atc_mc finished [took 39.9520s]
+05/11/23 12:43:40| INFO bin_sld finished [took 192.1873s]
+05/11/23 12:43:40| INFO binmc_sld finished [took 191.7820s]
+05/11/23 12:43:41| INFO binne_sld finished [took 191.9164s]
+05/11/23 12:43:41| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 194.8818s]
+05/11/23 12:43:41| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:44:22| INFO ref finished [took 36.9564s]
+05/11/23 12:44:26| INFO atc_mc finished [took 40.1293s]
+05/11/23 12:46:55| INFO bin_sld finished [took 192.4960s]
+05/11/23 12:46:56| INFO binmc_sld finished [took 192.8281s]
+05/11/23 12:46:58| INFO binne_sld finished [took 193.1524s]
+05/11/23 12:46:58| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 196.2697s]
+05/11/23 12:46:58| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:47:39| INFO ref finished [took 37.2831s]
+05/11/23 12:47:42| INFO atc_mc finished [took 39.7258s]
+05/11/23 12:50:16| INFO binmc_sld finished [took 195.9783s]
+05/11/23 12:50:16| INFO binne_sld finished [took 195.2592s]
+05/11/23 12:50:16| INFO bin_sld finished [took 197.4676s]
+05/11/23 12:50:16| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 198.8232s]
+05/11/23 12:50:16| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+05/11/23 12:50:58| INFO ref finished [took 37.4054s]
+05/11/23 12:51:02| INFO atc_mc finished [took 40.4573s]
+05/11/23 12:53:36| INFO bin_sld finished [took 198.0953s]
+05/11/23 12:53:36| INFO binmc_sld finished [took 197.8028s]
+05/11/23 12:53:37| INFO binne_sld finished [took 197.3027s]
+05/11/23 12:53:37| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 200.2560s]
+----------------------------------------------------------------------------------------------------
+05/11/23 13:29:43| INFO dataset rcv1_CCAT_9prevs
+05/11/23 13:29:47| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+05/11/23 13:30:43| INFO ref finished [took 47.3558s]
+05/11/23 13:30:48| INFO atc_mc finished [took 50.8788s]
+05/11/23 13:30:52| INFO mulne_sld finished [took 60.4851s]
+05/11/23 13:30:53| INFO mulmc_sld finished [took 63.4717s]
+05/11/23 13:33:31| INFO binmc_sld finished [took 222.0328s]
+05/11/23 13:33:33| INFO binne_sld finished [took 223.0449s]
+05/11/23 13:43:18| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': 'max_conf'} (score=0.00644) [took 803.9708s]
+05/11/23 13:44:01| INFO mul_sld_gs finished [took 847.1261s]
+05/11/23 13:49:04| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00589) [took 1151.2473s]
+05/11/23 13:52:06| INFO bin_sld_gs finished [took 1333.4736s]
+05/11/23 13:52:06| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 1338.9046s]
+05/11/23 13:52:06| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+05/11/23 13:53:00| INFO ref finished [took 45.3095s]
+05/11/23 13:53:04| INFO atc_mc finished [took 48.2659s]
+05/11/23 13:53:08| INFO mulmc_sld finished [took 58.9237s]
+05/11/23 13:53:11| INFO mulne_sld finished [took 59.5712s]
+05/11/23 13:55:46| INFO binmc_sld finished [took 218.1315s]
+05/11/23 13:55:51| INFO binne_sld finished [took 220.8543s]
+05/11/23 14:05:34| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00699) [took 800.6256s]
+05/11/23 14:06:16| INFO mul_sld_gs finished [took 842.1616s]
+05/11/23 14:12:14| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00768) [took 1201.3712s]
+05/11/23 14:15:15| INFO bin_sld_gs finished [took 1382.8113s]
+05/11/23 14:15:15| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 1388.8622s]
+05/11/23 14:15:15| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+05/11/23 14:16:11| INFO ref finished [took 46.8666s]
+05/11/23 14:16:15| INFO atc_mc finished [took 49.6779s]
+05/11/23 14:16:19| INFO mulmc_sld finished [took 61.0610s]
+05/11/23 14:16:22| INFO mulne_sld finished [took 62.2089s]
+05/11/23 14:19:02| INFO binmc_sld finished [took 225.5737s]
+05/11/23 14:19:03| INFO binne_sld finished [took 223.9017s]
+05/11/23 14:28:50| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00756) [took 806.7930s]
+05/11/23 14:29:32| INFO mul_sld_gs finished [took 848.7630s]
+05/11/23 14:36:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00781) [took 1240.9138s]
+05/11/23 14:39:04| INFO bin_sld_gs finished [took 1422.5520s]
+05/11/23 14:39:04| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1428.8824s]
+05/11/23 14:39:04| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+05/11/23 14:39:58| INFO ref finished [took 45.7514s]
+05/11/23 14:40:02| INFO atc_mc finished [took 48.3888s]
+05/11/23 14:40:05| INFO mulmc_sld finished [took 59.0537s]
+05/11/23 14:40:09| INFO mulne_sld finished [took 60.9189s]
+05/11/23 14:42:42| INFO binne_sld finished [took 214.5464s]
+05/11/23 14:42:44| INFO binmc_sld finished [took 218.8429s]
+05/11/23 14:52:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00984) [took 792.5474s]
+05/11/23 14:53:05| INFO mul_sld_gs finished [took 834.1824s]
+05/11/23 14:59:56| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.01112) [took 1247.0092s]
+05/11/23 15:02:57| INFO bin_sld_gs finished [took 1427.5051s]
+05/11/23 15:02:57| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1432.9172s]
+05/11/23 15:02:57| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+05/11/23 15:03:49| INFO ref finished [took 44.4148s]
+05/11/23 15:03:54| INFO atc_mc finished [took 47.7566s]
+05/11/23 15:04:00| INFO mulmc_sld finished [took 60.5480s]
+05/11/23 15:04:03| INFO mulne_sld finished [took 61.2226s]
+05/11/23 15:06:30| INFO binmc_sld finished [took 211.9647s]
+05/11/23 15:06:32| INFO binne_sld finished [took 211.4312s]
+05/11/23 15:16:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'max_conf'} (score=0.00571) [took 776.6085s]
+05/11/23 15:16:42| INFO mul_sld_gs finished [took 817.9358s]
+05/11/23 15:23:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'vs', 'confidence': 'entropy'} (score=0.00653) [took 1221.6531s]
+05/11/23 15:26:23| INFO bin_sld_gs finished [took 1400.9688s]
+05/11/23 15:26:23| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 1406.4620s]
+05/11/23 15:26:23| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+05/11/23 15:27:16| INFO ref finished [took 44.3988s]
+05/11/23 15:27:21| INFO atc_mc finished [took 48.5589s]
+05/11/23 15:27:27| INFO mulmc_sld finished [took 61.4269s]
+05/11/23 15:27:29| INFO mulne_sld finished [took 61.8292s]
+05/11/23 15:29:55| INFO binmc_sld finished [took 210.1585s]
+05/11/23 15:29:59| INFO binne_sld finished [took 212.0930s]
+05/11/23 15:39:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'max_conf'} (score=0.00616) [took 771.6071s]
+05/11/23 15:40:03| INFO mul_sld_gs finished [took 813.2905s]
+05/11/23 15:47:04| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': None} (score=0.00544) [took 1234.9832s]
+05/11/23 15:50:10| INFO bin_sld_gs finished [took 1421.7775s]
+05/11/23 15:50:10| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1427.0062s]
+05/11/23 15:50:10| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+05/11/23 15:51:11| INFO ref finished [took 49.7682s]
+05/11/23 15:51:19| INFO atc_mc finished [took 54.2855s]
+05/11/23 15:51:22| INFO mulmc_sld finished [took 68.7688s]
+05/11/23 15:51:26| INFO mulne_sld finished [took 69.3711s]
+05/11/23 15:54:07| INFO binmc_sld finished [took 234.7962s]
+05/11/23 15:54:09| INFO binne_sld finished [took 234.6444s]
+05/11/23 16:03:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'confidence': 'entropy'} (score=0.00765) [took 811.6704s]
+05/11/23 16:04:34| INFO mul_sld_gs finished [took 854.8196s]
+05/11/23 16:11:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': 'max_conf'} (score=0.01234) [took 1252.4784s]
+05/11/23 16:14:10| INFO bin_sld_gs finished [took 1431.7446s]
+05/11/23 16:14:10| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 1439.1145s]
+05/11/23 16:14:10| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+05/11/23 16:15:02| INFO ref finished [took 44.0970s]
+05/11/23 16:15:07| INFO atc_mc finished [took 48.2871s]
+05/11/23 16:15:13| INFO mulmc_sld finished [took 61.0461s]
+05/11/23 16:15:15| INFO mulne_sld finished [took 60.6375s]
+05/11/23 16:17:46| INFO binmc_sld finished [took 215.1734s]
+05/11/23 16:17:49| INFO binne_sld finished [took 215.7846s]
+05/11/23 16:27:15| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'confidence': None} (score=0.00822) [took 778.5688s]
+05/11/23 16:27:56| INFO mul_sld_gs finished [took 819.2615s]
+05/11/23 16:34:16| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'entropy'} (score=0.00894) [took 1200.6639s]
+05/11/23 16:37:21| INFO bin_sld_gs finished [took 1385.9035s]
+05/11/23 16:37:21| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 1391.5055s]
+05/11/23 16:37:21| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+05/11/23 16:38:13| INFO ref finished [took 44.7046s]
+05/11/23 16:38:18| INFO atc_mc finished [took 48.7802s]
+05/11/23 16:38:21| INFO mulmc_sld finished [took 57.4163s]
+05/11/23 16:38:24| INFO mulne_sld finished [took 58.9847s]
+05/11/23 16:40:59| INFO binmc_sld finished [took 216.7311s]
+05/11/23 16:41:01| INFO binne_sld finished [took 216.5312s]
+05/11/23 16:50:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'confidence': 'max_conf'} (score=0.00808) [took 758.6896s]
+05/11/23 16:50:46| INFO mul_sld_gs finished [took 798.8038s]
+05/11/23 16:56:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'confidence': 'entropy'} (score=0.00604) [took 1154.7043s]
+05/11/23 16:59:39| INFO bin_sld_gs finished [took 1332.5521s]
+05/11/23 16:59:39| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 1337.7947s]
+----------------------------------------------------------------------------------------------------
+05/11/23 20:08:46| ERROR estimate comparison failed. Exceprion: 'environ' object has no attribute 'OUT_PATH'
+----------------------------------------------------------------------------------------------------
+05/11/23 20:09:08| ERROR estimate comparison failed. Exceprion: 'environ' object has no attribute 'OUT_PATH'
+----------------------------------------------------------------------------------------------------
+05/11/23 20:09:27| INFO dataset imdb_3prevs
+05/11/23 20:09:34| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 20:09:44| INFO ref finished [took 8.9550s]
+05/11/23 20:09:47| INFO atc_mc finished [took 11.8923s]
+05/11/23 20:09:56| INFO mulmc_sld finished [took 21.3196s]
+05/11/23 20:09:56| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 21.7709s]
+05/11/23 20:09:56| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 20:10:05| INFO ref finished [took 8.6116s]
+05/11/23 20:10:08| INFO atc_mc finished [took 11.6880s]
+05/11/23 20:10:16| INFO mulmc_sld finished [took 19.7793s]
+05/11/23 20:10:16| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.3246s]
+05/11/23 20:10:16| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 20:10:26| INFO ref finished [took 8.6654s]
+05/11/23 20:10:29| INFO atc_mc finished [took 11.6975s]
+05/11/23 20:10:35| INFO mulmc_sld finished [took 18.1478s]
+05/11/23 20:10:35| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.7200s]
+----------------------------------------------------------------------------------------------------
+05/11/23 20:11:42| INFO dataset imdb_3prevs
+05/11/23 20:11:49| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 20:11:58| INFO ref finished [took 8.7146s]
+05/11/23 20:12:02| INFO atc_mc finished [took 11.9672s]
+05/11/23 20:12:10| INFO mulmc_sld finished [took 20.7824s]
+05/11/23 20:12:10| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 21.2293s]
+05/11/23 20:12:10| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 20:12:19| INFO ref finished [took 8.5867s]
+05/11/23 20:12:23| INFO atc_mc finished [took 11.6542s]
+05/11/23 20:12:30| INFO mulmc_sld finished [took 19.6709s]
+05/11/23 20:12:30| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.1802s]
+05/11/23 20:12:30| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 20:12:40| INFO ref finished [took 8.7231s]
+05/11/23 20:12:43| INFO atc_mc finished [took 11.8244s]
+05/11/23 20:12:49| INFO mulmc_sld finished [took 18.0420s]
+05/11/23 20:12:49| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.6102s]
+----------------------------------------------------------------------------------------------------
+05/11/23 20:14:32| INFO dataset imdb_3prevs
+05/11/23 20:14:39| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 20:14:48| INFO ref finished [took 8.6247s]
+05/11/23 20:14:51| INFO atc_mc finished [took 11.6363s]
+05/11/23 20:15:00| INFO mulmc_sld finished [took 20.4634s]
+05/11/23 20:15:00| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 20.9026s]
+05/11/23 20:15:00| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 20:15:09| INFO ref finished [took 8.5219s]
+05/11/23 20:15:12| INFO atc_mc finished [took 11.6739s]
+05/11/23 20:15:20| INFO mulmc_sld finished [took 19.8454s]
+05/11/23 20:15:20| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.3705s]
+05/11/23 20:15:20| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 20:15:29| INFO ref finished [took 8.5948s]
+05/11/23 20:15:32| INFO atc_mc finished [took 11.7465s]
+05/11/23 20:15:39| INFO mulmc_sld finished [took 17.9276s]
+05/11/23 20:15:39| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.4893s]
+----------------------------------------------------------------------------------------------------
+05/11/23 20:16:10| INFO dataset imdb_3prevs
+05/11/23 20:16:17| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+05/11/23 20:16:26| INFO ref finished [took 8.3736s]
+05/11/23 20:16:29| INFO atc_mc finished [took 11.3995s]
+05/11/23 20:16:38| INFO mulmc_sld finished [took 20.4916s]
+05/11/23 20:16:38| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 20.9187s]
+05/11/23 20:16:38| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+05/11/23 20:16:47| INFO ref finished [took 8.4368s]
+05/11/23 20:16:50| INFO atc_mc finished [took 11.4889s]
+05/11/23 20:16:58| INFO mulmc_sld finished [took 19.6803s]
+05/11/23 20:16:58| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 20.2091s]
+05/11/23 20:16:58| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+05/11/23 20:17:08| INFO ref finished [took 8.9281s]
+05/11/23 20:17:11| INFO atc_mc finished [took 11.9333s]
+05/11/23 20:17:17| INFO mulmc_sld finished [took 18.2367s]
+05/11/23 20:17:17| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 18.8309s]
+----------------------------------------------------------------------------------------------------
+06/11/23 01:34:48| INFO dataset imdb_3prevs
+06/11/23 01:34:59| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+06/11/23 01:35:18| INFO ref finished [took 18.0987s]
+06/11/23 01:35:24| INFO atc_mc finished [took 24.9118s]
+06/11/23 01:35:31| INFO mulmc_sld finished [took 32.0631s]
+06/11/23 01:35:31| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 32.6119s]
+06/11/23 01:35:31| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+06/11/23 01:35:51| INFO ref finished [took 18.7770s]
+06/11/23 01:35:58| INFO atc_mc finished [took 25.5592s]
+06/11/23 01:36:04| INFO mulmc_sld finished [took 31.9103s]
+06/11/23 01:36:04| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 32.5205s]
+06/11/23 01:36:04| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+06/11/23 01:36:23| INFO ref finished [took 18.5730s]
+06/11/23 01:36:31| INFO atc_mc finished [took 25.8019s]
+06/11/23 01:36:33| INFO mulmc_sld finished [took 28.9526s]
+06/11/23 01:36:33| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 29.5292s]
+----------------------------------------------------------------------------------------------------
+06/11/23 02:06:40| INFO dataset imdb_3prevs
+06/11/23 02:06:47| INFO Dataset sample 0.20 of dataset imdb_3prevs started
+06/11/23 02:06:56| INFO ref finished [took 9.0989s]
+06/11/23 02:06:59| INFO atc_mc finished [took 12.2513s]
+06/11/23 03:01:43| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'vs', 'quantifier__exact_train_prev': False, 'confidence': 'max_conf'} (score=0.00738) [took 3296.0714s]
+06/11/23 03:01:56| INFO mul_sld_gs finished [took 3309.2417s]
+06/11/23 03:01:56| INFO Dataset sample 0.20 of dataset imdb_3prevs finished [took 3309.7038s]
+06/11/23 03:01:56| INFO Dataset sample 0.50 of dataset imdb_3prevs started
+06/11/23 03:02:06| INFO ref finished [took 8.5518s]
+06/11/23 03:02:09| INFO atc_mc finished [took 11.4390s]
+06/11/23 03:54:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00899) [took 3146.2364s]
+06/11/23 03:54:37| INFO mul_sld_gs finished [took 3159.8209s]
+06/11/23 03:54:37| INFO Dataset sample 0.50 of dataset imdb_3prevs finished [took 3160.3546s]
+06/11/23 03:54:37| INFO Dataset sample 0.80 of dataset imdb_3prevs started
+06/11/23 03:54:46| INFO ref finished [took 8.2678s]
+06/11/23 03:54:48| INFO atc_mc finished [took 11.0430s]
+06/11/23 04:47:50| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': False, 'confidence': 'entropy'} (score=0.00770) [took 3193.1812s]
+06/11/23 04:48:04| INFO mul_sld_gs finished [took 3206.9550s]
+06/11/23 04:48:04| INFO Dataset sample 0.80 of dataset imdb_3prevs finished [took 3207.5040s]
+----------------------------------------------------------------------------------------------------
+06/11/23 05:14:48| INFO dataset rcv1_CCAT_9prevs
+06/11/23 05:14:53| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:15:55| INFO ref finished [took 48.0242s]
+06/11/23 05:16:01| INFO atc_mc finished [took 51.7851s]
+06/11/23 05:16:04| INFO mul_pacc finished [took 58.4704s]
+06/11/23 05:16:04| INFO mulne_sld finished [took 62.7354s]
+06/11/23 05:16:04| INFO mulmc_sld finished [took 66.2593s]
+06/11/23 05:16:14| INFO mul_sld finished [took 78.2483s]
+06/11/23 05:18:40| INFO bin_pacc finished [took 217.0012s]
+06/11/23 05:18:43| INFO bin_sld finished [took 227.8835s]
+06/11/23 05:18:43| INFO binne_sld finished [took 223.2764s]
+06/11/23 05:18:44| INFO binmc_sld finished [took 226.7324s]
+06/11/23 05:18:44| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 230.5906s]
+06/11/23 05:18:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:19:44| INFO ref finished [took 49.5147s]
+06/11/23 05:19:51| INFO atc_mc finished [took 54.8022s]
+06/11/23 05:19:53| INFO mul_pacc finished [took 60.3260s]
+06/11/23 05:19:55| INFO mulmc_sld finished [took 67.0280s]
+06/11/23 05:19:56| INFO mul_sld finished [took 70.4092s]
+06/11/23 05:19:58| INFO mulne_sld finished [took 67.3468s]
+06/11/23 05:22:30| INFO bin_sld finished [took 224.7344s]
+06/11/23 05:22:30| INFO bin_pacc finished [took 218.3044s]
+06/11/23 05:22:30| INFO binmc_sld finished [took 223.3607s]
+06/11/23 05:22:33| INFO binne_sld finished [took 223.6042s]
+06/11/23 05:22:33| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 229.0745s]
+06/11/23 05:22:33| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:23:32| INFO ref finished [took 48.1565s]
+06/11/23 05:23:37| INFO atc_mc finished [took 52.1124s]
+06/11/23 05:23:40| INFO mul_pacc finished [took 58.0112s]
+06/11/23 05:23:40| INFO mul_sld finished [took 65.2727s]
+06/11/23 05:23:42| INFO mulmc_sld finished [took 64.5943s]
+06/11/23 05:23:43| INFO mulne_sld finished [took 63.9053s]
+06/11/23 05:26:13| INFO bin_sld finished [took 218.6511s]
+06/11/23 05:26:16| INFO bin_pacc finished [took 215.1485s]
+06/11/23 05:26:17| INFO binne_sld finished [took 218.6855s]
+06/11/23 05:26:17| INFO binmc_sld finished [took 221.2605s]
+06/11/23 05:26:17| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 224.5608s]
+06/11/23 05:26:17| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:27:15| INFO ref finished [took 48.2181s]
+06/11/23 05:27:21| INFO atc_mc finished [took 52.3420s]
+06/11/23 05:27:23| INFO mul_pacc finished [took 57.1950s]
+06/11/23 05:27:24| INFO mul_sld finished [took 64.4722s]
+06/11/23 05:27:26| INFO mulmc_sld finished [took 64.1870s]
+06/11/23 05:27:27| INFO mulne_sld finished [took 63.7407s]
+06/11/23 05:29:52| INFO bin_sld finished [took 213.1913s]
+06/11/23 05:29:53| INFO bin_pacc finished [took 208.1322s]
+06/11/23 05:29:53| INFO binmc_sld finished [took 212.6473s]
+06/11/23 05:29:57| INFO binne_sld finished [took 214.5243s]
+06/11/23 05:29:57| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 219.5765s]
+06/11/23 05:29:57| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:30:55| INFO ref finished [took 47.7289s]
+06/11/23 05:31:01| INFO atc_mc finished [took 52.1531s]
+06/11/23 05:31:03| INFO mul_pacc finished [took 57.3804s]
+06/11/23 05:31:06| INFO mul_sld finished [took 66.9237s]
+06/11/23 05:31:06| INFO mulmc_sld finished [took 65.3230s]
+06/11/23 05:31:09| INFO mulne_sld finished [took 65.6645s]
+06/11/23 05:33:33| INFO bin_sld finished [took 214.3242s]
+06/11/23 05:33:34| INFO bin_pacc finished [took 209.3862s]
+06/11/23 05:33:35| INFO binmc_sld finished [took 214.4687s]
+06/11/23 05:33:37| INFO binne_sld finished [took 214.7267s]
+06/11/23 05:33:37| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 220.0212s]
+06/11/23 05:33:37| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:34:35| INFO ref finished [took 48.0021s]
+06/11/23 05:34:41| INFO atc_mc finished [took 52.2171s]
+06/11/23 05:34:43| INFO mul_pacc finished [took 57.2348s]
+06/11/23 05:34:46| INFO mul_sld finished [took 67.0899s]
+06/11/23 05:34:47| INFO mulmc_sld finished [took 66.1078s]
+06/11/23 05:34:49| INFO mulne_sld finished [took 66.0237s]
+06/11/23 05:37:13| INFO bin_sld finished [took 214.9942s]
+06/11/23 05:37:13| INFO binmc_sld finished [took 213.1574s]
+06/11/23 05:37:14| INFO bin_pacc finished [took 209.1347s]
+06/11/23 05:37:17| INFO binne_sld finished [took 214.9703s]
+06/11/23 05:37:17| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 220.1235s]
+06/11/23 05:37:17| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:38:15| INFO ref finished [took 47.8227s]
+06/11/23 05:38:20| INFO atc_mc finished [took 51.9364s]
+06/11/23 05:38:23| INFO mul_pacc finished [took 56.9053s]
+06/11/23 05:38:27| INFO mul_sld finished [took 67.4535s]
+06/11/23 05:38:27| INFO mulmc_sld finished [took 65.5956s]
+06/11/23 05:38:30| INFO mulne_sld finished [took 66.0476s]
+06/11/23 05:40:55| INFO bin_pacc finished [took 210.0633s]
+06/11/23 05:40:56| INFO binmc_sld finished [took 215.3452s]
+06/11/23 05:40:56| INFO bin_sld finished [took 217.8091s]
+06/11/23 05:40:59| INFO binne_sld finished [took 216.8970s]
+06/11/23 05:40:59| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 222.2971s]
+06/11/23 05:40:59| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:41:57| INFO ref finished [took 47.6970s]
+06/11/23 05:42:03| INFO atc_mc finished [took 52.0893s]
+06/11/23 05:42:05| INFO mul_pacc finished [took 56.6428s]
+06/11/23 05:42:09| INFO mul_sld finished [took 66.8810s]
+06/11/23 05:42:09| INFO mulmc_sld finished [took 65.8427s]
+06/11/23 05:42:11| INFO mulne_sld finished [took 64.8594s]
+06/11/23 05:44:36| INFO bin_pacc finished [took 208.7884s]
+06/11/23 05:44:38| INFO bin_sld finished [took 216.6052s]
+06/11/23 05:44:38| INFO binmc_sld finished [took 215.5486s]
+06/11/23 05:44:43| INFO binne_sld finished [took 217.9926s]
+06/11/23 05:44:43| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 223.2270s]
+06/11/23 05:44:43| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+06/11/23 05:45:40| INFO ref finished [took 48.0710s]
+06/11/23 05:45:46| INFO atc_mc finished [took 52.0992s]
+06/11/23 05:45:48| INFO mul_pacc finished [took 56.6568s]
+06/11/23 05:45:49| INFO mulmc_sld finished [took 61.7314s]
+06/11/23 05:45:52| INFO mulne_sld finished [took 62.7505s]
+06/11/23 05:45:59| INFO mul_sld finished [took 73.7681s]
+06/11/23 05:48:18| INFO bin_pacc finished [took 208.2267s]
+06/11/23 05:48:23| INFO bin_sld finished [took 218.9333s]
+06/11/23 05:48:24| INFO binmc_sld finished [took 218.0032s]
+06/11/23 05:48:27| INFO binne_sld finished [took 219.2450s]
+06/11/23 05:48:27| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 224.3446s]
+06/11/23 05:49:49| INFO dataset imdb_9prevs
+06/11/23 05:49:57| INFO Dataset sample 0.10 of dataset imdb_9prevs started
+06/11/23 05:50:12| INFO ref finished [took 13.3064s]
+06/11/23 05:50:17| INFO atc_mc finished [took 17.3508s]
+06/11/23 05:50:19| INFO mul_pacc finished [took 20.0802s]
+06/11/23 05:50:22| INFO mulne_sld finished [took 23.6723s]
+06/11/23 05:50:24| INFO mulmc_sld finished [took 25.5159s]
+06/11/23 05:50:39| INFO mul_sld finished [took 40.7099s]
+06/11/23 05:52:55| INFO bin_pacc finished [took 176.3728s]
+06/11/23 05:53:05| INFO binmc_sld finished [took 186.8240s]
+06/11/23 05:53:06| INFO binne_sld finished [took 187.6585s]
+06/11/23 05:53:07| INFO bin_sld finished [took 189.1728s]
+06/11/23 05:53:07| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 189.6034s]
+06/11/23 05:53:07| INFO Dataset sample 0.20 of dataset imdb_9prevs started
+06/11/23 05:53:22| INFO ref finished [took 13.2778s]
+06/11/23 05:53:26| INFO atc_mc finished [took 17.4491s]
+06/11/23 05:53:28| INFO mul_pacc finished [took 19.9359s]
+06/11/23 05:53:40| INFO mulmc_sld finished [took 31.6686s]
+06/11/23 05:53:44| INFO mulne_sld finished [took 35.2085s]
+06/11/23 05:53:44| INFO mul_sld finished [took 36.2502s]
+06/11/23 05:56:05| INFO bin_pacc finished [took 177.0225s]
+06/11/23 05:56:13| INFO binmc_sld finished [took 185.4811s]
+06/11/23 05:56:15| INFO bin_sld finished [took 187.1039s]
+06/11/23 05:56:16| INFO binne_sld finished [took 187.3163s]
+06/11/23 05:56:16| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 188.4781s]
+06/11/23 05:56:16| INFO Dataset sample 0.30 of dataset imdb_9prevs started
+06/11/23 05:56:31| INFO ref finished [took 13.4513s]
+06/11/23 05:56:36| INFO atc_mc finished [took 18.1025s]
+06/11/23 05:56:38| INFO mul_pacc finished [took 20.3997s]
+06/11/23 05:56:45| INFO mulmc_sld finished [took 28.4298s]
+06/11/23 05:56:46| INFO mulne_sld finished [took 28.8678s]
+06/11/23 05:56:46| INFO mul_sld finished [took 29.5573s]
+06/11/23 05:59:11| INFO bin_pacc finished [took 174.0262s]
+06/11/23 05:59:17| INFO binmc_sld finished [took 180.1998s]
+06/11/23 05:59:18| INFO binne_sld finished [took 181.2200s]
+06/11/23 05:59:19| INFO bin_sld finished [took 182.1672s]
+06/11/23 05:59:19| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 183.0515s]
+06/11/23 05:59:19| INFO Dataset sample 0.40 of dataset imdb_9prevs started
+06/11/23 05:59:34| INFO ref finished [took 13.5163s]
+06/11/23 05:59:39| INFO atc_mc finished [took 17.9856s]
+06/11/23 05:59:41| INFO mul_pacc finished [took 20.7441s]
+06/11/23 05:59:49| INFO mulmc_sld finished [took 29.2747s]
+06/11/23 05:59:50| INFO mulne_sld finished [took 29.6624s]
+06/11/23 05:59:50| INFO mul_sld finished [took 30.3432s]
+06/11/23 06:02:17| INFO bin_pacc finished [took 176.7354s]
+06/11/23 06:02:19| INFO binmc_sld finished [took 179.9981s]
+06/11/23 06:02:21| INFO bin_sld finished [took 181.6844s]
+06/11/23 06:02:22| INFO binne_sld finished [took 182.0846s]
+06/11/23 06:02:22| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 183.2033s]
+06/11/23 06:02:22| INFO Dataset sample 0.50 of dataset imdb_9prevs started
+06/11/23 06:02:37| INFO ref finished [took 13.4688s]
+06/11/23 06:02:42| INFO atc_mc finished [took 18.0218s]
+06/11/23 06:02:44| INFO mul_pacc finished [took 20.5800s]
+06/11/23 06:02:52| INFO mulmc_sld finished [took 29.0192s]
+06/11/23 06:02:52| INFO mul_sld finished [took 29.4403s]
+06/11/23 06:02:52| INFO mulne_sld finished [took 29.1611s]
+06/11/23 06:05:19| INFO bin_pacc finished [took 175.5125s]
+06/11/23 06:05:23| INFO binmc_sld finished [took 180.0427s]
+06/11/23 06:05:25| INFO binne_sld finished [took 182.5814s]
+06/11/23 06:05:26| INFO bin_sld finished [took 183.2892s]
+06/11/23 06:05:26| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 183.8611s]
+06/11/23 06:05:26| INFO Dataset sample 0.60 of dataset imdb_9prevs started
+06/11/23 06:05:41| INFO ref finished [took 13.4643s]
+06/11/23 06:05:45| INFO atc_mc finished [took 17.9768s]
+06/11/23 06:05:48| INFO mul_pacc finished [took 20.7525s]
+06/11/23 06:05:55| INFO mulmc_sld finished [took 28.8234s]
+06/11/23 06:05:55| INFO mulne_sld finished [took 28.6537s]
+06/11/23 06:05:56| INFO mul_sld finished [took 29.6167s]
+06/11/23 06:08:24| INFO bin_pacc finished [took 176.5335s]
+06/11/23 06:08:27| INFO binmc_sld finished [took 180.4803s]
+06/11/23 06:08:28| INFO bin_sld finished [took 181.6676s]
+06/11/23 06:08:29| INFO binne_sld finished [took 182.0534s]
+06/11/23 06:08:29| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 183.0240s]
+06/11/23 06:08:29| INFO Dataset sample 0.70 of dataset imdb_9prevs started
+06/11/23 06:08:44| INFO ref finished [took 13.7566s]
+06/11/23 06:08:49| INFO atc_mc finished [took 17.9495s]
+06/11/23 06:08:51| INFO mul_pacc finished [took 20.5859s]
+06/11/23 06:08:57| INFO mulmc_sld finished [took 27.4370s]
+06/11/23 06:08:58| INFO mul_sld finished [took 28.3224s]
+06/11/23 06:08:58| INFO mulne_sld finished [took 28.1390s]
+06/11/23 06:11:26| INFO bin_pacc finished [took 175.7412s]
+06/11/23 06:11:31| INFO binmc_sld finished [took 181.4310s]
+06/11/23 06:11:32| INFO binne_sld finished [took 182.0095s]
+06/11/23 06:11:33| INFO bin_sld finished [took 183.6520s]
+06/11/23 06:11:33| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 184.2005s]
+06/11/23 06:11:33| INFO Dataset sample 0.80 of dataset imdb_9prevs started
+06/11/23 06:11:48| INFO ref finished [took 13.5418s]
+06/11/23 06:11:53| INFO atc_mc finished [took 17.8150s]
+06/11/23 06:11:55| INFO mul_pacc finished [took 20.4761s]
+06/11/23 06:12:01| INFO mulmc_sld finished [took 27.2741s]
+06/11/23 06:12:02| INFO mulne_sld finished [took 27.2693s]
+06/11/23 06:12:02| INFO mul_sld finished [took 28.3364s]
+06/11/23 06:14:30| INFO bin_pacc finished [took 175.7637s]
+06/11/23 06:14:37| INFO binmc_sld finished [took 183.2422s]
+06/11/23 06:14:38| INFO bin_sld finished [took 184.1064s]
+06/11/23 06:14:39| INFO binne_sld finished [took 184.9073s]
+06/11/23 06:14:39| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 186.2580s]
+06/11/23 06:14:39| INFO Dataset sample 0.90 of dataset imdb_9prevs started
+06/11/23 06:14:41| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 06:14:41| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 06:14:52| INFO ref finished [took 11.6315s]
+06/11/23 06:14:56| INFO atc_mc finished [took 15.3068s]
+06/11/23 06:15:01| INFO mulne_sld finished [took 21.1133s]
+06/11/23 06:15:02| INFO mulmc_sld finished [took 22.2375s]
+06/11/23 06:15:08| INFO mul_sld finished [took 27.8149s]
+06/11/23 06:17:32| INFO binne_sld finished [took 171.8722s]
+06/11/23 06:17:32| INFO bin_sld finished [took 172.4710s]
+06/11/23 06:17:33| INFO binmc_sld finished [took 172.8193s]
+06/11/23 06:17:33| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 173.4411s]
+06/11/23 06:18:54| INFO dataset rcv1_GCAT_9prevs
+06/11/23 06:18:59| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:19:11| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 06:19:11| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 06:19:54| INFO ref finished [took 42.0769s]
+06/11/23 06:19:59| INFO atc_mc finished [took 45.5011s]
+06/11/23 06:20:14| INFO mulne_sld finished [took 66.0516s]
+06/11/23 06:20:15| INFO mul_sld finished [took 73.1171s]
+06/11/23 06:20:17| INFO mulmc_sld finished [took 72.1930s]
+06/11/23 06:22:23| INFO bin_sld finished [took 203.0368s]
+06/11/23 06:22:27| INFO binmc_sld finished [took 203.2975s]
+06/11/23 06:22:29| INFO binne_sld finished [took 202.7501s]
+06/11/23 06:22:29| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 210.2201s]
+06/11/23 06:22:29| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:23:26| INFO ref finished [took 46.6022s]
+06/11/23 06:23:31| INFO atc_mc finished [took 50.3293s]
+06/11/23 06:23:33| INFO mul_pacc finished [took 54.9265s]
+06/11/23 06:23:46| INFO mul_sld finished [took 74.9035s]
+06/11/23 06:23:52| INFO mulne_sld finished [took 76.2697s]
+06/11/23 06:23:54| INFO mulmc_sld finished [took 80.8754s]
+06/11/23 06:26:06| INFO bin_pacc finished [took 209.7751s]
+06/11/23 06:26:08| INFO bin_sld finished [took 217.8889s]
+06/11/23 06:26:13| INFO binmc_sld finished [took 220.7753s]
+06/11/23 06:26:14| INFO binne_sld finished [took 219.7510s]
+06/11/23 06:26:14| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 224.9268s]
+06/11/23 06:26:14| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:27:10| INFO ref finished [took 46.4938s]
+06/11/23 06:27:16| INFO atc_mc finished [took 50.5904s]
+06/11/23 06:27:18| INFO mul_pacc finished [took 55.4949s]
+06/11/23 06:27:26| INFO mulmc_sld finished [took 67.7140s]
+06/11/23 06:27:26| INFO mul_sld finished [took 70.0891s]
+06/11/23 06:27:28| INFO mulne_sld finished [took 68.1806s]
+06/11/23 06:29:50| INFO bin_pacc finished [took 208.6091s]
+06/11/23 06:29:51| INFO binmc_sld finished [took 213.7985s]
+06/11/23 06:29:51| INFO bin_sld finished [took 215.8158s]
+06/11/23 06:29:55| INFO binne_sld finished [took 215.5523s]
+06/11/23 06:29:55| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 220.4589s]
+06/11/23 06:29:55| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:30:51| INFO ref finished [took 46.3752s]
+06/11/23 06:30:56| INFO atc_mc finished [took 50.7062s]
+06/11/23 06:30:58| INFO mul_pacc finished [took 55.2260s]
+06/11/23 06:31:01| INFO mul_sld finished [took 64.2359s]
+06/11/23 06:31:02| INFO mulmc_sld finished [took 63.5099s]
+06/11/23 06:31:04| INFO mulne_sld finished [took 62.9188s]
+06/11/23 06:33:29| INFO bin_sld finished [took 213.2716s]
+06/11/23 06:33:30| INFO bin_pacc finished [took 208.6574s]
+06/11/23 06:33:31| INFO binmc_sld finished [took 213.1856s]
+06/11/23 06:33:33| INFO binne_sld finished [took 213.2771s]
+06/11/23 06:33:33| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 218.1742s]
+06/11/23 06:33:33| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:34:29| INFO ref finished [took 46.6793s]
+06/11/23 06:34:34| INFO atc_mc finished [took 50.9915s]
+06/11/23 06:34:37| INFO mul_pacc finished [took 55.9725s]
+06/11/23 06:34:38| INFO mul_sld finished [took 63.1317s]
+06/11/23 06:34:40| INFO mulmc_sld finished [took 62.7473s]
+06/11/23 06:34:41| INFO mulne_sld finished [took 62.1303s]
+06/11/23 06:37:08| INFO bin_pacc finished [took 207.7854s]
+06/11/23 06:37:08| INFO bin_sld finished [took 213.7945s]
+06/11/23 06:37:08| INFO binmc_sld finished [took 212.6207s]
+06/11/23 06:37:12| INFO binne_sld finished [took 213.8742s]
+06/11/23 06:37:12| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 218.7265s]
+06/11/23 06:37:12| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:38:08| INFO ref finished [took 46.6057s]
+06/11/23 06:38:14| INFO atc_mc finished [took 51.1055s]
+06/11/23 06:38:15| INFO mul_pacc finished [took 55.5338s]
+06/11/23 06:38:17| INFO mul_sld finished [took 63.2113s]
+06/11/23 06:38:18| INFO mulmc_sld finished [took 62.2265s]
+06/11/23 06:38:20| INFO mulne_sld finished [took 61.9918s]
+06/11/23 06:40:46| INFO bin_pacc finished [took 207.5094s]
+06/11/23 06:40:46| INFO bin_sld finished [took 213.6350s]
+06/11/23 06:40:47| INFO binmc_sld finished [took 212.8363s]
+06/11/23 06:40:49| INFO binne_sld finished [took 212.2587s]
+06/11/23 06:40:49| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 217.1976s]
+06/11/23 06:40:49| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:41:44| INFO ref finished [took 45.9582s]
+06/11/23 06:41:50| INFO atc_mc finished [took 50.0401s]
+06/11/23 06:41:54| INFO mul_sld finished [took 62.6045s]
+06/11/23 06:41:54| INFO mulmc_sld finished [took 61.4168s]
+06/11/23 06:41:56| INFO mulne_sld finished [took 61.3708s]
+06/11/23 06:42:00| INFO mul_pacc finished [took 62.6486s]
+06/11/23 06:44:23| INFO bin_sld finished [took 212.5992s]
+06/11/23 06:44:23| INFO bin_pacc finished [took 207.5241s]
+06/11/23 06:44:24| INFO binmc_sld finished [took 212.2794s]
+06/11/23 06:44:27| INFO binne_sld finished [took 212.8325s]
+06/11/23 06:44:27| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 217.7909s]
+06/11/23 06:44:27| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:45:23| INFO ref finished [took 46.6997s]
+06/11/23 06:45:28| INFO atc_mc finished [took 50.6417s]
+06/11/23 06:45:30| INFO mul_sld finished [took 61.5352s]
+06/11/23 06:45:31| INFO mul_pacc finished [took 55.9055s]
+06/11/23 06:45:31| INFO mulmc_sld finished [took 60.6608s]
+06/11/23 06:45:33| INFO mulne_sld finished [took 60.1616s]
+06/11/23 06:48:01| INFO bin_pacc finished [took 207.7543s]
+06/11/23 06:48:02| INFO bin_sld finished [took 213.7056s]
+06/11/23 06:48:03| INFO binmc_sld finished [took 213.7901s]
+06/11/23 06:48:04| INFO binne_sld finished [took 212.4421s]
+06/11/23 06:48:04| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 217.4465s]
+06/11/23 06:48:04| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
+06/11/23 06:48:06| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 06:48:07| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 06:48:09| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 06:48:11| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 06:48:13| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 06:48:49| INFO ref finished [took 36.4085s]
+06/11/23 06:48:53| INFO atc_mc finished [took 39.1380s]
+06/11/23 06:48:54| INFO mulmc_sld finished [took 46.0254s]
+06/11/23 06:48:55| INFO mulne_sld finished [took 45.1935s]
+06/11/23 06:49:00| INFO mul_sld finished [took 53.9145s]
+06/11/23 06:49:00| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 55.9159s]
+06/11/23 06:50:22| INFO dataset rcv1_MCAT_9prevs
+06/11/23 06:50:27| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
+06/11/23 06:51:29| INFO ref finished [took 47.8430s]
+06/11/23 06:51:34| INFO atc_mc finished [took 51.2418s]
+06/11/23 06:51:36| INFO mul_pacc finished [took 56.8770s]
+06/11/23 06:52:00| INFO mulne_sld finished [took 85.8579s]
+06/11/23 06:52:00| INFO mul_sld finished [took 90.6401s]
+06/11/23 06:52:12| INFO mulmc_sld finished [took 100.3728s]
+06/11/23 06:54:15| INFO bin_pacc finished [took 217.8843s]
+06/11/23 06:54:15| INFO bin_sld finished [took 226.6925s]
+06/11/23 06:54:17| INFO binne_sld finished [took 224.5785s]
+06/11/23 06:54:17| INFO binmc_sld finished [took 226.9490s]
+06/11/23 06:54:17| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 229.9256s]
+06/11/23 06:54:17| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
+06/11/23 06:55:14| INFO ref finished [took 46.7323s]
+06/11/23 06:55:20| INFO atc_mc finished [took 51.0126s]
+06/11/23 06:55:22| INFO mul_pacc finished [took 55.8357s]
+06/11/23 06:55:23| INFO mulmc_sld finished [took 62.0464s]
+06/11/23 06:55:24| INFO mul_sld finished [took 64.8106s]
+06/11/23 06:55:25| INFO mulne_sld finished [took 61.6750s]
+06/11/23 06:57:56| INFO bin_pacc finished [took 210.8901s]
+06/11/23 06:57:56| INFO bin_sld finished [took 217.3461s]
+06/11/23 06:57:57| INFO binmc_sld finished [took 216.6599s]
+06/11/23 06:58:00| INFO binne_sld finished [took 216.9668s]
+06/11/23 06:58:00| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 222.3450s]
+06/11/23 06:58:00| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
+06/11/23 06:58:57| INFO ref finished [took 47.5989s]
+06/11/23 06:59:02| INFO atc_mc finished [took 51.5080s]
+06/11/23 06:59:04| INFO mul_pacc finished [took 56.1671s]
+06/11/23 06:59:09| INFO mulmc_sld finished [took 65.0229s]
+06/11/23 06:59:10| INFO mul_sld finished [took 68.8366s]
+06/11/23 06:59:11| INFO mulne_sld finished [took 65.2964s]
+06/11/23 07:01:39| INFO bin_pacc finished [took 212.3570s]
+06/11/23 07:01:40| INFO bin_sld finished [took 219.3886s]
+06/11/23 07:01:42| INFO binmc_sld finished [took 219.1471s]
+06/11/23 07:01:43| INFO binne_sld finished [took 218.3714s]
+06/11/23 07:01:43| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 223.2305s]
+06/11/23 07:01:43| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
+06/11/23 07:02:40| INFO ref finished [took 47.3513s]
+06/11/23 07:02:45| INFO atc_mc finished [took 51.3858s]
+06/11/23 07:02:47| INFO mul_pacc finished [took 56.3829s]
+06/11/23 07:02:50| INFO mul_sld finished [took 64.9257s]
+06/11/23 07:02:50| INFO mulmc_sld finished [took 63.6515s]
+06/11/23 07:02:52| INFO mulne_sld finished [took 63.8008s]
+06/11/23 07:05:22| INFO bin_pacc finished [took 211.8418s]
+06/11/23 07:05:22| INFO binmc_sld finished [took 216.4950s]
+06/11/23 07:05:22| INFO bin_sld finished [took 218.2730s]
+06/11/23 07:05:25| INFO binne_sld finished [took 217.6016s]
+06/11/23 07:05:25| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 222.4416s]
+06/11/23 07:05:25| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
+06/11/23 07:06:22| INFO ref finished [took 47.3783s]
+06/11/23 07:06:27| INFO atc_mc finished [took 51.1924s]
+06/11/23 07:06:30| INFO mul_pacc finished [took 56.3115s]
+06/11/23 07:06:34| INFO mul_sld finished [took 66.6559s]
+06/11/23 07:06:34| INFO mulmc_sld finished [took 65.2448s]
+06/11/23 07:06:37| INFO mulne_sld finished [took 65.6557s]
+06/11/23 07:09:03| INFO binmc_sld finished [took 214.4549s]
+06/11/23 07:09:03| INFO bin_sld finished [took 216.8097s]
+06/11/23 07:09:04| INFO bin_pacc finished [took 211.9484s]
+06/11/23 07:09:06| INFO binne_sld finished [took 215.5010s]
+06/11/23 07:09:06| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 220.4788s]
+06/11/23 07:09:06| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
+06/11/23 07:10:03| INFO ref finished [took 47.0882s]
+06/11/23 07:10:08| INFO atc_mc finished [took 51.1826s]
+06/11/23 07:10:10| INFO mul_pacc finished [took 55.8766s]
+06/11/23 07:10:14| INFO mulmc_sld finished [took 64.7175s]
+06/11/23 07:10:15| INFO mul_sld finished [took 67.2892s]
+06/11/23 07:10:17| INFO mulne_sld finished [took 64.9305s]
+06/11/23 07:12:40| INFO bin_pacc finished [took 207.6921s]
+06/11/23 07:12:41| INFO binmc_sld finished [took 212.3821s]
+06/11/23 07:12:41| INFO bin_sld finished [took 214.5241s]
+06/11/23 07:12:43| INFO binne_sld finished [took 212.5115s]
+06/11/23 07:12:43| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 217.3597s]
+06/11/23 07:12:43| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
+06/11/23 07:13:39| INFO ref finished [took 46.5374s]
+06/11/23 07:13:45| INFO atc_mc finished [took 51.0121s]
+06/11/23 07:13:47| INFO mul_pacc finished [took 55.4950s]
+06/11/23 07:13:52| INFO mulmc_sld finished [took 64.7651s]
+06/11/23 07:13:52| INFO mul_sld finished [took 67.0632s]
+06/11/23 07:13:54| INFO mulne_sld finished [took 65.2533s]
+06/11/23 07:16:18| INFO bin_pacc finished [took 207.9541s]
+06/11/23 07:16:19| INFO bin_sld finished [took 214.6495s]
+06/11/23 07:16:19| INFO binmc_sld finished [took 213.2167s]
+06/11/23 07:16:24| INFO binne_sld finished [took 215.5646s]
+06/11/23 07:16:24| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 220.4851s]
+06/11/23 07:16:24| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
+06/11/23 07:17:20| INFO ref finished [took 46.7655s]
+06/11/23 07:17:25| INFO atc_mc finished [took 50.9430s]
+06/11/23 07:17:27| INFO mul_pacc finished [took 55.4948s]
+06/11/23 07:17:44| INFO mul_sld finished [took 78.5002s]
+06/11/23 07:17:46| INFO mulmc_sld finished [took 78.7519s]
+06/11/23 07:17:48| INFO mulne_sld finished [took 78.4293s]
+06/11/23 07:19:59| INFO bin_pacc finished [took 208.5200s]
+06/11/23 07:20:02| INFO bin_sld finished [took 216.9046s]
+06/11/23 07:20:03| INFO binmc_sld finished [took 216.2736s]
+06/11/23 07:20:03| INFO binne_sld finished [took 214.9573s]
+06/11/23 07:20:03| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 219.7592s]
+06/11/23 07:20:03| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
+06/11/23 07:20:05| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 07:20:06| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 07:20:08| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 07:20:10| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 07:20:12| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 07:20:48| INFO ref finished [took 36.6985s]
+06/11/23 07:20:52| INFO atc_mc finished [took 39.8292s]
+06/11/23 07:20:55| INFO mulmc_sld finished [took 48.0943s]
+06/11/23 07:20:56| INFO mul_sld finished [took 50.2138s]
+06/11/23 07:20:57| INFO mulne_sld finished [took 47.9755s]
+06/11/23 07:20:57| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 53.5645s]
+----------------------------------------------------------------------------------------------------
+----------------------------------------------------------------------------------------------------
+06/11/23 10:25:08| INFO dataset rcv1_CCAT_1prevs
+06/11/23 10:25:12| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs started
+06/11/23 10:26:02| INFO ref finished [took 43.6300s]
+06/11/23 10:26:05| INFO atc_mc finished [took 46.2297s]
+06/11/23 10:26:46| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00906) [took 88.7593s]
+06/11/23 10:27:29| INFO mul_pacc_gs finished [took 132.4595s]
+06/11/23 10:31:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00900) [took 379.8213s]
+06/11/23 10:34:52| INFO bin_pacc_gs finished [took 576.1136s]
+----------------------------------------------------------------------------------------------------
+06/11/23 10:55:40| INFO dataset rcv1_CCAT_1prevs
+06/11/23 10:55:44| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs started
+06/11/23 10:56:36| INFO ref finished [took 44.5230s]
+06/11/23 10:56:40| INFO atc_mc finished [took 47.6566s]
+06/11/23 10:57:20| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00927) [took 90.0830s]
+06/11/23 10:58:04| INFO mul_pacc_gs finished [took 134.5283s]
+06/11/23 11:02:12| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00974) [took 383.6784s]
+06/11/23 11:05:24| INFO bin_pacc_gs finished [took 574.8730s]
+06/11/23 11:10:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00775) [took 897.6622s]
+06/11/23 11:11:27| INFO mul_sld_gs finished [took 940.1205s]
+06/11/23 11:18:11| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00835) [took 1344.8544s]
+06/11/23 11:21:09| INFO bin_sld_gs finished [took 1523.4358s]
+06/11/23 11:21:09| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs finished [took 1525.2268s]
+----------------------------------------------------------------------------------------------------
+06/11/23 11:21:26| INFO dataset rcv1_CCAT_1prevs
+06/11/23 11:21:30| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs started
+06/11/23 11:22:18| INFO ref finished [took 42.1948s]
+06/11/23 11:22:23| INFO atc_mc finished [took 45.7857s]
+06/11/23 11:23:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00987) [took 87.4022s]
+06/11/23 11:23:45| INFO mul_pacc_gs finished [took 130.6127s]
+06/11/23 11:27:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00925) [took 374.1460s]
+06/11/23 11:29:46| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00775) [took 493.2309s]
+06/11/23 11:30:30| INFO mul_sld_gs finished [took 537.7362s]
+06/11/23 11:30:56| INFO bin_pacc_gs finished [took 562.8681s]
+06/11/23 11:35:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00835) [took 840.9875s]
+06/11/23 11:38:31| INFO bin_sld_gs finished [took 1019.8362s]
+06/11/23 11:38:31| INFO Dataset sample 0.50 of dataset rcv1_CCAT_1prevs finished [took 1021.3535s]
+----------------------------------------------------------------------------------------------------
+06/11/23 11:53:50| INFO dataset rcv1_CCAT_9prevs
+06/11/23 11:53:56| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+06/11/23 11:56:45| INFO doc_feat finished [took 83.7957s]
+06/11/23 11:56:58| INFO mulne_pacc finished [took 146.6577s]
+06/11/23 11:57:03| INFO ref finished [took 120.2665s]
+06/11/23 11:57:05| INFO mul_pacc finished [took 169.5909s]
+06/11/23 11:57:07| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+06/11/23 11:57:08| INFO kfcv finished [took 130.0948s]
+06/11/23 11:57:13| INFO mulmc_pacc finished [took 173.0431s]
+06/11/23 11:57:16| INFO atc_mc finished [took 125.2363s]
+06/11/23 11:57:17| INFO mul_sld finished [took 199.1179s]
+06/11/23 11:57:18| INFO mul_cc finished [took 148.2203s]
+06/11/23 11:57:20| INFO atc_ne finished [took 121.9570s]
+06/11/23 11:57:39| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00899) [took 176.8809s]
+06/11/23 11:58:48| INFO mul_pacc_gs finished [took 245.7641s]
+06/11/23 12:00:56| INFO bin_pacc finished [took 409.8967s]
+06/11/23 12:01:03| INFO bin_sld finished [took 426.0031s]
+06/11/23 12:01:09| INFO binmc_pacc finished [took 412.9057s]
+06/11/23 12:01:13| INFO bin_cc finished [took 389.4719s]
+06/11/23 12:01:14| INFO binne_pacc finished [took 411.1276s]
+06/11/23 12:02:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 12:03:18| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00719) [took 523.4665s]
+06/11/23 12:04:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 643.3372s]
+06/11/23 12:05:27| INFO mul_sld_gs finished [took 686.5912s]
+06/11/23 12:06:25| INFO bin_pacc_gs finished [took 710.5248s]
+06/11/23 12:08:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 892.3454s]
+06/11/23 12:11:50| INFO bin_sld_gs finished [took 1070.2847s]
+06/11/23 12:11:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 1073.7689s]
+06/11/23 12:11:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+06/11/23 12:14:15| INFO doc_feat finished [took 80.2198s]
+06/11/23 12:14:27| INFO ref finished [took 106.1446s]
+06/11/23 12:14:36| INFO mul_pacc finished [took 155.8715s]
+06/11/23 12:14:37| INFO mul_sld finished [took 162.7857s]
+06/11/23 12:14:47| INFO kfcv finished [took 132.1178s]
+06/11/23 12:14:55| INFO atc_mc finished [took 127.9109s]
+06/11/23 12:14:57| INFO atc_ne finished [took 121.6128s]
+06/11/23 12:14:58| INFO mulmc_pacc finished [took 173.9023s]
+06/11/23 12:14:58| INFO mulne_pacc finished [took 167.2920s]
+06/11/23 12:14:59| INFO mul_cc finished [took 147.7428s]
+06/11/23 12:15:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00931) [took 186.6087s]
+06/11/23 12:16:44| INFO mul_pacc_gs finished [took 261.9352s]
+06/11/23 12:18:49| INFO binmc_pacc finished [took 407.0394s]
+06/11/23 12:18:50| INFO bin_pacc finished [took 410.4620s]
+06/11/23 12:18:55| INFO bin_sld finished [took 422.8949s]
+06/11/23 12:19:01| INFO binne_pacc finished [took 410.3575s]
+06/11/23 12:19:03| INFO bin_cc finished [took 396.9482s]
+06/11/23 12:20:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 12:20:41| INFO bin_sld_gsq finished [took 524.4318s]
+06/11/23 12:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00784) [took 546.2730s]
+06/11/23 12:22:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 640.2364s]
+06/11/23 12:23:20| INFO mul_sld_gs finished [took 683.6191s]
+06/11/23 12:24:29| INFO bin_pacc_gs finished [took 732.6258s]
+06/11/23 12:27:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 948.8111s]
+06/11/23 12:30:43| INFO bin_sld_gs finished [took 1128.0644s]
+06/11/23 12:30:43| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 1132.7995s]
+06/11/23 12:30:43| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+06/11/23 12:33:12| INFO mul_sld finished [took 146.3214s]
+06/11/23 12:33:24| INFO mul_cc finished [took 118.2992s]
+06/11/23 12:33:26| INFO doc_feat finished [took 96.3414s]
+06/11/23 12:33:36| INFO atc_ne finished [took 108.2657s]
+06/11/23 12:33:37| INFO mulne_pacc finished [took 155.4759s]
+06/11/23 12:33:39| INFO atc_mc finished [took 119.0950s]
+06/11/23 12:33:39| INFO mul_pacc finished [took 166.1039s]
+06/11/23 12:33:40| INFO ref finished [took 122.3921s]
+06/11/23 12:33:40| INFO mulmc_pacc finished [took 164.5722s]
+06/11/23 12:33:43| INFO kfcv finished [took 131.6124s]
+06/11/23 12:34:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00857) [took 188.0301s]
+06/11/23 12:35:45| INFO mul_pacc_gs finished [took 269.4655s]
+06/11/23 12:37:47| INFO binne_pacc finished [took 409.7038s]
+06/11/23 12:37:47| INFO bin_sld finished [took 421.4590s]
+06/11/23 12:37:55| INFO bin_pacc finished [took 423.8805s]
+06/11/23 12:37:57| INFO binmc_pacc finished [took 422.8180s]
+06/11/23 12:38:01| INFO bin_cc finished [took 400.2199s]
+06/11/23 12:39:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 12:39:41| INFO bin_sld_gsq finished [took 531.7360s]
+06/11/23 12:40:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.6726s]
+06/11/23 12:41:35| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 646.0507s]
+06/11/23 12:42:19| INFO mul_sld_gs finished [took 690.7431s]
+06/11/23 12:43:25| INFO bin_pacc_gs finished [took 737.2287s]
+06/11/23 12:47:07| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 979.3211s]
+06/11/23 12:50:07| INFO bin_sld_gs finished [took 1159.4207s]
+06/11/23 12:50:07| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1163.9370s]
+06/11/23 12:50:07| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+06/11/23 12:52:34| INFO doc_feat finished [took 79.3857s]
+06/11/23 12:52:39| INFO mul_pacc finished [took 143.2358s]
+06/11/23 12:52:49| INFO mul_sld finished [took 159.6160s]
+06/11/23 12:52:58| INFO kfcv finished [took 121.1756s]
+06/11/23 12:53:07| INFO mulmc_pacc finished [took 167.6154s]
+06/11/23 12:53:09| INFO atc_ne finished [took 115.9704s]
+06/11/23 12:53:11| INFO ref finished [took 127.9906s]
+06/11/23 12:53:17| INFO atc_mc finished [took 129.9605s]
+06/11/23 12:53:19| INFO mulne_pacc finished [took 166.1444s]
+06/11/23 12:53:21| INFO mul_cc finished [took 152.0451s]
+06/11/23 12:53:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.1015s]
+06/11/23 12:55:03| INFO mul_pacc_gs finished [took 261.6088s]
+06/11/23 12:57:20| INFO binmc_pacc finished [took 422.6680s]
+06/11/23 12:57:23| INFO bin_sld finished [took 434.1109s]
+06/11/23 12:57:26| INFO bin_pacc finished [took 431.1893s]
+06/11/23 12:57:28| INFO binne_pacc finished [took 427.7980s]
+06/11/23 12:57:29| INFO bin_cc finished [took 402.6463s]
+06/11/23 12:58:43| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 12:59:20| INFO bin_sld_gsq finished [took 546.8013s]
+06/11/23 12:59:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00858) [took 550.8127s]
+06/11/23 13:01:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 652.8483s]
+06/11/23 13:01:47| INFO mul_sld_gs finished [took 695.7927s]
+06/11/23 13:02:56| INFO bin_pacc_gs finished [took 739.4380s]
+06/11/23 13:06:49| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 999.0699s]
+06/11/23 13:09:50| INFO bin_sld_gs finished [took 1179.8181s]
+06/11/23 13:09:50| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1183.4124s]
+06/11/23 13:09:50| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+06/11/23 13:12:34| INFO doc_feat finished [took 88.8963s]
+06/11/23 13:12:43| INFO mul_sld finished [took 169.3932s]
+06/11/23 13:12:47| INFO mul_pacc finished [took 166.5633s]
+06/11/23 13:12:50| INFO kfcv finished [took 134.2527s]
+06/11/23 13:12:58| INFO ref finished [took 128.7367s]
+06/11/23 13:12:59| INFO mulne_pacc finished [took 161.0902s]
+06/11/23 13:13:00| INFO mulmc_pacc finished [took 176.8006s]
+06/11/23 13:13:01| INFO atc_mc finished [took 129.5173s]
+06/11/23 13:13:06| INFO atc_ne finished [took 122.8886s]
+06/11/23 13:13:16| INFO mul_cc finished [took 152.5218s]
+06/11/23 13:13:34| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00774) [took 183.0928s]
+06/11/23 13:14:57| INFO mul_pacc_gs finished [took 266.4369s]
+06/11/23 13:17:06| INFO bin_pacc finished [took 427.3693s]
+06/11/23 13:17:08| INFO binmc_pacc finished [took 426.6359s]
+06/11/23 13:17:14| INFO bin_sld finished [took 441.7834s]
+06/11/23 13:17:20| INFO binne_pacc finished [took 435.6569s]
+06/11/23 13:17:22| INFO bin_cc finished [took 412.7263s]
+06/11/23 13:18:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 13:19:06| INFO bin_sld_gsq finished [took 549.0379s]
+06/11/23 13:19:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00709) [took 545.0306s]
+06/11/23 13:20:41| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 645.5669s]
+06/11/23 13:21:25| INFO mul_sld_gs finished [took 689.4814s]
+06/11/23 13:22:32| INFO bin_pacc_gs finished [took 730.0602s]
+06/11/23 13:26:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 985.8522s]
+06/11/23 13:29:21| INFO bin_sld_gs finished [took 1166.4200s]
+06/11/23 13:29:21| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 1170.8744s]
+06/11/23 13:29:21| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+06/11/23 13:31:52| INFO doc_feat finished [took 80.3058s]
+06/11/23 13:32:00| INFO mul_sld finished [took 153.1261s]
+06/11/23 13:32:00| INFO mul_pacc finished [took 148.0156s]
+06/11/23 13:32:13| INFO kfcv finished [took 122.2270s]
+06/11/23 13:32:13| INFO mulne_pacc finished [took 145.0130s]
+06/11/23 13:32:22| INFO ref finished [took 122.3525s]
+06/11/23 13:32:23| INFO atc_mc finished [took 120.2587s]
+06/11/23 13:32:23| INFO atc_ne finished [took 113.5667s]
+06/11/23 13:32:23| INFO mulmc_pacc finished [took 167.7106s]
+06/11/23 13:32:36| INFO mul_cc finished [took 143.6517s]
+06/11/23 13:33:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00802) [took 182.2049s]
+06/11/23 13:34:23| INFO mul_pacc_gs finished [took 261.0038s]
+06/11/23 13:36:19| INFO binmc_pacc finished [took 405.9199s]
+06/11/23 13:36:31| INFO bin_sld finished [took 426.3780s]
+06/11/23 13:36:32| INFO bin_pacc finished [took 420.2833s]
+06/11/23 13:36:34| INFO binne_pacc finished [took 417.2048s]
+06/11/23 13:36:42| INFO bin_cc finished [took 394.3524s]
+06/11/23 13:37:45| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 13:38:18| INFO bin_sld_gsq finished [took 528.6956s]
+06/11/23 13:38:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00707) [took 544.2769s]
+06/11/23 13:39:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 628.0656s]
+06/11/23 13:40:41| INFO mul_sld_gs finished [took 673.3968s]
+06/11/23 13:41:58| INFO bin_pacc_gs finished [took 730.5371s]
+06/11/23 13:45:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 960.1061s]
+06/11/23 13:48:28| INFO bin_sld_gs finished [took 1140.6073s]
+06/11/23 13:48:28| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1146.6395s]
+06/11/23 13:48:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+06/11/23 13:50:49| INFO mul_pacc finished [took 130.9408s]
+06/11/23 13:51:02| INFO doc_feat finished [took 86.2411s]
+06/11/23 13:51:07| INFO mul_sld finished [took 155.4513s]
+06/11/23 13:51:15| INFO atc_ne finished [took 101.0761s]
+06/11/23 13:51:20| INFO ref finished [took 121.3689s]
+06/11/23 13:51:20| INFO atc_mc finished [took 106.6415s]
+06/11/23 13:51:22| INFO mulmc_pacc finished [took 160.4221s]
+06/11/23 13:51:22| INFO mulne_pacc finished [took 150.1203s]
+06/11/23 13:51:25| INFO kfcv finished [took 127.5280s]
+06/11/23 13:51:35| INFO mul_cc finished [took 145.4437s]
+06/11/23 13:52:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00886) [took 182.0543s]
+06/11/23 13:53:23| INFO mul_pacc_gs finished [took 262.2496s]
+06/11/23 13:55:28| INFO bin_sld finished [took 417.7315s]
+06/11/23 13:55:30| INFO binmc_pacc finished [took 410.0114s]
+06/11/23 13:55:30| INFO bin_pacc finished [took 413.5912s]
+06/11/23 13:55:35| INFO binne_pacc finished [took 411.8241s]
+06/11/23 13:55:42| INFO bin_cc finished [took 396.5011s]
+06/11/23 13:56:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 13:57:22| INFO bin_sld_gsq finished [took 527.2507s]
+06/11/23 13:58:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00910) [took 547.7641s]
+06/11/23 13:59:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 634.8469s]
+06/11/23 13:59:54| INFO mul_sld_gs finished [took 680.2027s]
+06/11/23 14:01:07| INFO bin_pacc_gs finished [took 731.8655s]
+06/11/23 14:04:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 960.6861s]
+06/11/23 14:07:34| INFO bin_sld_gs finished [took 1141.7199s]
+06/11/23 14:07:34| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 1146.2680s]
+06/11/23 14:07:34| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+06/11/23 14:10:08| INFO mulmc_pacc finished [took 141.2266s]
+06/11/23 14:10:19| INFO atc_ne finished [took 101.4512s]
+06/11/23 14:10:20| INFO mul_sld finished [took 162.5808s]
+06/11/23 14:10:23| INFO mul_pacc finished [took 158.9068s]
+06/11/23 14:10:30| INFO kfcv finished [took 123.4790s]
+06/11/23 14:10:33| INFO mulne_pacc finished [took 158.4983s]
+06/11/23 14:10:33| INFO doc_feat finished [took 111.7987s]
+06/11/23 14:10:35| INFO ref finished [took 124.4184s]
+06/11/23 14:10:40| INFO atc_mc finished [took 126.3543s]
+06/11/23 14:10:40| INFO mul_cc finished [took 139.5958s]
+06/11/23 14:11:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.01309) [took 184.0645s]
+06/11/23 14:12:44| INFO mul_pacc_gs finished [took 272.5404s]
+06/11/23 14:14:32| INFO binmc_pacc finished [took 406.3609s]
+06/11/23 14:14:38| INFO bin_pacc finished [took 414.8972s]
+06/11/23 14:14:43| INFO binne_pacc finished [took 414.4123s]
+06/11/23 14:14:51| INFO bin_cc finished [took 395.5254s]
+06/11/23 14:14:55| INFO bin_sld finished [took 437.7681s]
+06/11/23 14:15:58| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 14:16:33| INFO bin_sld_gsq finished [took 532.4040s]
+06/11/23 14:16:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00812) [took 536.4746s]
+06/11/23 14:18:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 636.4067s]
+06/11/23 14:19:00| INFO mul_sld_gs finished [took 680.2467s]
+06/11/23 14:20:01| INFO bin_pacc_gs finished [took 720.9205s]
+06/11/23 14:23:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 954.4487s]
+06/11/23 14:26:41| INFO bin_sld_gs finished [took 1142.3328s]
+06/11/23 14:26:41| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 1146.7713s]
+06/11/23 14:26:41| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+06/11/23 14:29:04| INFO mul_pacc finished [took 133.1736s]
+06/11/23 14:29:07| INFO ref finished [took 87.1594s]
+06/11/23 14:29:16| INFO doc_feat finished [took 83.8190s]
+06/11/23 14:29:21| INFO mulmc_pacc finished [took 147.5202s]
+06/11/23 14:29:22| INFO atc_mc finished [took 99.1039s]
+06/11/23 14:29:23| INFO kfcv finished [took 109.5348s]
+06/11/23 14:29:27| INFO mulne_pacc finished [took 148.1672s]
+06/11/23 14:29:33| INFO atc_ne finished [took 101.4673s]
+06/11/23 14:29:36| INFO mul_cc finished [took 126.0447s]
+06/11/23 14:29:42| INFO mul_sld finished [took 177.5880s]
+06/11/23 14:30:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01497) [took 175.1432s]
+06/11/23 14:31:33| INFO mul_pacc_gs finished [took 252.3399s]
+06/11/23 14:33:34| INFO binmc_pacc finished [took 401.7891s]
+06/11/23 14:33:35| INFO binne_pacc finished [took 400.4138s]
+06/11/23 14:33:36| INFO bin_pacc finished [took 406.7598s]
+06/11/23 14:33:48| INFO bin_cc finished [took 378.7595s]
+06/11/23 14:33:48| INFO bin_sld finished [took 423.7366s]
+06/11/23 14:34:47| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 14:35:26| INFO bin_sld_gsq finished [took 518.8996s]
+06/11/23 14:36:13| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00880) [took 539.3992s]
+06/11/23 14:37:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 622.0419s]
+06/11/23 14:37:53| INFO mul_sld_gs finished [took 666.0058s]
+06/11/23 14:39:16| INFO bin_pacc_gs finished [took 722.5231s]
+06/11/23 14:42:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 929.3464s]
+06/11/23 14:45:14| INFO bin_sld_gs finished [took 1108.7356s]
+06/11/23 14:45:14| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 1113.2364s]
+06/11/23 14:48:04| INFO dataset imdb_9prevs
+06/11/23 14:48:14| INFO Dataset sample 0.10 of dataset imdb_9prevs started
+06/11/23 14:48:17| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 14:48:18| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 14:48:31| INFO doc_feat finished [took 11.5257s]
+06/11/23 14:48:36| INFO ref finished [took 18.5620s]
+06/11/23 14:48:42| INFO kfcv finished [took 24.7227s]
+06/11/23 14:48:44| INFO atc_ne finished [took 25.5676s]
+06/11/23 14:48:46| INFO atc_mc finished [took 27.4910s]
+06/11/23 14:48:50| INFO mulne_pacc finished [took 34.0415s]
+06/11/23 14:48:57| INFO mulmc_pacc finished [took 41.7500s]
+06/11/23 14:48:58| INFO mul_pacc finished [took 43.0162s]
+06/11/23 14:48:58| INFO mul_cc finished [took 40.3279s]
+06/11/23 14:49:16| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+06/11/23 14:49:26| INFO mul_sld finished [took 71.4588s]
+06/11/23 14:50:10| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+06/11/23 14:52:12| INFO binne_pacc finished [took 236.2174s]
+06/11/23 14:52:16| INFO binmc_pacc finished [took 240.4686s]
+06/11/23 14:52:19| INFO bin_cc finished [took 241.9141s]
+06/11/23 14:52:20| INFO bin_pacc finished [took 244.5632s]
+06/11/23 14:52:23| INFO bin_sld finished [took 249.0477s]
+06/11/23 14:53:48| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 14:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 443.6010s]
+06/11/23 14:55:51| INFO mul_sld_gs finished [took 455.9932s]
+06/11/23 14:55:51| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 456.7746s]
+06/11/23 14:55:51| INFO Dataset sample 0.20 of dataset imdb_9prevs started
+06/11/23 14:56:07| INFO doc_feat finished [took 11.2758s]
+06/11/23 14:56:18| INFO atc_mc finished [took 22.2986s]
+06/11/23 14:56:22| INFO ref finished [took 26.3482s]
+06/11/23 14:56:25| INFO kfcv finished [took 30.4761s]
+06/11/23 14:56:29| INFO mul_pacc finished [took 36.5892s]
+06/11/23 14:56:29| INFO mulmc_pacc finished [took 36.7773s]
+06/11/23 14:56:38| INFO atc_ne finished [took 41.7824s]
+06/11/23 14:56:41| INFO mulne_pacc finished [took 47.8318s]
+06/11/23 14:56:41| INFO mul_cc finished [took 46.7221s]
+06/11/23 14:56:55| INFO mul_sld finished [took 63.3547s]
+06/11/23 14:57:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.01017) [took 119.9166s]
+06/11/23 14:58:15| INFO mul_pacc_gs finished [took 141.4446s]
+06/11/23 15:00:38| INFO binne_pacc finished [took 285.5562s]
+06/11/23 15:00:48| INFO bin_cc finished [took 293.8727s]
+06/11/23 15:00:49| INFO binmc_pacc finished [took 296.7176s]
+06/11/23 15:00:49| INFO bin_pacc finished [took 297.1868s]
+06/11/23 15:01:03| INFO bin_sld finished [took 312.0358s]
+06/11/23 15:02:29| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 15:02:34| INFO bin_sld_gsq finished [took 402.0748s]
+06/11/23 15:03:56| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00980) [took 482.9237s]
+06/11/23 15:05:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 548.0443s]
+06/11/23 15:05:14| INFO mul_sld_gs finished [took 562.2966s]
+06/11/23 15:06:30| INFO bin_pacc_gs finished [took 636.7956s]
+06/11/23 15:10:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 884.9748s]
+06/11/23 15:13:11| INFO bin_sld_gs finished [took 1039.3282s]
+06/11/23 15:13:11| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 1040.0772s]
+06/11/23 15:13:11| INFO Dataset sample 0.30 of dataset imdb_9prevs started
+06/11/23 15:13:39| INFO doc_feat finished [took 22.8145s]
+06/11/23 15:13:41| INFO atc_ne finished [took 24.3471s]
+06/11/23 15:13:45| INFO ref finished [took 28.7559s]
+06/11/23 15:13:52| INFO mulne_pacc finished [took 38.1365s]
+06/11/23 15:13:53| INFO kfcv finished [took 37.4026s]
+06/11/23 15:13:56| INFO atc_mc finished [took 39.4198s]
+06/11/23 15:13:59| INFO mul_pacc finished [took 45.9542s]
+06/11/23 15:13:59| INFO mul_cc finished [took 43.9076s]
+06/11/23 15:13:59| INFO mulmc_pacc finished [took 45.9395s]
+06/11/23 15:14:11| INFO mul_sld finished [took 59.8835s]
+06/11/23 15:15:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01028) [took 128.2866s]
+06/11/23 15:15:44| INFO mul_pacc_gs finished [took 149.5820s]
+06/11/23 15:18:03| INFO binne_pacc finished [took 289.3504s]
+06/11/23 15:18:07| INFO bin_pacc finished [took 294.7115s]
+06/11/23 15:18:14| INFO bin_cc finished [took 298.6839s]
+06/11/23 15:18:14| INFO binmc_pacc finished [took 300.9499s]
+06/11/23 15:18:14| INFO bin_sld finished [took 302.9035s]
+06/11/23 15:19:46| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 15:20:05| INFO bin_sld_gsq finished [took 413.1151s]
+06/11/23 15:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00916) [took 488.7327s]
+06/11/23 15:22:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 541.2865s]
+06/11/23 15:22:28| INFO mul_sld_gs finished [took 556.0867s]
+06/11/23 15:23:57| INFO bin_pacc_gs finished [took 643.0717s]
+06/11/23 15:27:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 860.3135s]
+06/11/23 15:30:05| INFO bin_sld_gs finished [took 1013.1878s]
+06/11/23 15:30:05| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 1014.3141s]
+06/11/23 15:30:05| INFO Dataset sample 0.40 of dataset imdb_9prevs started
+06/11/23 15:30:24| INFO doc_feat finished [took 13.8500s]
+06/11/23 15:30:32| INFO ref finished [took 22.3531s]
+06/11/23 15:30:41| INFO mul_pacc finished [took 34.1860s]
+06/11/23 15:30:45| INFO atc_ne finished [took 34.8111s]
+06/11/23 15:30:46| INFO kfcv finished [took 36.4055s]
+06/11/23 15:30:49| INFO atc_mc finished [took 38.7978s]
+06/11/23 15:30:49| INFO mulmc_pacc finished [took 42.4552s]
+06/11/23 15:30:51| INFO mul_cc finished [took 42.6899s]
+06/11/23 15:30:53| INFO mulne_pacc finished [took 45.2694s]
+06/11/23 15:30:57| INFO mul_sld finished [took 51.2705s]
+06/11/23 15:32:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01220) [took 124.5801s]
+06/11/23 15:32:34| INFO mul_pacc_gs finished [took 145.3368s]
+06/11/23 15:34:56| INFO binmc_pacc finished [took 289.1451s]
+06/11/23 15:35:04| INFO bin_sld finished [took 298.3514s]
+06/11/23 15:35:04| INFO binne_pacc finished [took 296.5538s]
+06/11/23 15:35:05| INFO bin_pacc finished [took 298.5077s]
+06/11/23 15:35:09| INFO bin_cc finished [took 300.1332s]
+06/11/23 15:36:41| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 15:37:08| INFO bin_sld_gsq finished [took 421.3938s]
+06/11/23 15:38:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01137) [took 490.9644s]
+06/11/23 15:38:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 531.8225s]
+06/11/23 15:39:12| INFO mul_sld_gs finished [took 546.4524s]
+06/11/23 15:40:53| INFO bin_pacc_gs finished [took 645.0957s]
+06/11/23 15:44:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 882.0550s]
+06/11/23 15:47:19| INFO bin_sld_gs finished [took 1033.2802s]
+06/11/23 15:47:19| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 1034.1241s]
+06/11/23 15:47:19| INFO Dataset sample 0.50 of dataset imdb_9prevs started
+06/11/23 15:47:36| INFO doc_feat finished [took 11.6005s]
+06/11/23 15:47:40| INFO ref finished [took 16.3058s]
+06/11/23 15:47:50| INFO atc_mc finished [took 25.8745s]
+06/11/23 15:47:52| INFO kfcv finished [took 29.0931s]
+06/11/23 15:47:53| INFO atc_ne finished [took 28.8903s]
+06/11/23 15:47:53| INFO mul_pacc finished [took 32.5473s]
+06/11/23 15:48:00| INFO mul_cc finished [took 37.3478s]
+06/11/23 15:48:01| INFO mulne_pacc finished [took 39.9745s]
+06/11/23 15:48:02| INFO mulmc_pacc finished [took 40.5057s]
+06/11/23 15:48:10| INFO mul_sld finished [took 50.1825s]
+06/11/23 15:49:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01107) [took 125.0329s]
+06/11/23 15:49:49| INFO mul_pacc_gs finished [took 146.7316s]
+06/11/23 15:52:15| INFO bin_cc finished [took 292.6719s]
+06/11/23 15:52:15| INFO binne_pacc finished [took 293.9844s]
+06/11/23 15:52:17| INFO bin_pacc finished [took 296.2830s]
+06/11/23 15:52:21| INFO binmc_pacc finished [took 299.4873s]
+06/11/23 15:52:23| INFO bin_sld finished [took 303.4889s]
+06/11/23 15:53:57| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 15:54:18| INFO bin_sld_gsq finished [took 418.0959s]
+06/11/23 15:55:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 489.7797s]
+06/11/23 15:56:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 536.7408s]
+06/11/23 15:56:33| INFO mul_sld_gs finished [took 552.5393s]
+06/11/23 15:58:05| INFO bin_pacc_gs finished [took 643.1581s]
+06/11/23 16:01:42| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 862.6012s]
+06/11/23 16:04:15| INFO bin_sld_gs finished [took 1015.3606s]
+06/11/23 16:04:15| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 1016.0642s]
+06/11/23 16:04:15| INFO Dataset sample 0.60 of dataset imdb_9prevs started
+06/11/23 16:04:40| INFO doc_feat finished [took 19.9628s]
+06/11/23 16:04:41| INFO kfcv finished [took 21.8848s]
+06/11/23 16:04:46| INFO ref finished [took 26.2613s]
+06/11/23 16:04:56| INFO mulmc_pacc finished [took 38.6399s]
+06/11/23 16:04:56| INFO atc_ne finished [took 35.7501s]
+06/11/23 16:04:57| INFO atc_mc finished [took 37.3907s]
+06/11/23 16:05:01| INFO mul_cc finished [took 41.6420s]
+06/11/23 16:05:01| INFO mul_pacc finished [took 44.6898s]
+06/11/23 16:05:02| INFO mulne_pacc finished [took 44.7679s]
+06/11/23 16:05:12| INFO mul_sld finished [took 56.0834s]
+06/11/23 16:06:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01082) [took 125.2569s]
+06/11/23 16:06:44| INFO mul_pacc_gs finished [took 146.2318s]
+06/11/23 16:09:05| INFO binne_pacc finished [took 288.1949s]
+06/11/23 16:09:10| INFO bin_pacc finished [took 293.3207s]
+06/11/23 16:09:12| INFO bin_sld finished [took 296.1022s]
+06/11/23 16:09:13| INFO binmc_pacc finished [took 296.4000s]
+06/11/23 16:09:18| INFO bin_cc finished [took 299.1982s]
+06/11/23 16:10:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 16:11:22| INFO bin_sld_gsq finished [took 425.6641s]
+06/11/23 16:12:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00976) [took 492.8847s]
+06/11/23 16:13:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 536.8669s]
+06/11/23 16:13:28| INFO mul_sld_gs finished [took 551.6187s]
+06/11/23 16:15:03| INFO bin_pacc_gs finished [took 645.6602s]
+06/11/23 16:19:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 907.7074s]
+06/11/23 16:21:57| INFO bin_sld_gs finished [took 1060.9759s]
+06/11/23 16:21:57| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 1061.7730s]
+06/11/23 16:21:57| INFO Dataset sample 0.70 of dataset imdb_9prevs started
+06/11/23 16:22:23| INFO doc_feat finished [took 20.2428s]
+06/11/23 16:22:34| INFO kfcv finished [took 32.1532s]
+06/11/23 16:22:36| INFO ref finished [took 34.3738s]
+06/11/23 16:22:38| INFO mul_sld finished [took 40.1101s]
+06/11/23 16:22:40| INFO mul_cc finished [took 38.6722s]
+06/11/23 16:22:41| INFO atc_mc finished [took 38.9379s]
+06/11/23 16:22:43| INFO atc_ne finished [took 40.3132s]
+06/11/23 16:22:43| INFO mulne_pacc finished [took 43.7833s]
+06/11/23 16:22:44| INFO mulmc_pacc finished [took 44.4084s]
+06/11/23 16:22:46| INFO mul_pacc finished [took 47.7998s]
+06/11/23 16:24:08| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01575) [took 127.2393s]
+06/11/23 16:24:31| INFO mul_pacc_gs finished [took 150.2100s]
+06/11/23 16:26:49| INFO bin_cc finished [took 288.6128s]
+06/11/23 16:26:51| INFO bin_pacc finished [took 292.1757s]
+06/11/23 16:26:52| INFO binne_pacc finished [took 293.0194s]
+06/11/23 16:27:01| INFO binmc_pacc finished [took 302.5703s]
+06/11/23 16:27:01| INFO bin_sld finished [took 303.9303s]
+06/11/23 16:28:32| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 16:28:53| INFO bin_sld_gsq finished [took 414.4520s]
+06/11/23 16:30:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01641) [took 494.7681s]
+06/11/23 16:31:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 542.3282s]
+06/11/23 16:31:15| INFO mul_sld_gs finished [took 557.2859s]
+06/11/23 16:32:49| INFO bin_pacc_gs finished [took 648.9428s]
+06/11/23 16:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 864.7237s]
+06/11/23 16:38:54| INFO bin_sld_gs finished [took 1015.9618s]
+06/11/23 16:38:54| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 1016.7743s]
+06/11/23 16:38:54| INFO Dataset sample 0.80 of dataset imdb_9prevs started
+06/11/23 16:39:19| INFO doc_feat finished [took 19.9639s]
+06/11/23 16:39:22| INFO atc_mc finished [took 22.9650s]
+06/11/23 16:39:26| INFO kfcv finished [took 27.9671s]
+06/11/23 16:39:30| INFO mul_pacc finished [took 34.3899s]
+06/11/23 16:39:31| INFO ref finished [took 32.4692s]
+06/11/23 16:39:33| INFO mulne_pacc finished [took 37.2045s]
+06/11/23 16:39:39| INFO atc_ne finished [took 39.7686s]
+06/11/23 16:39:41| INFO mul_cc finished [took 42.9411s]
+06/11/23 16:39:41| INFO mulmc_pacc finished [took 44.9724s]
+06/11/23 16:39:46| INFO mul_sld finished [took 51.4269s]
+06/11/23 16:40:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01013) [took 122.2196s]
+06/11/23 16:41:24| INFO mul_pacc_gs finished [took 146.7076s]
+06/11/23 16:43:40| INFO binne_pacc finished [took 284.1154s]
+06/11/23 16:43:52| INFO bin_pacc finished [took 296.8885s]
+06/11/23 16:43:54| INFO bin_cc finished [took 297.1714s]
+06/11/23 16:43:56| INFO binmc_pacc finished [took 300.6806s]
+06/11/23 16:43:57| INFO bin_sld finished [took 302.6966s]
+06/11/23 16:45:26| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
+06/11/23 16:45:41| INFO bin_sld_gsq finished [took 405.8247s]
+06/11/23 16:47:00| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00949) [took 483.3129s]
+06/11/23 16:47:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 539.6504s]
+06/11/23 16:48:09| INFO mul_sld_gs finished [took 553.8401s]
+06/11/23 16:49:34| INFO bin_pacc_gs finished [took 637.2772s]
+06/11/23 16:53:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 875.8870s]
+06/11/23 16:56:08| INFO bin_sld_gs finished [took 1033.4325s]
+06/11/23 16:56:08| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 1034.1983s]
+06/11/23 16:56:08| INFO Dataset sample 0.90 of dataset imdb_9prevs started
+06/11/23 16:56:09| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:09| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:10| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:10| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:10| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:10| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:10| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:10| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:11| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:11| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 16:56:22| INFO doc_feat finished [took 10.1613s]
+06/11/23 16:56:25| INFO ref finished [took 13.7569s]
+06/11/23 16:56:27| INFO kfcv finished [took 15.6337s]
+06/11/23 16:56:29| INFO atc_mc finished [took 18.0104s]
+06/11/23 16:56:30| INFO atc_ne finished [took 18.0260s]
+06/11/23 16:56:31| INFO mul_cc finished [took 20.6201s]
+06/11/23 16:56:40| INFO mul_sld finished [took 31.2942s]
+06/11/23 16:56:47| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 16:58:55| INFO bin_cc finished [took 164.5182s]
+06/11/23 16:58:59| INFO bin_sld finished [took 170.5046s]
+06/11/23 17:02:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 368.6067s]
+06/11/23 17:02:29| INFO mul_sld_gs finished [took 380.7801s]
+06/11/23 17:02:29| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 381.5305s]
+----------------------------------------------------------------------------------------------------
+06/11/23 18:04:06| INFO dataset rcv1_GCAT_9prevs
+06/11/23 18:04:12| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
+06/11/23 18:04:19| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:21| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:22| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:24| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:24| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:26| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:27| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:28| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:04:29| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:05:10| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+06/11/23 18:05:41| INFO ref finished [took 65.3048s]
+06/11/23 18:05:43| INFO kfcv finished [took 66.9585s]
+06/11/23 18:05:45| INFO doc_feat finished [took 56.7504s]
+06/11/23 18:05:49| INFO mul_cc finished [took 77.6035s]
+06/11/23 18:05:49| INFO atc_mc finished [took 66.4650s]
+06/11/23 18:05:52| INFO atc_ne finished [took 65.1035s]
+06/11/23 18:05:52| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+06/11/23 18:05:56| INFO mul_sld finished [took 101.3427s]
+06/11/23 18:08:12| INFO bin_sld finished [took 238.6323s]
+06/11/23 18:08:21| INFO bin_cc finished [took 230.3034s]
+06/11/23 18:10:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00897) [took 402.3046s]
+06/11/23 18:11:39| INFO mul_sld_gs finished [took 441.7473s]
+06/11/23 18:11:39| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 446.6543s]
+06/11/23 18:11:39| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
+06/11/23 18:14:11| INFO mulmc_pacc finished [took 140.5240s]
+06/11/23 18:14:13| INFO kfcv finished [took 108.3325s]
+06/11/23 18:14:16| INFO doc_feat finished [took 91.1407s]
+06/11/23 18:14:21| INFO atc_ne finished [took 96.9645s]
+06/11/23 18:14:22| INFO mul_pacc finished [took 154.9757s]
+06/11/23 18:14:36| INFO ref finished [took 118.1583s]
+06/11/23 18:14:37| INFO atc_mc finished [took 118.5016s]
+06/11/23 18:14:41| INFO mulne_pacc finished [took 157.8831s]
+06/11/23 18:14:49| INFO mul_cc finished [took 144.8053s]
+06/11/23 18:14:50| INFO mul_sld finished [took 188.8450s]
+06/11/23 18:15:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01452) [took 184.0929s]
+06/11/23 18:16:33| INFO mul_pacc_gs finished [took 258.2234s]
+06/11/23 18:18:46| INFO binmc_pacc finished [took 417.1372s]
+06/11/23 18:18:48| INFO bin_pacc finished [took 422.0619s]
+06/11/23 18:18:52| INFO bin_sld finished [took 431.4426s]
+06/11/23 18:18:56| INFO binne_pacc finished [took 421.5812s]
+06/11/23 18:19:02| INFO bin_cc finished [took 402.4673s]
+06/11/23 18:19:32| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
+06/11/23 18:20:26| INFO bin_sld_gsq finished [took 522.0734s]
+06/11/23 18:21:11| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 540.4022s]
+06/11/23 18:21:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00821) [took 600.6611s]
+06/11/23 18:22:25| INFO mul_sld_gs finished [took 642.1063s]
+06/11/23 18:24:14| INFO bin_pacc_gs finished [took 723.2605s]
+06/11/23 18:26:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00816) [took 911.5066s]
+06/11/23 18:29:56| INFO bin_sld_gs finished [took 1093.4674s]
+06/11/23 18:29:56| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 1096.7184s]
+06/11/23 18:29:56| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
+06/11/23 18:32:21| INFO ref finished [took 89.3355s]
+06/11/23 18:32:33| INFO doc_feat finished [took 91.9119s]
+06/11/23 18:32:35| INFO mulmc_pacc finished [took 147.2084s]
+06/11/23 18:32:38| INFO mulne_pacc finished [took 137.0643s]
+06/11/23 18:32:54| INFO atc_mc finished [took 117.6847s]
+06/11/23 18:32:56| INFO kfcv finished [took 129.8598s]
+06/11/23 18:33:00| INFO mul_pacc finished [took 174.5769s]
+06/11/23 18:33:00| INFO mul_sld finished [took 181.1734s]
+06/11/23 18:33:03| INFO atc_ne finished [took 123.9984s]
+06/11/23 18:33:09| INFO mul_cc finished [took 148.8635s]
+06/11/23 18:33:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00629) [took 177.7598s]
+06/11/23 18:34:51| INFO mul_pacc_gs finished [took 256.4186s]
+06/11/23 18:37:10| INFO bin_pacc finished [took 425.7912s]
+06/11/23 18:37:12| INFO binmc_pacc finished [took 425.7599s]
+06/11/23 18:37:14| INFO binne_pacc finished [took 424.0101s]
+06/11/23 18:37:18| INFO bin_sld finished [took 440.4389s]
+06/11/23 18:37:22| INFO bin_cc finished [took 407.2413s]
+06/11/23 18:37:52| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
+06/11/23 18:38:51| INFO bin_sld_gsq finished [took 529.6242s]
+06/11/23 18:39:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00489) [took 541.8062s]
+06/11/23 18:40:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00615) [took 601.7630s]
+06/11/23 18:40:45| INFO mul_sld_gs finished [took 644.5111s]
+06/11/23 18:42:37| INFO bin_pacc_gs finished [took 729.3942s]
+06/11/23 18:45:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00490) [took 936.3088s]
+06/11/23 18:48:37| INFO bin_sld_gs finished [took 1117.0610s]
+06/11/23 18:48:37| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 1120.9681s]
+06/11/23 18:48:37| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
+06/11/23 18:51:02| INFO doc_feat finished [took 79.6380s]
+06/11/23 18:51:20| INFO mulne_pacc finished [took 144.5625s]
+06/11/23 18:51:30| INFO mul_sld finished [took 171.1473s]
+06/11/23 18:51:35| INFO mulmc_pacc finished [took 166.1468s]
+06/11/23 18:51:39| INFO mul_pacc finished [took 172.9449s]
+06/11/23 18:51:43| INFO ref finished [took 132.2492s]
+06/11/23 18:51:45| INFO kfcv finished [took 137.9538s]
+06/11/23 18:51:52| INFO atc_mc finished [took 137.7185s]
+06/11/23 18:51:54| INFO atc_ne finished [took 134.1066s]
+06/11/23 18:51:59| INFO mul_cc finished [took 159.0670s]
+06/11/23 18:52:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01049) [took 180.3366s]
+06/11/23 18:53:38| INFO mul_pacc_gs finished [took 266.6075s]
+06/11/23 18:56:00| INFO bin_sld finished [took 441.9022s]
+06/11/23 18:56:02| INFO binne_pacc finished [took 431.1354s]
+06/11/23 18:56:02| INFO binmc_pacc finished [took 434.5268s]
+06/11/23 18:56:04| INFO bin_pacc finished [took 438.8400s]
+06/11/23 18:56:07| INFO bin_cc finished [took 412.8827s]
+06/11/23 18:56:38| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
+06/11/23 18:57:38| INFO bin_sld_gsq finished [took 534.9970s]
+06/11/23 18:58:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.5790s]
+06/11/23 18:58:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00692) [took 616.7506s]
+06/11/23 18:59:43| INFO mul_sld_gs finished [took 661.6976s]
+06/11/23 19:01:20| INFO bin_pacc_gs finished [took 735.1934s]
+06/11/23 19:04:29| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00601) [took 948.3129s]
+06/11/23 19:07:30| INFO bin_sld_gs finished [took 1129.1432s]
+06/11/23 19:07:30| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 1133.2853s]
+06/11/23 19:07:30| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
+06/11/23 19:10:11| INFO doc_feat finished [took 90.8028s]
+06/11/23 19:10:12| INFO mul_sld finished [took 159.3725s]
+06/11/23 19:10:17| INFO atc_mc finished [took 108.3872s]
+06/11/23 19:10:20| INFO mulmc_pacc finished [took 158.7937s]
+06/11/23 19:10:27| INFO kfcv finished [took 125.4384s]
+06/11/23 19:10:32| INFO mul_cc finished [took 134.1449s]
+06/11/23 19:10:33| INFO atc_ne finished [took 115.0137s]
+06/11/23 19:10:33| INFO mul_pacc finished [took 173.4398s]
+06/11/23 19:10:35| INFO ref finished [took 127.6900s]
+06/11/23 19:10:35| INFO mulne_pacc finished [took 158.1989s]
+06/11/23 19:11:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00893) [took 181.2645s]
+06/11/23 19:12:28| INFO mul_pacc_gs finished [took 263.1619s]
+06/11/23 19:14:45| INFO bin_sld finished [took 432.8401s]
+06/11/23 19:14:48| INFO bin_pacc finished [took 430.1210s]
+06/11/23 19:14:54| INFO binmc_pacc finished [took 433.8715s]
+06/11/23 19:14:58| INFO bin_cc finished [took 405.7688s]
+06/11/23 19:14:59| INFO binne_pacc finished [took 435.7315s]
+06/11/23 19:15:29| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
+06/11/23 19:16:36| INFO bin_sld_gsq finished [took 539.4078s]
+06/11/23 19:17:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00831) [took 545.8362s]
+06/11/23 19:17:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00797) [took 609.7895s]
+06/11/23 19:18:32| INFO mul_sld_gs finished [took 657.1765s]
+06/11/23 19:20:08| INFO bin_pacc_gs finished [took 728.9184s]
+06/11/23 19:23:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00738) [took 966.8750s]
+06/11/23 19:26:42| INFO bin_sld_gs finished [took 1148.2428s]
+06/11/23 19:26:42| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 1152.4463s]
+06/11/23 19:26:43| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
+06/11/23 19:29:16| INFO mul_pacc finished [took 142.3375s]
+06/11/23 19:29:26| INFO doc_feat finished [took 92.0123s]
+06/11/23 19:29:29| INFO atc_ne finished [took 96.1697s]
+06/11/23 19:29:32| INFO mul_sld finished [took 164.7852s]
+06/11/23 19:29:33| INFO ref finished [took 114.3664s]
+06/11/23 19:29:36| INFO kfcv finished [took 118.4300s]
+06/11/23 19:29:37| INFO atc_mc finished [took 111.6950s]
+06/11/23 19:29:37| INFO mul_cc finished [took 127.8860s]
+06/11/23 19:29:39| INFO mulmc_pacc finished [took 162.5217s]
+06/11/23 19:29:46| INFO mulne_pacc finished [took 159.7535s]
+06/11/23 19:30:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.2267s]
+06/11/23 19:31:42| INFO mul_pacc_gs finished [took 263.2959s]
+06/11/23 19:33:48| INFO bin_pacc finished [took 415.7355s]
+06/11/23 19:33:49| INFO binne_pacc finished [took 411.7032s]
+06/11/23 19:33:49| INFO bin_sld finished [took 423.6935s]
+06/11/23 19:33:56| INFO binmc_pacc finished [took 422.0731s]
+06/11/23 19:34:02| INFO bin_cc finished [took 394.8074s]
+06/11/23 19:34:45| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
+06/11/23 19:35:33| INFO bin_sld_gsq finished [took 523.6794s]
+06/11/23 19:36:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00651) [took 539.0149s]
+06/11/23 19:36:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00646) [took 605.4721s]
+06/11/23 19:37:37| INFO mul_sld_gs finished [took 647.9998s]
+06/11/23 19:39:13| INFO bin_pacc_gs finished [took 722.3065s]
+06/11/23 19:42:14| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00635) [took 926.2548s]
+06/11/23 19:45:13| INFO bin_sld_gs finished [took 1105.8303s]
+06/11/23 19:45:13| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 1110.5345s]
+06/11/23 19:45:13| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
+06/11/23 19:47:55| INFO mul_pacc finished [took 151.2717s]
+06/11/23 19:48:01| INFO mul_sld finished [took 164.7303s]
+06/11/23 19:48:02| INFO doc_feat finished [took 95.7218s]
+06/11/23 19:48:20| INFO kfcv finished [took 132.6414s]
+06/11/23 19:48:26| INFO ref finished [took 136.4855s]
+06/11/23 19:48:27| INFO mulmc_pacc finished [took 180.2510s]
+06/11/23 19:48:30| INFO mulne_pacc finished [took 173.6996s]
+06/11/23 19:48:33| INFO atc_mc finished [took 135.5939s]
+06/11/23 19:48:34| INFO atc_ne finished [took 129.3719s]
+06/11/23 19:48:35| INFO mul_cc finished [took 153.9587s]
+06/11/23 19:48:47| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00782) [took 177.0918s]
+06/11/23 19:50:13| INFO mul_pacc_gs finished [took 262.7047s]
+06/11/23 19:52:34| INFO bin_pacc finished [took 431.9695s]
+06/11/23 19:52:36| INFO binmc_pacc finished [took 430.1566s]
+06/11/23 19:52:43| INFO bin_sld finished [took 446.4452s]
+06/11/23 19:52:44| INFO bin_cc finished [took 407.8850s]
+06/11/23 19:52:47| INFO binne_pacc finished [took 438.4423s]
+06/11/23 19:53:19| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
+06/11/23 19:54:09| INFO bin_sld_gsq finished [took 528.9254s]
+06/11/23 19:54:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00669) [took 545.8164s]
+06/11/23 19:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00814) [took 619.0258s]
+06/11/23 19:56:21| INFO mul_sld_gs finished [took 661.4303s]
+06/11/23 19:57:51| INFO bin_pacc_gs finished [took 733.3970s]
+06/11/23 20:00:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00795) [took 935.9973s]
+06/11/23 20:03:55| INFO bin_sld_gs finished [took 1117.3981s]
+06/11/23 20:03:55| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 1121.8060s]
+06/11/23 20:03:55| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
+06/11/23 20:06:27| INFO mul_sld finished [took 147.0727s]
+06/11/23 20:06:30| INFO doc_feat finished [took 81.1117s]
+06/11/23 20:06:48| INFO mul_pacc finished [took 162.2312s]
+06/11/23 20:07:04| INFO kfcv finished [took 133.4389s]
+06/11/23 20:07:04| INFO ref finished [took 132.6728s]
+06/11/23 20:07:05| INFO mulne_pacc finished [took 171.0782s]
+06/11/23 20:07:08| INFO mulmc_pacc finished [took 179.6909s]
+06/11/23 20:07:10| INFO atc_mc finished [took 130.5941s]
+06/11/23 20:07:14| INFO mul_cc finished [took 150.3795s]
+06/11/23 20:07:15| INFO atc_ne finished [took 131.0309s]
+06/11/23 20:07:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00813) [took 177.7289s]
+06/11/23 20:08:49| INFO mul_pacc_gs finished [took 257.9675s]
+06/11/23 20:10:44| INFO bin_pacc finished [took 399.4800s]
+06/11/23 21:01:51| INFO bin_pacc_gs finished [took 3446.1854s]
+06/11/23 21:03:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00684) [took 3563.0699s]
+06/11/23 21:04:07| INFO mul_sld_gs finished [took 3606.0194s]
+06/11/23 21:08:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00519) [took 3863.9570s]
+06/11/23 21:11:26| INFO bin_sld_gs finished [took 4046.4500s]
+06/11/23 21:11:26| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 4051.2016s]
+06/11/23 21:11:26| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
+06/11/23 21:11:31| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:32| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:34| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:35| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
+06/11/23 21:11:36| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:38| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 21:11:38| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:40| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 21:11:40| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:42| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 21:11:42| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:11:44| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 21:11:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 21:12:27| INFO mul_sld finished [took 56.8958s]
+06/11/23 21:12:32| INFO ref finished [took 44.3311s]
+06/11/23 21:12:32| INFO doc_feat finished [took 41.1551s]
+06/11/23 21:12:33| INFO kfcv finished [took 46.1873s]
+06/11/23 21:12:36| INFO atc_mc finished [took 47.9541s]
+06/11/23 21:12:37| INFO mul_cc finished [took 51.8838s]
+06/11/23 21:12:37| INFO atc_ne finished [took 47.4962s]
+06/11/23 21:16:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00843) [took 312.8612s]
+06/11/23 21:17:24| INFO mul_sld_gs finished [took 351.5693s]
+06/11/23 21:17:24| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 357.7321s]
+06/11/23 21:20:10| INFO dataset rcv1_MCAT_9prevs
+06/11/23 21:20:18| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
+06/11/23 21:23:12| INFO doc_feat finished [took 81.2849s]
+06/11/23 21:23:21| INFO mul_pacc finished [took 168.3242s]
+06/11/23 21:23:30| INFO mulmc_pacc finished [took 173.2730s]
+06/11/23 21:23:35| INFO atc_mc finished [took 115.3803s]
+06/11/23 21:23:41| INFO ref finished [took 125.5611s]
+06/11/23 21:23:41| INFO kfcv finished [took 136.3040s]
+06/11/23 21:23:51| INFO mulne_pacc finished [took 185.3346s]
+06/11/23 21:23:58| INFO atc_ne finished [took 129.7752s]
+06/11/23 21:23:59| INFO mul_cc finished [took 164.3501s]
+06/11/23 21:24:26| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.02036) [took 203.9839s]
+06/11/23 21:24:32| INFO mul_sld finished [took 249.6979s]
+06/11/23 21:25:50| INFO mul_pacc_gs finished [took 287.7634s]
+06/11/23 21:28:08| INFO binne_pacc finished [took 443.1314s]
+06/11/23 21:28:11| INFO bin_cc finished [took 427.7416s]
+06/11/23 21:28:26| INFO bin_pacc finished [took 475.7859s]
+06/11/23 21:28:28| INFO binmc_pacc finished [took 472.2702s]
+06/11/23 21:28:33| INFO bin_sld finished [took 492.0457s]
+06/11/23 21:29:19| INFO mul_sld_gsq finished [took 529.8190s]
+06/11/23 21:29:26| INFO bin_sld_gsq finished [took 539.2552s]
+06/11/23 21:30:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00591) [took 573.3773s]
+06/11/23 21:31:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00754) [took 661.4704s]
+06/11/23 21:32:10| INFO mul_sld_gs finished [took 704.6441s]
+06/11/23 21:33:40| INFO bin_pacc_gs finished [took 763.3541s]
+06/11/23 21:36:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00760) [took 965.4559s]
+06/11/23 21:39:31| INFO bin_sld_gs finished [took 1146.5622s]
+06/11/23 21:39:31| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 1152.1700s]
+06/11/23 21:39:31| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
+06/11/23 21:42:13| INFO doc_feat finished [took 88.9970s]
+06/11/23 21:42:24| INFO mul_pacc finished [took 161.9999s]
+06/11/23 21:42:31| INFO mulmc_pacc finished [took 159.0109s]
+06/11/23 21:42:34| INFO mul_sld finished [took 179.5397s]
+06/11/23 21:42:42| INFO kfcv finished [took 138.3784s]
+06/11/23 21:42:42| INFO atc_mc finished [took 127.5150s]
+06/11/23 21:42:45| INFO ref finished [took 133.9163s]
+06/11/23 21:42:48| INFO mulne_pacc finished [took 170.3191s]
+06/11/23 21:42:53| INFO mul_cc finished [took 153.9952s]
+06/11/23 21:42:57| INFO atc_ne finished [took 133.9857s]
+06/11/23 21:43:07| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01406) [took 179.2817s]
+06/11/23 21:44:27| INFO mul_pacc_gs finished [took 259.4430s]
+06/11/23 21:46:57| INFO bin_pacc finished [took 435.9586s]
+06/11/23 21:47:02| INFO binmc_pacc finished [took 436.7170s]
+06/11/23 21:47:02| INFO bin_sld finished [took 448.6901s]
+06/11/23 21:47:03| INFO binne_pacc finished [took 430.3933s]
+06/11/23 21:47:06| INFO bin_cc finished [took 413.3717s]
+06/11/23 21:47:44| INFO mul_sld_gsq finished [took 485.8565s]
+06/11/23 21:48:40| INFO bin_sld_gsq finished [took 542.6385s]
+06/11/23 21:49:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01029) [took 558.1111s]
+06/11/23 21:49:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00862) [took 617.7204s]
+06/11/23 21:50:38| INFO mul_sld_gs finished [took 661.3619s]
+06/11/23 21:52:31| INFO bin_pacc_gs finished [took 747.8605s]
+06/11/23 21:55:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00631) [took 947.6305s]
+06/11/23 21:58:25| INFO bin_sld_gs finished [took 1128.9705s]
+06/11/23 21:58:25| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 1133.8038s]
+06/11/23 21:58:25| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
+06/11/23 22:01:11| INFO doc_feat finished [took 91.6284s]
+06/11/23 22:01:13| INFO mul_pacc finished [took 157.8979s]
+06/11/23 22:01:21| INFO ref finished [took 117.5064s]
+06/11/23 22:01:29| INFO mulmc_pacc finished [took 171.3367s]
+06/11/23 22:01:34| INFO kfcv finished [took 138.8623s]
+06/11/23 22:01:44| INFO atc_ne finished [took 127.4515s]
+06/11/23 22:01:45| INFO mulne_pacc finished [took 175.7659s]
+06/11/23 22:01:45| INFO atc_mc finished [took 134.5717s]
+06/11/23 22:01:47| INFO mul_sld finished [took 198.7132s]
+06/11/23 22:01:53| INFO mul_cc finished [took 156.7010s]
+06/11/23 22:01:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00920) [took 169.8061s]
+06/11/23 22:03:15| INFO mul_pacc_gs finished [took 248.7885s]
+06/11/23 22:05:47| INFO bin_pacc finished [took 433.9454s]
+06/11/23 22:05:52| INFO binmc_pacc finished [took 435.7566s]
+06/11/23 22:05:55| INFO binne_pacc finished [took 432.5216s]
+06/11/23 22:06:02| INFO bin_sld finished [took 455.4425s]
+06/11/23 22:06:03| INFO bin_cc finished [took 409.9712s]
+06/11/23 22:06:43| INFO mul_sld_gsq finished [took 490.7571s]
+06/11/23 22:07:34| INFO bin_sld_gsq finished [took 542.4371s]
+06/11/23 22:08:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00585) [took 557.7911s]
+06/11/23 22:08:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 598.8338s]
+06/11/23 22:09:12| INFO mul_sld_gs finished [took 641.4050s]
+06/11/23 22:11:15| INFO bin_pacc_gs finished [took 742.8423s]
+06/11/23 22:14:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00443) [took 940.7448s]
+06/11/23 22:17:12| INFO bin_sld_gs finished [took 1122.5660s]
+06/11/23 22:17:12| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 1126.9865s]
+06/11/23 22:17:12| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
+06/11/23 22:19:32| INFO ref finished [took 85.6333s]
+06/11/23 22:19:43| INFO mulmc_pacc finished [took 138.3833s]
+06/11/23 22:19:44| INFO doc_feat finished [took 84.2844s]
+06/11/23 22:19:54| INFO atc_ne finished [took 99.6744s]
+06/11/23 22:19:57| INFO kfcv finished [took 114.5018s]
+06/11/23 22:19:59| INFO mul_cc finished [took 123.4161s]
+06/11/23 22:20:05| INFO mul_pacc finished [took 163.4607s]
+06/11/23 22:20:09| INFO mul_sld finished [took 173.7721s]
+06/11/23 22:20:16| INFO mulne_pacc finished [took 162.8502s]
+06/11/23 22:20:16| INFO atc_mc finished [took 124.1504s]
+06/11/23 22:20:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00596) [took 169.9575s]
+06/11/23 22:21:55| INFO mul_pacc_gs finished [took 248.8139s]
+06/11/23 22:24:04| INFO binmc_pacc finished [took 400.7570s]
+06/11/23 22:24:12| INFO bin_pacc finished [took 411.2454s]
+06/11/23 22:24:21| INFO binne_pacc finished [took 414.5496s]
+06/11/23 22:24:21| INFO bin_cc finished [took 389.2880s]
+06/11/23 22:24:25| INFO bin_sld finished [took 431.6256s]
+06/11/23 22:25:13| INFO mul_sld_gsq finished [took 474.0621s]
+06/11/23 22:25:54| INFO bin_sld_gsq finished [took 515.9435s]
+06/11/23 22:26:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00626) [took 539.2315s]
+06/11/23 22:27:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00612) [took 594.2222s]
+06/11/23 22:27:54| INFO mul_sld_gs finished [took 637.0683s]
+06/11/23 22:29:48| INFO bin_pacc_gs finished [took 725.8952s]
+06/11/23 22:33:01| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00682) [took 945.7122s]
+06/11/23 22:36:02| INFO bin_sld_gs finished [took 1126.7133s]
+06/11/23 22:36:02| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 1130.5566s]
+06/11/23 22:36:02| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
+06/11/23 22:38:42| INFO doc_feat finished [took 76.3995s]
+06/11/23 22:39:04| INFO mul_pacc finished [took 170.8108s]
+06/11/23 22:39:11| INFO mulmc_pacc finished [took 169.1537s]
+06/11/23 22:39:22| INFO ref finished [took 134.5551s]
+06/11/23 22:39:23| INFO kfcv finished [took 144.5049s]
+06/11/23 22:39:28| INFO mul_sld finished [took 201.7112s]
+06/11/23 22:39:31| INFO atc_ne finished [took 127.5871s]
+06/11/23 22:39:32| INFO atc_mc finished [took 141.1615s]
+06/11/23 22:39:33| INFO mulne_pacc finished [took 181.7155s]
+06/11/23 22:39:34| INFO mul_cc finished [took 156.9505s]
+06/11/23 22:39:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00848) [took 178.6463s]
+06/11/23 22:41:02| INFO mul_pacc_gs finished [took 264.1109s]
+06/11/23 22:43:34| INFO binmc_pacc finished [took 438.9742s]
+06/11/23 22:43:34| INFO bin_pacc finished [took 442.7005s]
+06/11/23 22:43:43| INFO bin_sld finished [took 458.4940s]
+06/11/23 22:43:44| INFO binne_pacc finished [took 443.0455s]
+06/11/23 22:43:55| INFO bin_cc finished [took 423.6361s]
+06/11/23 22:44:45| INFO mul_sld_gsq finished [took 514.4586s]
+06/11/23 22:45:32| INFO bin_sld_gsq finished [took 562.7681s]
+06/11/23 22:46:12| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00790) [took 574.1156s]
+06/11/23 22:46:42| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00824) [took 633.5645s]
+06/11/23 22:47:24| INFO mul_sld_gs finished [took 676.3552s]
+06/11/23 22:49:27| INFO bin_pacc_gs finished [took 768.3574s]
+06/11/23 22:52:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00861) [took 979.5729s]
+06/11/23 22:55:32| INFO bin_sld_gs finished [took 1164.7331s]
+06/11/23 22:55:32| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 1169.2748s]
+06/11/23 22:55:32| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
+06/11/23 22:58:47| INFO doc_feat finished [took 112.6375s]
+06/11/23 22:59:00| INFO kfcv finished [took 150.2412s]
+06/11/23 22:59:00| INFO mul_pacc finished [took 197.0521s]
+06/11/23 22:59:06| INFO mul_sld finished [took 209.9482s]
+06/11/23 22:59:07| INFO mulmc_pacc finished [took 198.8911s]
+06/11/23 22:59:07| INFO ref finished [took 148.7702s]
+06/11/23 22:59:16| INFO atc_ne finished [took 143.7730s]
+06/11/23 22:59:18| INFO atc_mc finished [took 151.2783s]
+06/11/23 22:59:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01122) [took 190.1694s]
+06/11/23 22:59:26| INFO mul_cc finished [took 179.0100s]
+06/11/23 22:59:33| INFO mulne_pacc finished [took 211.9002s]
+06/11/23 23:00:52| INFO mul_pacc_gs finished [took 283.5718s]
+06/11/23 23:03:21| INFO bin_sld finished [took 466.9682s]
+06/11/23 23:03:24| INFO binmc_pacc finished [took 456.9500s]
+06/11/23 23:03:25| INFO bin_pacc finished [took 464.1421s]
+06/11/23 23:03:39| INFO bin_cc finished [took 445.8302s]
+06/11/23 23:03:40| INFO binne_pacc finished [took 466.3427s]
+06/11/23 23:04:10| INFO mul_sld_gsq finished [took 509.0584s]
+06/11/23 23:04:56| INFO bin_sld_gsq finished [took 556.7578s]
+06/11/23 23:05:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01033) [took 581.0899s]
+06/11/23 23:06:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00791) [took 636.6955s]
+06/11/23 23:07:00| INFO mul_sld_gs finished [took 682.1829s]
+06/11/23 23:08:59| INFO bin_pacc_gs finished [took 772.0584s]
+06/11/23 23:11:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00722) [took 966.7367s]
+06/11/23 23:14:47| INFO bin_sld_gs finished [took 1150.2138s]
+06/11/23 23:14:47| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 1155.4582s]
+06/11/23 23:14:47| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
+06/11/23 23:17:29| INFO mulmc_pacc finished [took 140.6592s]
+06/11/23 23:17:37| INFO doc_feat finished [took 93.5374s]
+06/11/23 23:17:58| INFO mul_pacc finished [took 176.1101s]
+06/11/23 23:18:06| INFO mulne_pacc finished [took 168.2578s]
+06/11/23 23:18:06| INFO ref finished [took 138.9670s]
+06/11/23 23:18:13| INFO atc_ne finished [took 133.8368s]
+06/11/23 23:18:13| INFO mul_cc finished [took 156.3809s]
+06/11/23 23:18:14| INFO atc_mc finished [took 140.7865s]
+06/11/23 23:18:15| INFO kfcv finished [took 150.8563s]
+06/11/23 23:18:28| INFO mul_sld finished [took 213.5502s]
+06/11/23 23:18:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00696) [took 184.7202s]
+06/11/23 23:20:04| INFO mul_pacc_gs finished [took 271.8620s]
+06/11/23 23:22:38| INFO binne_pacc finished [took 444.7274s]
+06/11/23 23:22:39| INFO binmc_pacc finished [took 454.8866s]
+06/11/23 23:22:39| INFO bin_pacc finished [took 458.6381s]
+06/11/23 23:22:47| INFO bin_cc finished [took 432.1075s]
+06/11/23 23:22:54| INFO bin_sld finished [took 480.5003s]
+06/11/23 23:23:33| INFO mul_sld_gsq finished [took 514.0066s]
+06/11/23 23:24:13| INFO bin_sld_gsq finished [took 554.7885s]
+06/11/23 23:24:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00603) [took 574.6463s]
+06/11/23 23:25:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00528) [took 609.3079s]
+06/11/23 23:25:51| INFO mul_sld_gs finished [took 654.2885s]
+06/11/23 23:28:10| INFO bin_pacc_gs finished [took 767.8253s]
+06/11/23 23:30:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00733) [took 947.2105s]
+06/11/23 23:33:48| INFO bin_sld_gs finished [took 1132.1309s]
+06/11/23 23:33:48| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 1140.6743s]
+06/11/23 23:33:48| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
+06/11/23 23:36:55| INFO doc_feat finished [took 101.6311s]
+06/11/23 23:37:16| INFO atc_ne finished [took 124.5854s]
+06/11/23 23:37:39| INFO mulne_pacc finished [took 198.5060s]
+06/11/23 23:37:42| INFO mulmc_pacc finished [took 210.8408s]
+06/11/23 23:37:43| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01019) [took 194.4422s]
+06/11/23 23:37:44| INFO mul_pacc finished [took 224.0155s]
+06/11/23 23:37:44| INFO kfcv finished [took 178.0222s]
+06/11/23 23:37:47| INFO ref finished [took 176.1278s]
+06/11/23 23:37:55| INFO atc_mc finished [took 173.0154s]
+06/11/23 23:37:58| INFO mul_cc finished [took 198.1420s]
+06/11/23 23:38:10| INFO mul_sld finished [took 258.4898s]
+06/11/23 23:39:25| INFO mul_pacc_gs finished [took 297.0552s]
+06/11/23 23:41:55| INFO binmc_pacc finished [took 471.8397s]
+06/11/23 23:42:06| INFO binne_pacc finished [took 470.6917s]
+06/11/23 23:42:08| INFO bin_pacc finished [took 490.2025s]
+06/11/23 23:42:11| INFO bin_sld finished [took 500.3974s]
+06/11/23 23:42:17| INFO bin_cc finished [took 463.2719s]
+06/11/23 23:42:33| INFO mul_sld_gsq finished [took 515.9211s]
+06/11/23 23:43:19| INFO bin_sld_gsq finished [took 563.2792s]
+06/11/23 23:44:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01110) [took 580.7011s]
+06/11/23 23:44:33| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00755) [took 638.9055s]
+06/11/23 23:45:18| INFO mul_sld_gs finished [took 683.7473s]
+06/11/23 23:47:14| INFO bin_pacc_gs finished [took 769.5136s]
+06/11/23 23:50:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00653) [took 986.1331s]
+06/11/23 23:53:23| INFO bin_sld_gs finished [took 1170.3407s]
+06/11/23 23:53:23| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 1175.4004s]
+06/11/23 23:53:23| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
+06/11/23 23:53:29| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:31| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:32| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:34| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
+06/11/23 23:53:34| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:36| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 23:53:37| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:38| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:39| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 23:53:41| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 23:53:41| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:53:43| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
+06/11/23 23:53:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+06/11/23 23:54:33| INFO ref finished [took 46.5615s]
+06/11/23 23:54:34| INFO doc_feat finished [took 43.4254s]
+06/11/23 23:54:34| INFO kfcv finished [took 48.7260s]
+06/11/23 23:54:34| INFO mul_sld finished [took 64.5496s]
+06/11/23 23:54:38| INFO atc_mc finished [took 49.9172s]
+06/11/23 23:54:39| INFO atc_ne finished [took 49.8635s]
+06/11/23 23:54:39| INFO mul_cc finished [took 54.7417s]
+06/11/23 23:58:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01247) [took 295.7388s]
+06/11/23 23:59:08| INFO mul_sld_gs finished [took 336.2009s]
+06/11/23 23:59:08| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 344.1389s]
+----------------------------------------------------------------------------------------------------
+07/11/23 01:05:25| INFO dataset rcv1_CCAT_9prevs
+07/11/23 01:05:30| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
+07/11/23 01:06:23| INFO ref finished [took 48.3560s]
+07/11/23 01:06:29| INFO atc_mc finished [took 52.9929s]
+07/11/23 01:06:30| INFO atc_ne finished [took 53.3908s]
+07/11/23 01:07:06| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+07/11/23 01:11:38| INFO mul_sld_gsq finished [took 364.0698s]
+07/11/23 01:13:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 499.4945s]
+07/11/23 01:14:34| INFO mul_sld_gs finished [took 542.6047s]
+07/11/23 01:18:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 750.8663s]
+07/11/23 01:21:01| INFO bin_sld_gs finished [took 930.1356s]
+07/11/23 01:21:01| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 931.4321s]
+07/11/23 01:21:01| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
+07/11/23 01:22:02| INFO ref finished [took 55.2212s]
+07/11/23 01:22:07| INFO atc_mc finished [took 59.3890s]
+07/11/23 01:22:09| INFO atc_ne finished [took 59.7388s]
+07/11/23 01:27:21| INFO mul_sld_gsq finished [took 375.2352s]
+07/11/23 01:27:24| INFO bin_sld_gsq finished [took 379.6159s]
+07/11/23 01:29:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 502.0302s]
+07/11/23 01:30:08| INFO mul_sld_gs finished [took 545.0285s]
+07/11/23 01:34:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 802.3620s]
+07/11/23 01:37:25| INFO bin_sld_gs finished [took 982.3260s]
+07/11/23 01:37:25| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 983.7236s]
+07/11/23 01:37:25| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
+07/11/23 01:38:20| INFO ref finished [took 49.9803s]
+07/11/23 01:38:25| INFO atc_mc finished [took 53.3765s]
+07/11/23 01:38:26| INFO atc_ne finished [took 53.8925s]
+07/11/23 01:43:41| INFO mul_sld_gsq finished [took 372.2608s]
+07/11/23 01:43:45| INFO bin_sld_gsq finished [took 377.3380s]
+07/11/23 01:45:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 497.5768s]
+07/11/23 01:46:28| INFO mul_sld_gs finished [took 540.8267s]
+07/11/23 01:51:09| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 822.2849s]
+07/11/23 01:54:10| INFO bin_sld_gs finished [took 1003.7804s]
+07/11/23 01:54:10| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1005.2506s]
+07/11/23 01:54:10| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
+07/11/23 01:55:05| INFO ref finished [took 49.8884s]
+07/11/23 01:55:09| INFO atc_mc finished [took 53.3594s]
+07/11/23 01:55:10| INFO atc_ne finished [took 53.5162s]
+07/11/23 02:00:25| INFO mul_sld_gsq finished [took 371.4460s]
+07/11/23 02:00:41| INFO bin_sld_gsq finished [took 387.6183s]
+07/11/23 02:02:30| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 498.0096s]
+07/11/23 02:03:11| INFO mul_sld_gs finished [took 539.1531s]
+07/11/23 02:07:53| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 821.8730s]
+07/11/23 02:10:52| INFO bin_sld_gs finished [took 1001.0803s]
+07/11/23 02:10:52| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1002.3085s]
+07/11/23 02:10:52| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
+07/11/23 02:11:44| INFO ref finished [took 47.2218s]
+07/11/23 02:11:48| INFO atc_mc finished [took 49.6349s]
+07/11/23 02:11:50| INFO atc_ne finished [took 50.9082s]
+07/11/23 02:16:51| INFO mul_sld_gsq finished [took 354.3706s]
+07/11/23 02:17:11| INFO bin_sld_gsq finished [took 376.0124s]
+07/11/23 02:18:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 476.0587s]
+07/11/23 02:19:33| INFO mul_sld_gs finished [took 518.5692s]
+07/11/23 02:24:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 803.4978s]
+07/11/23 02:27:16| INFO bin_sld_gs finished [took 982.4395s]
+07/11/23 02:27:16| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 983.7838s]
+07/11/23 02:27:16| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
+07/11/23 02:28:08| INFO ref finished [took 46.6191s]
+07/11/23 02:28:13| INFO atc_mc finished [took 50.3543s]
+07/11/23 02:28:15| INFO atc_ne finished [took 51.6601s]
+07/11/23 02:33:15| INFO mul_sld_gsq finished [took 354.6014s]
+07/11/23 02:33:34| INFO bin_sld_gsq finished [took 374.7872s]
+07/11/23 02:35:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 475.9302s]
+07/11/23 02:35:57| INFO mul_sld_gs finished [took 518.5425s]
+07/11/23 02:40:20| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 782.7268s]
+07/11/23 02:43:18| INFO bin_sld_gs finished [took 960.6334s]
+07/11/23 02:43:18| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 961.9030s]
+07/11/23 02:43:18| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
+07/11/23 02:44:10| INFO ref finished [took 47.1234s]
+07/11/23 02:44:14| INFO atc_mc finished [took 49.9871s]
+07/11/23 02:44:16| INFO atc_ne finished [took 50.9160s]
+07/11/23 02:49:19| INFO mul_sld_gsq finished [took 357.0613s]
+07/11/23 02:49:30| INFO bin_sld_gsq finished [took 368.8000s]
+07/11/23 02:51:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 475.7332s]
+07/11/23 02:51:59| INFO mul_sld_gs finished [took 518.6671s]
+07/11/23 02:56:28| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 788.7117s]
+07/11/23 02:59:28| INFO bin_sld_gs finished [took 968.7653s]
+07/11/23 02:59:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 970.1516s]
+07/11/23 02:59:28| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
+07/11/23 03:00:20| INFO ref finished [took 46.9898s]
+07/11/23 03:00:24| INFO atc_mc finished [took 49.8768s]
+07/11/23 03:00:25| INFO atc_ne finished [took 49.6324s]
+07/11/23 03:05:23| INFO mul_sld_gsq finished [took 350.7932s]
+07/11/23 03:05:32| INFO bin_sld_gsq finished [took 360.8665s]
+07/11/23 03:07:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 474.6581s]
+07/11/23 03:08:07| INFO mul_sld_gs finished [took 516.4890s]
+07/11/23 03:12:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 774.9140s]
+07/11/23 03:15:29| INFO bin_sld_gs finished [took 959.3579s]
+07/11/23 03:15:29| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 960.6992s]
+07/11/23 03:15:29| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
+07/11/23 03:16:21| INFO ref finished [took 47.3281s]
+07/11/23 03:16:25| INFO atc_mc finished [took 49.8016s]
+07/11/23 03:16:28| INFO atc_ne finished [took 51.2288s]
+07/11/23 03:21:16| INFO mul_sld_gsq finished [took 343.2861s]
+07/11/23 03:21:22| INFO bin_sld_gsq finished [took 349.6065s]
+07/11/23 03:23:20| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 468.7910s]
+07/11/23 03:24:01| INFO mul_sld_gs finished [took 509.9001s]
+07/11/23 03:28:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 752.8185s]
+07/11/23 03:31:01| INFO bin_sld_gs finished [took 930.3934s]
+07/11/23 03:31:01| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 931.7055s]
+07/11/23 03:31:29| INFO dataset imdb_9prevs
+07/11/23 03:31:37| INFO Dataset sample 0.10 of dataset imdb_9prevs started
+07/11/23 03:31:49| INFO ref finished [took 11.4117s]
+07/11/23 03:31:53| INFO atc_mc finished [took 14.8218s]
+07/11/23 03:31:53| INFO atc_ne finished [took 14.8359s]
+07/11/23 03:32:11| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+07/11/23 03:32:56| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
+07/11/23 03:36:32| INFO mul_sld_gsq finished [took 294.6812s]
+07/11/23 03:38:05| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 387.7698s]
+07/11/23 03:38:18| INFO mul_sld_gs finished [took 400.7660s]
+07/11/23 03:38:18| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 401.3208s]
+07/11/23 03:38:18| INFO Dataset sample 0.20 of dataset imdb_9prevs started
+07/11/23 03:38:30| INFO ref finished [took 11.1665s]
+07/11/23 03:38:34| INFO atc_mc finished [took 14.4483s]
+07/11/23 03:38:34| INFO atc_ne finished [took 14.8634s]
+07/11/23 03:43:16| INFO bin_sld_gsq finished [took 296.8786s]
+07/11/23 03:43:32| INFO mul_sld_gsq finished [took 312.4588s]
+07/11/23 03:45:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 445.1331s]
+07/11/23 03:45:58| INFO mul_sld_gs finished [took 459.5855s]
+07/11/23 03:51:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 766.1528s]
+07/11/23 03:53:40| INFO bin_sld_gs finished [took 921.5996s]
+07/11/23 03:53:40| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 922.0949s]
+07/11/23 03:53:40| INFO Dataset sample 0.30 of dataset imdb_9prevs started
+07/11/23 03:53:53| INFO ref finished [took 11.5825s]
+07/11/23 03:53:57| INFO atc_mc finished [took 14.8590s]
+07/11/23 03:53:57| INFO atc_ne finished [took 15.3090s]
+07/11/23 03:58:53| INFO mul_sld_gsq finished [took 311.9891s]
+07/11/23 03:58:54| INFO bin_sld_gsq finished [took 313.1182s]
+07/11/23 04:01:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 441.3198s]
+07/11/23 04:01:18| INFO mul_sld_gs finished [took 456.2347s]
+07/11/23 04:06:06| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 745.0596s]
+07/11/23 04:08:40| INFO bin_sld_gs finished [took 898.9046s]
+07/11/23 04:08:40| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 899.6778s]
+07/11/23 04:08:40| INFO Dataset sample 0.40 of dataset imdb_9prevs started
+07/11/23 04:08:52| INFO ref finished [took 11.0605s]
+07/11/23 04:08:56| INFO atc_mc finished [took 14.9590s]
+07/11/23 04:08:56| INFO atc_ne finished [took 14.8804s]
+07/11/23 04:13:54| INFO mul_sld_gsq finished [took 313.3797s]
+07/11/23 04:13:56| INFO bin_sld_gsq finished [took 315.5862s]
+07/11/23 04:15:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 432.9025s]
+07/11/23 04:16:08| INFO mul_sld_gs finished [took 447.1098s]
+07/11/23 04:21:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 764.2230s]
+07/11/23 04:23:56| INFO bin_sld_gs finished [took 915.4905s]
+07/11/23 04:23:56| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 916.1187s]
+07/11/23 04:23:56| INFO Dataset sample 0.50 of dataset imdb_9prevs started
+07/11/23 04:24:08| INFO ref finished [took 10.9214s]
+07/11/23 04:24:12| INFO atc_mc finished [took 14.9236s]
+07/11/23 04:24:12| INFO atc_ne finished [took 14.9240s]
+07/11/23 04:29:11| INFO bin_sld_gsq finished [took 314.3071s]
+07/11/23 04:29:19| INFO mul_sld_gsq finished [took 322.1027s]
+07/11/23 04:31:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 448.0202s]
+07/11/23 04:31:40| INFO mul_sld_gs finished [took 463.2243s]
+07/11/23 04:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 746.2797s]
+07/11/23 04:38:55| INFO bin_sld_gs finished [took 898.7899s]
+07/11/23 04:38:55| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 899.2924s]
+07/11/23 04:38:55| INFO Dataset sample 0.60 of dataset imdb_9prevs started
+07/11/23 04:39:08| INFO ref finished [took 11.9811s]
+07/11/23 04:39:12| INFO atc_mc finished [took 15.7159s]
+07/11/23 04:39:12| INFO atc_ne finished [took 15.9512s]
+07/11/23 04:44:19| INFO bin_sld_gsq finished [took 323.1420s]
+07/11/23 04:44:21| INFO mul_sld_gsq finished [took 325.2299s]
+07/11/23 04:46:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 445.8872s]
+07/11/23 04:46:37| INFO mul_sld_gs finished [took 460.6339s]
+07/11/23 04:52:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 786.7500s]
+07/11/23 04:54:36| INFO bin_sld_gs finished [took 940.1627s]
+07/11/23 04:54:36| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 940.6023s]
+07/11/23 04:54:36| INFO Dataset sample 0.70 of dataset imdb_9prevs started
+07/11/23 04:54:48| INFO ref finished [took 11.1744s]
+07/11/23 04:54:52| INFO atc_mc finished [took 14.7518s]
+07/11/23 04:54:52| INFO atc_ne finished [took 14.8147s]
+07/11/23 04:59:45| INFO bin_sld_gsq finished [took 308.3645s]
+07/11/23 05:00:07| INFO mul_sld_gsq finished [took 330.3332s]
+07/11/23 05:02:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 456.8448s]
+07/11/23 05:02:28| INFO mul_sld_gs finished [took 471.4675s]
+07/11/23 05:06:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 731.2847s]
+07/11/23 05:09:19| INFO bin_sld_gs finished [took 882.2200s]
+07/11/23 05:09:19| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 882.8165s]
+07/11/23 05:09:19| INFO Dataset sample 0.80 of dataset imdb_9prevs started
+07/11/23 05:09:31| INFO ref finished [took 11.0645s]
+07/11/23 05:09:35| INFO atc_mc finished [took 14.7375s]
+07/11/23 05:09:35| INFO atc_ne finished [took 14.7704s]
+07/11/23 05:14:22| INFO bin_sld_gsq finished [took 302.1848s]
+07/11/23 05:14:33| INFO mul_sld_gsq finished [took 313.5459s]
+07/11/23 05:16:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 438.9863s]
+07/11/23 05:16:52| INFO mul_sld_gs finished [took 452.7273s]
+07/11/23 05:21:59| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 759.8355s]
+07/11/23 05:24:38| INFO bin_sld_gs finished [took 918.7338s]
+07/11/23 05:24:38| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 919.2981s]
+07/11/23 05:24:38| INFO Dataset sample 0.90 of dataset imdb_9prevs started
+07/11/23 05:24:39| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+07/11/23 05:24:39| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
+07/11/23 05:24:48| INFO ref finished [took 9.1378s]
+07/11/23 05:24:51| INFO atc_mc finished [took 12.1603s]
+07/11/23 05:24:52| INFO atc_ne finished [took 12.3482s]
+07/11/23 05:25:08| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
+07/11/23 05:30:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 353.7904s]
+07/11/23 05:30:45| INFO mul_sld_gs finished [took 365.9283s]
+07/11/23 05:30:45| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 366.4930s]
+----------------------------------------------------------------------------------------------------
diff --git a/quacc/data.py b/quacc/data.py
index 7eb1809..3103d74 100644
--- a/quacc/data.py
+++ b/quacc/data.py
@@ -1,150 +1,150 @@
-import math
-from typing import List, Optional
-
-import numpy as np
-import scipy.sparse as sp
-from quapy.data import LabelledCollection
-
-
-# Extended classes
-#
-# 0 ~ True 0
-# 1 ~ False 1
-# 2 ~ False 0
-# 3 ~ True 1
-# _____________________
-# | | |
-# | True 0 | False 1 |
-# |__________|__________|
-# | | |
-# | False 0 | True 1 |
-# |__________|__________|
-#
-class ExClassManager:
- @staticmethod
- def get_ex(n_classes: int, true_class: int, pred_class: int) -> int:
- return true_class * n_classes + pred_class
-
- @staticmethod
- def get_pred(n_classes: int, ex_class: int) -> int:
- return ex_class % n_classes
-
- @staticmethod
- def get_true(n_classes: int, ex_class: int) -> int:
- return ex_class // n_classes
-
-
-class ExtendedCollection(LabelledCollection):
- def __init__(
- self,
- instances: np.ndarray | sp.csr_matrix,
- labels: np.ndarray,
- classes: Optional[List] = None,
- ):
- super().__init__(instances, labels, classes=classes)
-
- def split_by_pred(self):
- _ncl = int(math.sqrt(self.n_classes))
- _indexes = ExtendedCollection._split_index_by_pred(_ncl, self.instances)
- if isinstance(self.instances, np.ndarray):
- _instances = [
- self.instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
- for ind in _indexes
- ]
- elif isinstance(self.instances, sp.csr_matrix):
- _instances = [
- self.instances[ind]
- if ind.shape[0] > 0
- else sp.csr_matrix(np.empty((0, 0), dtype=int))
- for ind in _indexes
- ]
- _labels = [
- np.asarray(
- [
- ExClassManager.get_true(_ncl, lbl)
- for lbl in (self.labels[ind] if len(ind) > 0 else [])
- ],
- dtype=int,
- )
- for ind in _indexes
- ]
- return [
- ExtendedCollection(inst, lbl, classes=range(0, _ncl))
- for (inst, lbl) in zip(_instances, _labels)
- ]
-
- @classmethod
- def split_inst_by_pred(
- cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
- ) -> (List[np.ndarray | sp.csr_matrix], List[float]):
- _indexes = cls._split_index_by_pred(n_classes, instances)
- if isinstance(instances, np.ndarray):
- _instances = [
- instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
- for ind in _indexes
- ]
- elif isinstance(instances, sp.csr_matrix):
- _instances = [
- instances[ind]
- if ind.shape[0] > 0
- else sp.csr_matrix(np.empty((0, 0), dtype=int))
- for ind in _indexes
- ]
- norms = [inst.shape[0] / instances.shape[0] for inst in _instances]
- return _instances, norms
-
- @classmethod
- def _split_index_by_pred(
- cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
- ) -> List[np.ndarray]:
- if isinstance(instances, np.ndarray):
- _pred_label = [np.argmax(inst[-n_classes:], axis=0) for inst in instances]
- elif isinstance(instances, sp.csr_matrix):
- _pred_label = [
- np.argmax(inst[:, -n_classes:].toarray().flatten(), axis=0)
- for inst in instances
- ]
- else:
- raise ValueError("Unsupported matrix format")
-
- return [
- np.asarray([j for (j, x) in enumerate(_pred_label) if x == i], dtype=int)
- for i in range(0, n_classes)
- ]
-
- @classmethod
- def extend_instances(
- cls, instances: np.ndarray | sp.csr_matrix, pred_proba: np.ndarray
- ) -> np.ndarray | sp.csr_matrix:
- if isinstance(instances, sp.csr_matrix):
- _pred_proba = sp.csr_matrix(pred_proba)
- n_x = sp.hstack([instances, _pred_proba])
- elif isinstance(instances, np.ndarray):
- n_x = np.concatenate((instances, pred_proba), axis=1)
- else:
- raise ValueError("Unsupported matrix format")
-
- return n_x
-
- @classmethod
- def extend_collection(
- cls,
- base: LabelledCollection,
- pred_proba: np.ndarray,
- ):
- n_classes = base.n_classes
-
- # n_X = [ X | predicted probs. ]
- n_x = cls.extend_instances(base.X, pred_proba)
-
- # n_y = (exptected y, predicted y)
- pred_proba = pred_proba[:, -n_classes:]
- preds = np.argmax(pred_proba, axis=-1)
- n_y = np.asarray(
- [
- ExClassManager.get_ex(n_classes, true_class, pred_class)
- for (true_class, pred_class) in zip(base.y, preds)
- ]
- )
-
- return ExtendedCollection(n_x, n_y, classes=[*range(0, n_classes * n_classes)])
+import math
+from typing import List, Optional
+
+import numpy as np
+import scipy.sparse as sp
+from quapy.data import LabelledCollection
+
+
+# Extended classes
+#
+# 0 ~ True 0
+# 1 ~ False 1
+# 2 ~ False 0
+# 3 ~ True 1
+# _____________________
+# | | |
+# | True 0 | False 1 |
+# |__________|__________|
+# | | |
+# | False 0 | True 1 |
+# |__________|__________|
+#
+class ExClassManager:
+ @staticmethod
+ def get_ex(n_classes: int, true_class: int, pred_class: int) -> int:
+ return true_class * n_classes + pred_class
+
+ @staticmethod
+ def get_pred(n_classes: int, ex_class: int) -> int:
+ return ex_class % n_classes
+
+ @staticmethod
+ def get_true(n_classes: int, ex_class: int) -> int:
+ return ex_class // n_classes
+
+
+class ExtendedCollection(LabelledCollection):
+ def __init__(
+ self,
+ instances: np.ndarray | sp.csr_matrix,
+ labels: np.ndarray,
+ classes: Optional[List] = None,
+ ):
+ super().__init__(instances, labels, classes=classes)
+
+ def split_by_pred(self):
+ _ncl = int(math.sqrt(self.n_classes))
+ _indexes = ExtendedCollection._split_index_by_pred(_ncl, self.instances)
+ if isinstance(self.instances, np.ndarray):
+ _instances = [
+ self.instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
+ for ind in _indexes
+ ]
+ elif isinstance(self.instances, sp.csr_matrix):
+ _instances = [
+ self.instances[ind]
+ if ind.shape[0] > 0
+ else sp.csr_matrix(np.empty((0, 0), dtype=int))
+ for ind in _indexes
+ ]
+ _labels = [
+ np.asarray(
+ [
+ ExClassManager.get_true(_ncl, lbl)
+ for lbl in (self.labels[ind] if len(ind) > 0 else [])
+ ],
+ dtype=int,
+ )
+ for ind in _indexes
+ ]
+ return [
+ ExtendedCollection(inst, lbl, classes=range(0, _ncl))
+ for (inst, lbl) in zip(_instances, _labels)
+ ]
+
+ @classmethod
+ def split_inst_by_pred(
+ cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
+ ) -> (List[np.ndarray | sp.csr_matrix], List[float]):
+ _indexes = cls._split_index_by_pred(n_classes, instances)
+ if isinstance(instances, np.ndarray):
+ _instances = [
+ instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
+ for ind in _indexes
+ ]
+ elif isinstance(instances, sp.csr_matrix):
+ _instances = [
+ instances[ind]
+ if ind.shape[0] > 0
+ else sp.csr_matrix(np.empty((0, 0), dtype=int))
+ for ind in _indexes
+ ]
+ norms = [inst.shape[0] / instances.shape[0] for inst in _instances]
+ return _instances, norms
+
+ @classmethod
+ def _split_index_by_pred(
+ cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
+ ) -> List[np.ndarray]:
+ if isinstance(instances, np.ndarray):
+ _pred_label = [np.argmax(inst[-n_classes:], axis=0) for inst in instances]
+ elif isinstance(instances, sp.csr_matrix):
+ _pred_label = [
+ np.argmax(inst[:, -n_classes:].toarray().flatten(), axis=0)
+ for inst in instances
+ ]
+ else:
+ raise ValueError("Unsupported matrix format")
+
+ return [
+ np.asarray([j for (j, x) in enumerate(_pred_label) if x == i], dtype=int)
+ for i in range(0, n_classes)
+ ]
+
+ @classmethod
+ def extend_instances(
+ cls, instances: np.ndarray | sp.csr_matrix, pred_proba: np.ndarray
+ ) -> np.ndarray | sp.csr_matrix:
+ if isinstance(instances, sp.csr_matrix):
+ _pred_proba = sp.csr_matrix(pred_proba)
+ n_x = sp.hstack([instances, _pred_proba])
+ elif isinstance(instances, np.ndarray):
+ n_x = np.concatenate((instances, pred_proba), axis=1)
+ else:
+ raise ValueError("Unsupported matrix format")
+
+ return n_x
+
+ @classmethod
+ def extend_collection(
+ cls,
+ base: LabelledCollection,
+ pred_proba: np.ndarray,
+ ):
+ n_classes = base.n_classes
+
+ # n_X = [ X | predicted probs. ]
+ n_x = cls.extend_instances(base.X, pred_proba)
+
+ # n_y = (exptected y, predicted y)
+ pred_proba = pred_proba[:, -n_classes:]
+ preds = np.argmax(pred_proba, axis=-1)
+ n_y = np.asarray(
+ [
+ ExClassManager.get_ex(n_classes, true_class, pred_class)
+ for (true_class, pred_class) in zip(base.y, preds)
+ ]
+ )
+
+ return ExtendedCollection(n_x, n_y, classes=[*range(0, n_classes * n_classes)])
diff --git a/quacc/dataset.py b/quacc/dataset.py
index aff0fbb..fe91e92 100644
--- a/quacc/dataset.py
+++ b/quacc/dataset.py
@@ -1,171 +1,171 @@
-import math
-from typing import List
-
-import numpy as np
-import quapy as qp
-from quapy.data.base import LabelledCollection
-from sklearn.conftest import fetch_rcv1
-
-TRAIN_VAL_PROP = 0.5
-
-
-class DatasetSample:
- def __init__(
- self,
- train: LabelledCollection,
- validation: LabelledCollection,
- test: LabelledCollection,
- ):
- self.train = train
- self.validation = validation
- self.test = test
-
- @property
- def train_prev(self):
- return self.train.prevalence()
-
- @property
- def validation_prev(self):
- return self.validation.prevalence()
-
- @property
- def prevs(self):
- return {"train": self.train_prev, "validation": self.validation_prev}
-
-
-class Dataset:
- def __init__(self, name, n_prevalences=9, prevs=None, target=None):
- self._name = name
- self._target = target
-
- self.prevs = None
- self.n_prevs = n_prevalences
- if prevs is not None:
- prevs = np.unique([p for p in prevs if p > 0.0 and p < 1.0])
- if prevs.shape[0] > 0:
- self.prevs = np.sort(prevs)
- self.n_prevs = self.prevs.shape[0]
-
- def __spambase(self):
- return qp.datasets.fetch_UCIDataset("spambase", verbose=False).train_test
-
- # provare min_df=5
- def __imdb(self):
- return qp.datasets.fetch_reviews("imdb", tfidf=True, min_df=3).train_test
-
- def __rcv1(self):
- n_train = 23149
- available_targets = ["CCAT", "GCAT", "MCAT"]
-
- if self._target is None or self._target not in available_targets:
- raise ValueError(f"Invalid target {self._target}")
-
- dataset = fetch_rcv1()
- target_index = np.where(dataset.target_names == self._target)[0]
- all_train_d = dataset.data[:n_train, :]
- test_d = dataset.data[n_train:, :]
- labels = dataset.target[:, target_index].toarray().flatten()
- all_train_l, test_l = labels[:n_train], labels[n_train:]
- all_train = LabelledCollection(all_train_d, all_train_l, classes=[0, 1])
- test = LabelledCollection(test_d, test_l, classes=[0, 1])
-
- return all_train, test
-
- def get_raw(self) -> DatasetSample:
- all_train, test = {
- "spambase": self.__spambase,
- "imdb": self.__imdb,
- "rcv1": self.__rcv1,
- }[self._name]()
-
- train, val = all_train.split_stratified(
- train_prop=TRAIN_VAL_PROP, random_state=0
- )
-
- return DatasetSample(train, val, test)
-
- def get(self) -> List[DatasetSample]:
- (all_train, test) = {
- "spambase": self.__spambase,
- "imdb": self.__imdb,
- "rcv1": self.__rcv1,
- }[self._name]()
-
- # resample all_train set to have (0.5, 0.5) prevalence
- at_positives = np.sum(all_train.y)
- all_train = all_train.sampling(
- min(at_positives, len(all_train) - at_positives) * 2, 0.5, random_state=0
- )
-
- # sample prevalences
- if self.prevs is not None:
- prevs = self.prevs
- else:
- prevs = np.linspace(0.0, 1.0, num=self.n_prevs + 1, endpoint=False)[1:]
-
- at_size = min(math.floor(len(all_train) * 0.5 / p) for p in prevs)
- datasets = []
- for p in 1.0 - prevs:
- all_train_sampled = all_train.sampling(at_size, p, random_state=0)
- train, validation = all_train_sampled.split_stratified(
- train_prop=TRAIN_VAL_PROP, random_state=0
- )
- datasets.append(DatasetSample(train, validation, test))
-
- return datasets
-
- def __call__(self):
- return self.get()
-
- @property
- def name(self):
- return (
- f"{self._name}_{self._target}_{self.n_prevs}prevs"
- if self._name == "rcv1"
- else f"{self._name}_{self.n_prevs}prevs"
- )
-
-
-# >>> fetch_rcv1().target_names
-# array(['C11', 'C12', 'C13', 'C14', 'C15', 'C151', 'C1511', 'C152', 'C16',
-# 'C17', 'C171', 'C172', 'C173', 'C174', 'C18', 'C181', 'C182',
-# 'C183', 'C21', 'C22', 'C23', 'C24', 'C31', 'C311', 'C312', 'C313',
-# 'C32', 'C33', 'C331', 'C34', 'C41', 'C411', 'C42', 'CCAT', 'E11',
-# 'E12', 'E121', 'E13', 'E131', 'E132', 'E14', 'E141', 'E142',
-# 'E143', 'E21', 'E211', 'E212', 'E31', 'E311', 'E312', 'E313',
-# 'E41', 'E411', 'E51', 'E511', 'E512', 'E513', 'E61', 'E71', 'ECAT',
-# 'G15', 'G151', 'G152', 'G153', 'G154', 'G155', 'G156', 'G157',
-# 'G158', 'G159', 'GCAT', 'GCRIM', 'GDEF', 'GDIP', 'GDIS', 'GENT',
-# 'GENV', 'GFAS', 'GHEA', 'GJOB', 'GMIL', 'GOBIT', 'GODD', 'GPOL',
-# 'GPRO', 'GREL', 'GSCI', 'GSPO', 'GTOUR', 'GVIO', 'GVOTE', 'GWEA',
-# 'GWELF', 'M11', 'M12', 'M13', 'M131', 'M132', 'M14', 'M141',
-# 'M142', 'M143', 'MCAT'], dtype=object)
-
-
-def rcv1_info():
- dataset = fetch_rcv1()
- n_train = 23149
-
- targets = []
- for target in range(103):
- train_t_prev = np.average(dataset.target[:n_train, target].toarray().flatten())
- test_t_prev = np.average(dataset.target[n_train:, target].toarray().flatten())
- targets.append(
- (
- dataset.target_names[target],
- {
- "train": (1.0 - train_t_prev, train_t_prev),
- "test": (1.0 - test_t_prev, test_t_prev),
- },
- )
- )
-
- targets.sort(key=lambda t: t[1]["train"][1])
- for n, d in targets:
- print(f"{n}:")
- for k, (fp, tp) in d.items():
- print(f"\t{k}: {fp:.4f}, {tp:.4f}")
-
-
-if __name__ == "__main__":
- rcv1_info()
+import math
+from typing import List
+
+import numpy as np
+import quapy as qp
+from quapy.data.base import LabelledCollection
+from sklearn.conftest import fetch_rcv1
+
+TRAIN_VAL_PROP = 0.5
+
+
+class DatasetSample:
+ def __init__(
+ self,
+ train: LabelledCollection,
+ validation: LabelledCollection,
+ test: LabelledCollection,
+ ):
+ self.train = train
+ self.validation = validation
+ self.test = test
+
+ @property
+ def train_prev(self):
+ return self.train.prevalence()
+
+ @property
+ def validation_prev(self):
+ return self.validation.prevalence()
+
+ @property
+ def prevs(self):
+ return {"train": self.train_prev, "validation": self.validation_prev}
+
+
+class Dataset:
+ def __init__(self, name, n_prevalences=9, prevs=None, target=None):
+ self._name = name
+ self._target = target
+
+ self.prevs = None
+ self.n_prevs = n_prevalences
+ if prevs is not None:
+ prevs = np.unique([p for p in prevs if p > 0.0 and p < 1.0])
+ if prevs.shape[0] > 0:
+ self.prevs = np.sort(prevs)
+ self.n_prevs = self.prevs.shape[0]
+
+ def __spambase(self):
+ return qp.datasets.fetch_UCIDataset("spambase", verbose=False).train_test
+
+ # provare min_df=5
+ def __imdb(self):
+ return qp.datasets.fetch_reviews("imdb", tfidf=True, min_df=3).train_test
+
+ def __rcv1(self):
+ n_train = 23149
+ available_targets = ["CCAT", "GCAT", "MCAT"]
+
+ if self._target is None or self._target not in available_targets:
+ raise ValueError(f"Invalid target {self._target}")
+
+ dataset = fetch_rcv1()
+ target_index = np.where(dataset.target_names == self._target)[0]
+ all_train_d = dataset.data[:n_train, :]
+ test_d = dataset.data[n_train:, :]
+ labels = dataset.target[:, target_index].toarray().flatten()
+ all_train_l, test_l = labels[:n_train], labels[n_train:]
+ all_train = LabelledCollection(all_train_d, all_train_l, classes=[0, 1])
+ test = LabelledCollection(test_d, test_l, classes=[0, 1])
+
+ return all_train, test
+
+ def get_raw(self) -> DatasetSample:
+ all_train, test = {
+ "spambase": self.__spambase,
+ "imdb": self.__imdb,
+ "rcv1": self.__rcv1,
+ }[self._name]()
+
+ train, val = all_train.split_stratified(
+ train_prop=TRAIN_VAL_PROP, random_state=0
+ )
+
+ return DatasetSample(train, val, test)
+
+ def get(self) -> List[DatasetSample]:
+ (all_train, test) = {
+ "spambase": self.__spambase,
+ "imdb": self.__imdb,
+ "rcv1": self.__rcv1,
+ }[self._name]()
+
+ # resample all_train set to have (0.5, 0.5) prevalence
+ at_positives = np.sum(all_train.y)
+ all_train = all_train.sampling(
+ min(at_positives, len(all_train) - at_positives) * 2, 0.5, random_state=0
+ )
+
+ # sample prevalences
+ if self.prevs is not None:
+ prevs = self.prevs
+ else:
+ prevs = np.linspace(0.0, 1.0, num=self.n_prevs + 1, endpoint=False)[1:]
+
+ at_size = min(math.floor(len(all_train) * 0.5 / p) for p in prevs)
+ datasets = []
+ for p in 1.0 - prevs:
+ all_train_sampled = all_train.sampling(at_size, p, random_state=0)
+ train, validation = all_train_sampled.split_stratified(
+ train_prop=TRAIN_VAL_PROP, random_state=0
+ )
+ datasets.append(DatasetSample(train, validation, test))
+
+ return datasets
+
+ def __call__(self):
+ return self.get()
+
+ @property
+ def name(self):
+ return (
+ f"{self._name}_{self._target}_{self.n_prevs}prevs"
+ if self._name == "rcv1"
+ else f"{self._name}_{self.n_prevs}prevs"
+ )
+
+
+# >>> fetch_rcv1().target_names
+# array(['C11', 'C12', 'C13', 'C14', 'C15', 'C151', 'C1511', 'C152', 'C16',
+# 'C17', 'C171', 'C172', 'C173', 'C174', 'C18', 'C181', 'C182',
+# 'C183', 'C21', 'C22', 'C23', 'C24', 'C31', 'C311', 'C312', 'C313',
+# 'C32', 'C33', 'C331', 'C34', 'C41', 'C411', 'C42', 'CCAT', 'E11',
+# 'E12', 'E121', 'E13', 'E131', 'E132', 'E14', 'E141', 'E142',
+# 'E143', 'E21', 'E211', 'E212', 'E31', 'E311', 'E312', 'E313',
+# 'E41', 'E411', 'E51', 'E511', 'E512', 'E513', 'E61', 'E71', 'ECAT',
+# 'G15', 'G151', 'G152', 'G153', 'G154', 'G155', 'G156', 'G157',
+# 'G158', 'G159', 'GCAT', 'GCRIM', 'GDEF', 'GDIP', 'GDIS', 'GENT',
+# 'GENV', 'GFAS', 'GHEA', 'GJOB', 'GMIL', 'GOBIT', 'GODD', 'GPOL',
+# 'GPRO', 'GREL', 'GSCI', 'GSPO', 'GTOUR', 'GVIO', 'GVOTE', 'GWEA',
+# 'GWELF', 'M11', 'M12', 'M13', 'M131', 'M132', 'M14', 'M141',
+# 'M142', 'M143', 'MCAT'], dtype=object)
+
+
+def rcv1_info():
+ dataset = fetch_rcv1()
+ n_train = 23149
+
+ targets = []
+ for target in range(103):
+ train_t_prev = np.average(dataset.target[:n_train, target].toarray().flatten())
+ test_t_prev = np.average(dataset.target[n_train:, target].toarray().flatten())
+ targets.append(
+ (
+ dataset.target_names[target],
+ {
+ "train": (1.0 - train_t_prev, train_t_prev),
+ "test": (1.0 - test_t_prev, test_t_prev),
+ },
+ )
+ )
+
+ targets.sort(key=lambda t: t[1]["train"][1])
+ for n, d in targets:
+ print(f"{n}:")
+ for k, (fp, tp) in d.items():
+ print(f"\t{k}: {fp:.4f}, {tp:.4f}")
+
+
+if __name__ == "__main__":
+ rcv1_info()
diff --git a/quacc/environment.py b/quacc/environment.py
index f22f162..92a039a 100644
--- a/quacc/environment.py
+++ b/quacc/environment.py
@@ -1,118 +1,118 @@
-import collections as C
-import copy
-from typing import Any
-
-import yaml
-
-
-class environ:
- _instance = None
- _default_env = {
- "DATASET_NAME": None,
- "DATASET_TARGET": None,
- "METRICS": [],
- "COMP_ESTIMATORS": [],
- "DATASET_N_PREVS": 9,
- "DATASET_PREVS": None,
- "OUT_DIR_NAME": "output",
- "OUT_DIR": None,
- "PLOT_DIR_NAME": "plot",
- "PLOT_OUT_DIR": None,
- "DATASET_DIR_UPDATE": False,
- "PROTOCOL_N_PREVS": 21,
- "PROTOCOL_REPEATS": 100,
- "SAMPLE_SIZE": 1000,
- "PLOT_ESTIMATORS": [],
- "PLOT_STDEV": False,
- }
- _keys = list(_default_env.keys())
-
- def __init__(self):
- self.exec = []
- self.confs = []
- self.load_conf()
- self._stack = C.deque([self.__getdict()])
-
- def __setdict(self, d):
- for k, v in d.items():
- super().__setattr__(k, v)
-
- def __getdict(self):
- return {k: self.__getattribute__(k) for k in environ._keys}
-
- def __setattr__(self, __name: str, __value: Any) -> None:
- if __name in environ._keys:
- self._stack[-1][__name] = __value
- super().__setattr__(__name, __value)
-
- def load_conf(self):
- self.__setdict(environ._default_env)
-
- with open("conf.yaml", "r") as f:
- confs = yaml.safe_load(f)["exec"]
-
- _global = confs["global"]
- _estimators = set()
- for pc in confs["plot_confs"].values():
- _estimators = _estimators.union(set(pc["PLOT_ESTIMATORS"]))
- _global["COMP_ESTIMATORS"] = list(_estimators)
-
- self.__setdict(_global)
-
- self.confs = confs["confs"]
- self.plot_confs = confs["plot_confs"]
-
- def get_confs(self):
- self._stack.append(None)
- for _conf in self.confs:
- self._stack.pop()
- self.__setdict(self._stack[-1])
- self.__setdict(_conf)
- self._stack.append(self.__getdict())
-
- yield copy.deepcopy(self._stack[-1])
-
- self._stack.pop()
-
- def get_plot_confs(self):
- self._stack.append(None)
- for k, pc in self.plot_confs.items():
- self._stack.pop()
- self.__setdict(self._stack[-1])
- self.__setdict(pc)
- self._stack.append(self.__getdict())
-
- name = self.DATASET_NAME
- if self.DATASET_TARGET is not None:
- name += f"_{self.DATASET_TARGET}"
- name += f"_{k}"
- yield name
-
- self._stack.pop()
-
- @property
- def current(self):
- return copy.deepcopy(self.__getdict())
-
-
-env = environ()
-
-if __name__ == "__main__":
- stack = C.deque()
- stack.append(-1)
-
- def __gen(stack: C.deque):
- stack.append(None)
- for i in range(5):
- stack.pop()
- stack.append(i)
- yield stack[-1]
-
- stack.pop()
-
- print(stack)
-
- for i in __gen(stack):
- print(stack, i)
-
- print(stack)
+import collections as C
+import copy
+from typing import Any
+
+import yaml
+
+
+class environ:
+ _instance = None
+ _default_env = {
+ "DATASET_NAME": None,
+ "DATASET_TARGET": None,
+ "METRICS": [],
+ "COMP_ESTIMATORS": [],
+ "DATASET_N_PREVS": 9,
+ "DATASET_PREVS": None,
+ "OUT_DIR_NAME": "output",
+ "OUT_DIR": None,
+ "PLOT_DIR_NAME": "plot",
+ "PLOT_OUT_DIR": None,
+ "DATASET_DIR_UPDATE": False,
+ "PROTOCOL_N_PREVS": 21,
+ "PROTOCOL_REPEATS": 100,
+ "SAMPLE_SIZE": 1000,
+ "PLOT_ESTIMATORS": [],
+ "PLOT_STDEV": False,
+ }
+ _keys = list(_default_env.keys())
+
+ def __init__(self):
+ self.exec = []
+ self.confs = []
+ self.load_conf()
+ self._stack = C.deque([self.__getdict()])
+
+ def __setdict(self, d):
+ for k, v in d.items():
+ super().__setattr__(k, v)
+
+ def __getdict(self):
+ return {k: self.__getattribute__(k) for k in environ._keys}
+
+ def __setattr__(self, __name: str, __value: Any) -> None:
+ if __name in environ._keys:
+ self._stack[-1][__name] = __value
+ super().__setattr__(__name, __value)
+
+ def load_conf(self):
+ self.__setdict(environ._default_env)
+
+ with open("conf.yaml", "r") as f:
+ confs = yaml.safe_load(f)["exec"]
+
+ _global = confs["global"]
+ _estimators = set()
+ for pc in confs["plot_confs"].values():
+ _estimators = _estimators.union(set(pc["PLOT_ESTIMATORS"]))
+ _global["COMP_ESTIMATORS"] = list(_estimators)
+
+ self.__setdict(_global)
+
+ self.confs = confs["confs"]
+ self.plot_confs = confs["plot_confs"]
+
+ def get_confs(self):
+ self._stack.append(None)
+ for _conf in self.confs:
+ self._stack.pop()
+ self.__setdict(self._stack[-1])
+ self.__setdict(_conf)
+ self._stack.append(self.__getdict())
+
+ yield copy.deepcopy(self._stack[-1])
+
+ self._stack.pop()
+
+ def get_plot_confs(self):
+ self._stack.append(None)
+ for k, pc in self.plot_confs.items():
+ self._stack.pop()
+ self.__setdict(self._stack[-1])
+ self.__setdict(pc)
+ self._stack.append(self.__getdict())
+
+ name = self.DATASET_NAME
+ if self.DATASET_TARGET is not None:
+ name += f"_{self.DATASET_TARGET}"
+ name += f"_{k}"
+ yield name
+
+ self._stack.pop()
+
+ @property
+ def current(self):
+ return copy.deepcopy(self.__getdict())
+
+
+env = environ()
+
+if __name__ == "__main__":
+ stack = C.deque()
+ stack.append(-1)
+
+ def __gen(stack: C.deque):
+ stack.append(None)
+ for i in range(5):
+ stack.pop()
+ stack.append(i)
+ yield stack[-1]
+
+ stack.pop()
+
+ print(stack)
+
+ for i in __gen(stack):
+ print(stack, i)
+
+ print(stack)
diff --git a/quacc/error.py b/quacc/error.py
index 4393d72..748c07a 100644
--- a/quacc/error.py
+++ b/quacc/error.py
@@ -1,55 +1,55 @@
-import numpy as np
-
-
-def from_name(err_name):
- assert err_name in ERROR_NAMES, f"unknown error {err_name}"
- callable_error = globals()[err_name]
- return callable_error
-
-
-# def f1(prev):
-# # https://github.com/dice-group/gerbil/wiki/Precision,-Recall-and-F1-measure
-# if prev[0] == 0 and prev[1] == 0 and prev[2] == 0:
-# return 1.0
-# elif prev[0] == 0 and prev[1] > 0 and prev[2] == 0:
-# return 0.0
-# elif prev[0] == 0 and prev[1] == 0 and prev[2] > 0:
-# return float('NaN')
-# else:
-# recall = prev[0] / (prev[0] + prev[1])
-# precision = prev[0] / (prev[0] + prev[2])
-# return 2 * (precision * recall) / (precision + recall)
-
-
-def f1(prev):
- den = (2 * prev[3]) + prev[1] + prev[2]
- if den == 0:
- return 0.0
- else:
- return (2 * prev[3]) / den
-
-
-def f1e(prev):
- return 1 - f1(prev)
-
-
-def acc(prev: np.ndarray) -> float:
- return (prev[0] + prev[3]) / np.sum(prev)
-
-
-def accd(true_prevs: np.ndarray, estim_prevs: np.ndarray) -> np.ndarray:
- vacc = np.vectorize(acc, signature="(m)->()")
- a_tp = vacc(true_prevs)
- a_ep = vacc(estim_prevs)
- return np.abs(a_tp - a_ep)
-
-
-def maccd(true_prevs: np.ndarray, estim_prevs: np.ndarray) -> float:
- return accd(true_prevs, estim_prevs).mean()
-
-
-ACCURACY_ERROR = {maccd}
-ACCURACY_ERROR_SINGLE = {accd}
-ACCURACY_ERROR_NAMES = {func.__name__ for func in ACCURACY_ERROR}
-ACCURACY_ERROR_SINGLE_NAMES = {func.__name__ for func in ACCURACY_ERROR_SINGLE}
-ERROR_NAMES = ACCURACY_ERROR_NAMES | ACCURACY_ERROR_SINGLE_NAMES
+import numpy as np
+
+
+def from_name(err_name):
+ assert err_name in ERROR_NAMES, f"unknown error {err_name}"
+ callable_error = globals()[err_name]
+ return callable_error
+
+
+# def f1(prev):
+# # https://github.com/dice-group/gerbil/wiki/Precision,-Recall-and-F1-measure
+# if prev[0] == 0 and prev[1] == 0 and prev[2] == 0:
+# return 1.0
+# elif prev[0] == 0 and prev[1] > 0 and prev[2] == 0:
+# return 0.0
+# elif prev[0] == 0 and prev[1] == 0 and prev[2] > 0:
+# return float('NaN')
+# else:
+# recall = prev[0] / (prev[0] + prev[1])
+# precision = prev[0] / (prev[0] + prev[2])
+# return 2 * (precision * recall) / (precision + recall)
+
+
+def f1(prev):
+ den = (2 * prev[3]) + prev[1] + prev[2]
+ if den == 0:
+ return 0.0
+ else:
+ return (2 * prev[3]) / den
+
+
+def f1e(prev):
+ return 1 - f1(prev)
+
+
+def acc(prev: np.ndarray) -> float:
+ return (prev[0] + prev[3]) / np.sum(prev)
+
+
+def accd(true_prevs: np.ndarray, estim_prevs: np.ndarray) -> np.ndarray:
+ vacc = np.vectorize(acc, signature="(m)->()")
+ a_tp = vacc(true_prevs)
+ a_ep = vacc(estim_prevs)
+ return np.abs(a_tp - a_ep)
+
+
+def maccd(true_prevs: np.ndarray, estim_prevs: np.ndarray) -> float:
+ return accd(true_prevs, estim_prevs).mean()
+
+
+ACCURACY_ERROR = {maccd}
+ACCURACY_ERROR_SINGLE = {accd}
+ACCURACY_ERROR_NAMES = {func.__name__ for func in ACCURACY_ERROR}
+ACCURACY_ERROR_SINGLE_NAMES = {func.__name__ for func in ACCURACY_ERROR_SINGLE}
+ERROR_NAMES = ACCURACY_ERROR_NAMES | ACCURACY_ERROR_SINGLE_NAMES
diff --git a/quacc/evaluation/__init__.py b/quacc/evaluation/__init__.py
index 1851c4b..aa393ad 100644
--- a/quacc/evaluation/__init__.py
+++ b/quacc/evaluation/__init__.py
@@ -1,34 +1,34 @@
-from typing import Callable, Union
-
-import numpy as np
-from quapy.protocol import AbstractProtocol, OnLabelledCollectionProtocol
-
-import quacc as qc
-
-from ..method.base import BaseAccuracyEstimator
-
-
-def evaluate(
- estimator: BaseAccuracyEstimator,
- protocol: AbstractProtocol,
- error_metric: Union[Callable | str],
-) -> float:
- if isinstance(error_metric, str):
- error_metric = qc.error.from_name(error_metric)
-
- collator_bck_ = protocol.collator
- protocol.collator = OnLabelledCollectionProtocol.get_collator("labelled_collection")
-
- estim_prevs, true_prevs = [], []
- for sample in protocol():
- e_sample = estimator.extend(sample)
- estim_prev = estimator.estimate(e_sample.X, ext=True)
- estim_prevs.append(estim_prev)
- true_prevs.append(e_sample.prevalence())
-
- protocol.collator = collator_bck_
-
- true_prevs = np.array(true_prevs)
- estim_prevs = np.array(estim_prevs)
-
- return error_metric(true_prevs, estim_prevs)
+from typing import Callable, Union
+
+import numpy as np
+from quapy.protocol import AbstractProtocol, OnLabelledCollectionProtocol
+
+import quacc as qc
+
+from ..method.base import BaseAccuracyEstimator
+
+
+def evaluate(
+ estimator: BaseAccuracyEstimator,
+ protocol: AbstractProtocol,
+ error_metric: Union[Callable | str],
+) -> float:
+ if isinstance(error_metric, str):
+ error_metric = qc.error.from_name(error_metric)
+
+ collator_bck_ = protocol.collator
+ protocol.collator = OnLabelledCollectionProtocol.get_collator("labelled_collection")
+
+ estim_prevs, true_prevs = [], []
+ for sample in protocol():
+ e_sample = estimator.extend(sample)
+ estim_prev = estimator.estimate(e_sample.X, ext=True)
+ estim_prevs.append(estim_prev)
+ true_prevs.append(e_sample.prevalence())
+
+ protocol.collator = collator_bck_
+
+ true_prevs = np.array(true_prevs)
+ estim_prevs = np.array(estim_prevs)
+
+ return error_metric(true_prevs, estim_prevs)
diff --git a/quacc/evaluation/baseline.py b/quacc/evaluation/baseline.py
index c51351e..6532568 100644
--- a/quacc/evaluation/baseline.py
+++ b/quacc/evaluation/baseline.py
@@ -1,299 +1,299 @@
-from functools import wraps
-from statistics import mean
-
-import numpy as np
-import sklearn.metrics as metrics
-from quapy.data import LabelledCollection
-from quapy.protocol import AbstractStochasticSeededProtocol
-from scipy.sparse import issparse
-from sklearn.base import BaseEstimator
-from sklearn.model_selection import cross_validate
-
-import baselines.atc as atc
-import baselines.doc as doc
-import baselines.impweight as iw
-import baselines.rca as rcalib
-
-from .report import EvaluationReport
-
-_baselines = {}
-
-
-def baseline(func):
- @wraps(func)
- def wrapper(c_model, validation, protocol):
- return func(c_model, validation, protocol)
-
- _baselines[func.__name__] = wrapper
-
- return wrapper
-
-
-@baseline
-def kfcv(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict",
-):
- c_model_predict = getattr(c_model, predict_method)
-
- scoring = ["accuracy", "f1_macro"]
- scores = cross_validate(c_model, validation.X, validation.y, scoring=scoring)
- acc_score = mean(scores["test_accuracy"])
- f1_score = mean(scores["test_f1_macro"])
-
- report = EvaluationReport(name="kfcv")
- for test in protocol():
- test_preds = c_model_predict(test.X)
- meta_acc = abs(acc_score - metrics.accuracy_score(test.y, test_preds))
- meta_f1 = abs(f1_score - metrics.f1_score(test.y, test_preds))
- report.append_row(
- test.prevalence(),
- acc_score=acc_score,
- f1_score=f1_score,
- acc=meta_acc,
- f1=meta_f1,
- )
-
- return report
-
-
-@baseline
-def ref(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
-):
- c_model_predict = getattr(c_model, "predict")
- report = EvaluationReport(name="ref")
- for test in protocol():
- test_preds = c_model_predict(test.X)
- report.append_row(
- test.prevalence(),
- acc_score=metrics.accuracy_score(test.y, test_preds),
- f1_score=metrics.f1_score(test.y, test_preds),
- )
-
- return report
-
-
-@baseline
-def atc_mc(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict_proba",
-):
- """garg"""
- c_model_predict = getattr(c_model, predict_method)
-
- ## Load ID validation data probs and labels
- val_probs, val_labels = c_model_predict(validation.X), validation.y
-
- ## score function, e.g., negative entropy or argmax confidence
- val_scores = atc.get_max_conf(val_probs)
- val_preds = np.argmax(val_probs, axis=-1)
- _, atc_thres = atc.find_ATC_threshold(val_scores, val_labels == val_preds)
-
- report = EvaluationReport(name="atc_mc")
- for test in protocol():
- ## Load OOD test data probs
- test_probs = c_model_predict(test.X)
- test_preds = np.argmax(test_probs, axis=-1)
- test_scores = atc.get_max_conf(test_probs)
- atc_accuracy = atc.get_ATC_acc(atc_thres, test_scores)
- meta_acc = abs(atc_accuracy - metrics.accuracy_score(test.y, test_preds))
- f1_score = atc.get_ATC_f1(atc_thres, test_scores, test_probs)
- meta_f1 = abs(f1_score - metrics.f1_score(test.y, test_preds))
- report.append_row(
- test.prevalence(),
- acc=meta_acc,
- acc_score=atc_accuracy,
- f1_score=f1_score,
- f1=meta_f1,
- )
-
- return report
-
-
-@baseline
-def atc_ne(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict_proba",
-):
- """garg"""
- c_model_predict = getattr(c_model, predict_method)
-
- ## Load ID validation data probs and labels
- val_probs, val_labels = c_model_predict(validation.X), validation.y
-
- ## score function, e.g., negative entropy or argmax confidence
- val_scores = atc.get_entropy(val_probs)
- val_preds = np.argmax(val_probs, axis=-1)
- _, atc_thres = atc.find_ATC_threshold(val_scores, val_labels == val_preds)
-
- report = EvaluationReport(name="atc_ne")
- for test in protocol():
- ## Load OOD test data probs
- test_probs = c_model_predict(test.X)
- test_preds = np.argmax(test_probs, axis=-1)
- test_scores = atc.get_entropy(test_probs)
- atc_accuracy = atc.get_ATC_acc(atc_thres, test_scores)
- meta_acc = abs(atc_accuracy - metrics.accuracy_score(test.y, test_preds))
- f1_score = atc.get_ATC_f1(atc_thres, test_scores, test_probs)
- meta_f1 = abs(f1_score - metrics.f1_score(test.y, test_preds))
- report.append_row(
- test.prevalence(),
- acc=meta_acc,
- acc_score=atc_accuracy,
- f1_score=f1_score,
- f1=meta_f1,
- )
-
- return report
-
-
-@baseline
-def doc_feat(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict_proba",
-):
- c_model_predict = getattr(c_model, predict_method)
-
- val_probs, val_labels = c_model_predict(validation.X), validation.y
- val_scores = np.max(val_probs, axis=-1)
- val_preds = np.argmax(val_probs, axis=-1)
- v1acc = np.mean(val_preds == val_labels) * 100
-
- report = EvaluationReport(name="doc_feat")
- for test in protocol():
- test_probs = c_model_predict(test.X)
- test_preds = np.argmax(test_probs, axis=-1)
- test_scores = np.max(test_probs, axis=-1)
- score = (v1acc + doc.get_doc(val_scores, test_scores)) / 100.0
- meta_acc = abs(score - metrics.accuracy_score(test.y, test_preds))
- report.append_row(test.prevalence(), acc=meta_acc, acc_score=score)
-
- return report
-
-
-@baseline
-def rca(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict",
-):
- """elsahar19"""
- c_model_predict = getattr(c_model, predict_method)
- val_pred1 = c_model_predict(validation.X)
-
- report = EvaluationReport(name="rca")
- for test in protocol():
- try:
- test_pred = c_model_predict(test.X)
- c_model2 = rcalib.clone_fit(c_model, test.X, test_pred)
- c_model2_predict = getattr(c_model2, predict_method)
- val_pred2 = c_model2_predict(validation.X)
- rca_score = 1.0 - rcalib.get_score(val_pred1, val_pred2, validation.y)
- meta_score = abs(rca_score - metrics.accuracy_score(test.y, test_pred))
- report.append_row(test.prevalence(), acc=meta_score, acc_score=rca_score)
- except ValueError:
- report.append_row(
- test.prevalence(), acc=float("nan"), acc_score=float("nan")
- )
-
- return report
-
-
-@baseline
-def rca_star(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict",
-):
- """elsahar19"""
- c_model_predict = getattr(c_model, predict_method)
- validation1, validation2 = validation.split_stratified(
- train_prop=0.5, random_state=0
- )
- val1_pred = c_model_predict(validation1.X)
- c_model1 = rcalib.clone_fit(c_model, validation1.X, val1_pred)
- c_model1_predict = getattr(c_model1, predict_method)
- val2_pred1 = c_model1_predict(validation2.X)
-
- report = EvaluationReport(name="rca_star")
- for test in protocol():
- try:
- test_pred = c_model_predict(test.X)
- c_model2 = rcalib.clone_fit(c_model, test.X, test_pred)
- c_model2_predict = getattr(c_model2, predict_method)
- val2_pred2 = c_model2_predict(validation2.X)
- rca_star_score = 1.0 - rcalib.get_score(
- val2_pred1, val2_pred2, validation2.y
- )
- meta_score = abs(rca_star_score - metrics.accuracy_score(test.y, test_pred))
- report.append_row(
- test.prevalence(), acc=meta_score, acc_score=rca_star_score
- )
- except ValueError:
- report.append_row(
- test.prevalence(), acc=float("nan"), acc_score=float("nan")
- )
-
- return report
-
-
-@baseline
-def logreg(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict",
-):
- c_model_predict = getattr(c_model, predict_method)
-
- val_preds = c_model_predict(validation.X)
-
- report = EvaluationReport(name="logreg")
- for test in protocol():
- wx = iw.logreg(validation.X, validation.y, test.X)
- test_preds = c_model_predict(test.X)
- estim_acc = iw.get_acc(val_preds, validation.y, wx)
- true_acc = metrics.accuracy_score(test.y, test_preds)
- meta_score = abs(estim_acc - true_acc)
- report.append_row(test.prevalence(), acc=meta_score, acc_score=estim_acc)
-
- return report
-
-
-@baseline
-def kdex2(
- c_model: BaseEstimator,
- validation: LabelledCollection,
- protocol: AbstractStochasticSeededProtocol,
- predict_method="predict",
-):
- c_model_predict = getattr(c_model, predict_method)
-
- val_preds = c_model_predict(validation.X)
- log_likelihood_val = iw.kdex2_lltr(validation.X)
- Xval = validation.X.toarray() if issparse(validation.X) else validation.X
-
- report = EvaluationReport(name="kdex2")
- for test in protocol():
- Xte = test.X.toarray() if issparse(test.X) else test.X
- wx = iw.kdex2_weights(Xval, Xte, log_likelihood_val)
- test_preds = c_model_predict(Xte)
- estim_acc = iw.get_acc(val_preds, validation.y, wx)
- true_acc = metrics.accuracy_score(test.y, test_preds)
- meta_score = abs(estim_acc - true_acc)
- report.append_row(test.prevalence(), acc=meta_score, acc_score=estim_acc)
-
- return report
+from functools import wraps
+from statistics import mean
+
+import numpy as np
+import sklearn.metrics as metrics
+from quapy.data import LabelledCollection
+from quapy.protocol import AbstractStochasticSeededProtocol
+from scipy.sparse import issparse
+from sklearn.base import BaseEstimator
+from sklearn.model_selection import cross_validate
+
+import baselines.atc as atc
+import baselines.doc as doc
+import baselines.impweight as iw
+import baselines.rca as rcalib
+
+from .report import EvaluationReport
+
+_baselines = {}
+
+
+def baseline(func):
+ @wraps(func)
+ def wrapper(c_model, validation, protocol):
+ return func(c_model, validation, protocol)
+
+ _baselines[func.__name__] = wrapper
+
+ return wrapper
+
+
+@baseline
+def kfcv(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict",
+):
+ c_model_predict = getattr(c_model, predict_method)
+
+ scoring = ["accuracy", "f1_macro"]
+ scores = cross_validate(c_model, validation.X, validation.y, scoring=scoring)
+ acc_score = mean(scores["test_accuracy"])
+ f1_score = mean(scores["test_f1_macro"])
+
+ report = EvaluationReport(name="kfcv")
+ for test in protocol():
+ test_preds = c_model_predict(test.X)
+ meta_acc = abs(acc_score - metrics.accuracy_score(test.y, test_preds))
+ meta_f1 = abs(f1_score - metrics.f1_score(test.y, test_preds))
+ report.append_row(
+ test.prevalence(),
+ acc_score=acc_score,
+ f1_score=f1_score,
+ acc=meta_acc,
+ f1=meta_f1,
+ )
+
+ return report
+
+
+@baseline
+def ref(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+):
+ c_model_predict = getattr(c_model, "predict")
+ report = EvaluationReport(name="ref")
+ for test in protocol():
+ test_preds = c_model_predict(test.X)
+ report.append_row(
+ test.prevalence(),
+ acc_score=metrics.accuracy_score(test.y, test_preds),
+ f1_score=metrics.f1_score(test.y, test_preds),
+ )
+
+ return report
+
+
+@baseline
+def atc_mc(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict_proba",
+):
+ """garg"""
+ c_model_predict = getattr(c_model, predict_method)
+
+ ## Load ID validation data probs and labels
+ val_probs, val_labels = c_model_predict(validation.X), validation.y
+
+ ## score function, e.g., negative entropy or argmax confidence
+ val_scores = atc.get_max_conf(val_probs)
+ val_preds = np.argmax(val_probs, axis=-1)
+ _, atc_thres = atc.find_ATC_threshold(val_scores, val_labels == val_preds)
+
+ report = EvaluationReport(name="atc_mc")
+ for test in protocol():
+ ## Load OOD test data probs
+ test_probs = c_model_predict(test.X)
+ test_preds = np.argmax(test_probs, axis=-1)
+ test_scores = atc.get_max_conf(test_probs)
+ atc_accuracy = atc.get_ATC_acc(atc_thres, test_scores)
+ meta_acc = abs(atc_accuracy - metrics.accuracy_score(test.y, test_preds))
+ f1_score = atc.get_ATC_f1(atc_thres, test_scores, test_probs)
+ meta_f1 = abs(f1_score - metrics.f1_score(test.y, test_preds))
+ report.append_row(
+ test.prevalence(),
+ acc=meta_acc,
+ acc_score=atc_accuracy,
+ f1_score=f1_score,
+ f1=meta_f1,
+ )
+
+ return report
+
+
+@baseline
+def atc_ne(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict_proba",
+):
+ """garg"""
+ c_model_predict = getattr(c_model, predict_method)
+
+ ## Load ID validation data probs and labels
+ val_probs, val_labels = c_model_predict(validation.X), validation.y
+
+ ## score function, e.g., negative entropy or argmax confidence
+ val_scores = atc.get_entropy(val_probs)
+ val_preds = np.argmax(val_probs, axis=-1)
+ _, atc_thres = atc.find_ATC_threshold(val_scores, val_labels == val_preds)
+
+ report = EvaluationReport(name="atc_ne")
+ for test in protocol():
+ ## Load OOD test data probs
+ test_probs = c_model_predict(test.X)
+ test_preds = np.argmax(test_probs, axis=-1)
+ test_scores = atc.get_entropy(test_probs)
+ atc_accuracy = atc.get_ATC_acc(atc_thres, test_scores)
+ meta_acc = abs(atc_accuracy - metrics.accuracy_score(test.y, test_preds))
+ f1_score = atc.get_ATC_f1(atc_thres, test_scores, test_probs)
+ meta_f1 = abs(f1_score - metrics.f1_score(test.y, test_preds))
+ report.append_row(
+ test.prevalence(),
+ acc=meta_acc,
+ acc_score=atc_accuracy,
+ f1_score=f1_score,
+ f1=meta_f1,
+ )
+
+ return report
+
+
+@baseline
+def doc_feat(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict_proba",
+):
+ c_model_predict = getattr(c_model, predict_method)
+
+ val_probs, val_labels = c_model_predict(validation.X), validation.y
+ val_scores = np.max(val_probs, axis=-1)
+ val_preds = np.argmax(val_probs, axis=-1)
+ v1acc = np.mean(val_preds == val_labels) * 100
+
+ report = EvaluationReport(name="doc_feat")
+ for test in protocol():
+ test_probs = c_model_predict(test.X)
+ test_preds = np.argmax(test_probs, axis=-1)
+ test_scores = np.max(test_probs, axis=-1)
+ score = (v1acc + doc.get_doc(val_scores, test_scores)) / 100.0
+ meta_acc = abs(score - metrics.accuracy_score(test.y, test_preds))
+ report.append_row(test.prevalence(), acc=meta_acc, acc_score=score)
+
+ return report
+
+
+@baseline
+def rca(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict",
+):
+ """elsahar19"""
+ c_model_predict = getattr(c_model, predict_method)
+ val_pred1 = c_model_predict(validation.X)
+
+ report = EvaluationReport(name="rca")
+ for test in protocol():
+ try:
+ test_pred = c_model_predict(test.X)
+ c_model2 = rcalib.clone_fit(c_model, test.X, test_pred)
+ c_model2_predict = getattr(c_model2, predict_method)
+ val_pred2 = c_model2_predict(validation.X)
+ rca_score = 1.0 - rcalib.get_score(val_pred1, val_pred2, validation.y)
+ meta_score = abs(rca_score - metrics.accuracy_score(test.y, test_pred))
+ report.append_row(test.prevalence(), acc=meta_score, acc_score=rca_score)
+ except ValueError:
+ report.append_row(
+ test.prevalence(), acc=float("nan"), acc_score=float("nan")
+ )
+
+ return report
+
+
+@baseline
+def rca_star(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict",
+):
+ """elsahar19"""
+ c_model_predict = getattr(c_model, predict_method)
+ validation1, validation2 = validation.split_stratified(
+ train_prop=0.5, random_state=0
+ )
+ val1_pred = c_model_predict(validation1.X)
+ c_model1 = rcalib.clone_fit(c_model, validation1.X, val1_pred)
+ c_model1_predict = getattr(c_model1, predict_method)
+ val2_pred1 = c_model1_predict(validation2.X)
+
+ report = EvaluationReport(name="rca_star")
+ for test in protocol():
+ try:
+ test_pred = c_model_predict(test.X)
+ c_model2 = rcalib.clone_fit(c_model, test.X, test_pred)
+ c_model2_predict = getattr(c_model2, predict_method)
+ val2_pred2 = c_model2_predict(validation2.X)
+ rca_star_score = 1.0 - rcalib.get_score(
+ val2_pred1, val2_pred2, validation2.y
+ )
+ meta_score = abs(rca_star_score - metrics.accuracy_score(test.y, test_pred))
+ report.append_row(
+ test.prevalence(), acc=meta_score, acc_score=rca_star_score
+ )
+ except ValueError:
+ report.append_row(
+ test.prevalence(), acc=float("nan"), acc_score=float("nan")
+ )
+
+ return report
+
+
+@baseline
+def logreg(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict",
+):
+ c_model_predict = getattr(c_model, predict_method)
+
+ val_preds = c_model_predict(validation.X)
+
+ report = EvaluationReport(name="logreg")
+ for test in protocol():
+ wx = iw.logreg(validation.X, validation.y, test.X)
+ test_preds = c_model_predict(test.X)
+ estim_acc = iw.get_acc(val_preds, validation.y, wx)
+ true_acc = metrics.accuracy_score(test.y, test_preds)
+ meta_score = abs(estim_acc - true_acc)
+ report.append_row(test.prevalence(), acc=meta_score, acc_score=estim_acc)
+
+ return report
+
+
+@baseline
+def kdex2(
+ c_model: BaseEstimator,
+ validation: LabelledCollection,
+ protocol: AbstractStochasticSeededProtocol,
+ predict_method="predict",
+):
+ c_model_predict = getattr(c_model, predict_method)
+
+ val_preds = c_model_predict(validation.X)
+ log_likelihood_val = iw.kdex2_lltr(validation.X)
+ Xval = validation.X.toarray() if issparse(validation.X) else validation.X
+
+ report = EvaluationReport(name="kdex2")
+ for test in protocol():
+ Xte = test.X.toarray() if issparse(test.X) else test.X
+ wx = iw.kdex2_weights(Xval, Xte, log_likelihood_val)
+ test_preds = c_model_predict(Xte)
+ estim_acc = iw.get_acc(val_preds, validation.y, wx)
+ true_acc = metrics.accuracy_score(test.y, test_preds)
+ meta_score = abs(estim_acc - true_acc)
+ report.append_row(test.prevalence(), acc=meta_score, acc_score=estim_acc)
+
+ return report
diff --git a/quacc/evaluation/comp.py b/quacc/evaluation/comp.py
index 6df27a6..37ce1ae 100644
--- a/quacc/evaluation/comp.py
+++ b/quacc/evaluation/comp.py
@@ -1,128 +1,128 @@
-import multiprocessing
-import time
-from traceback import print_exception as traceback
-from typing import List
-
-import numpy as np
-import pandas as pd
-import quapy as qp
-
-from quacc.dataset import Dataset
-from quacc.environment import env
-from quacc.evaluation import baseline, method
-from quacc.evaluation.report import CompReport, DatasetReport, EvaluationReport
-from quacc.evaluation.worker import estimate_worker
-from quacc.logger import Logger
-
-pd.set_option("display.float_format", "{:.4f}".format)
-qp.environ["SAMPLE_SIZE"] = env.SAMPLE_SIZE
-
-
-class CompEstimatorName_:
- def __init__(self, ce):
- self.ce = ce
-
- def __getitem__(self, e: str | List[str]):
- if isinstance(e, str):
- return self.ce._CompEstimator__get(e)[0]
- elif isinstance(e, list):
- return list(self.ce._CompEstimator__get(e).keys())
-
-
-class CompEstimatorFunc_:
- def __init__(self, ce):
- self.ce = ce
-
- def __getitem__(self, e: str | List[str]):
- if isinstance(e, str):
- return self.ce._CompEstimator__get(e)[1]
- elif isinstance(e, list):
- return list(self.ce._CompEstimator__get(e).values())
-
-
-class CompEstimator:
- __dict = method._methods | baseline._baselines
-
- def __get(cls, e: str | List[str]):
- if isinstance(e, str):
- try:
- return (e, cls.__dict[e])
- except KeyError:
- raise KeyError(f"Invalid estimator: estimator {e} does not exist")
- elif isinstance(e, list):
- _subtr = np.setdiff1d(e, list(cls.__dict.keys()))
- if len(_subtr) > 0:
- raise KeyError(
- f"Invalid estimator: estimator {_subtr[0]} does not exist"
- )
-
- e_fun = {k: fun for k, fun in cls.__dict.items() if k in e}
- if "ref" not in e:
- e_fun["ref"] = cls.__dict["ref"]
-
- return e_fun
-
- @property
- def name(self):
- return CompEstimatorName_(self)
-
- @property
- def func(self):
- return CompEstimatorFunc_(self)
-
-
-CE = CompEstimator()
-
-
-def evaluate_comparison(dataset: Dataset, estimators=None) -> EvaluationReport:
- log = Logger.logger()
- # with multiprocessing.Pool(1) as pool:
- with multiprocessing.Pool(len(estimators)) as pool:
- dr = DatasetReport(dataset.name)
- log.info(f"dataset {dataset.name}")
- for d in dataset():
- log.info(
- f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} started"
- )
- tstart = time.time()
- tasks = [
- (estim, d.train, d.validation, d.test) for estim in CE.func[estimators]
- ]
- results = [
- pool.apply_async(estimate_worker, t, {"_env": env, "q": Logger.queue()})
- for t in tasks
- ]
-
- results_got = []
- for _r in results:
- try:
- r = _r.get()
- if r["result"] is not None:
- results_got.append(r)
- except Exception as e:
- log.warning(
- f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} failed. Exception: {e}"
- )
-
- tend = time.time()
- times = {r["name"]: r["time"] for r in results_got}
- times["tot"] = tend - tstart
- log.info(
- f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} finished [took {times['tot']:.4f}s]"
- )
- try:
- cr = CompReport(
- [r["result"] for r in results_got],
- name=dataset.name,
- train_prev=d.train_prev,
- valid_prev=d.validation_prev,
- times=times,
- )
- except Exception as e:
- log.warning(
- f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} failed. Exception: {e}"
- )
- traceback(e)
- cr = None
- dr += cr
- return dr
+import multiprocessing
+import time
+from traceback import print_exception as traceback
+from typing import List
+
+import numpy as np
+import pandas as pd
+import quapy as qp
+
+from quacc.dataset import Dataset
+from quacc.environment import env
+from quacc.evaluation import baseline, method
+from quacc.evaluation.report import CompReport, DatasetReport, EvaluationReport
+from quacc.evaluation.worker import estimate_worker
+from quacc.logger import Logger
+
+pd.set_option("display.float_format", "{:.4f}".format)
+qp.environ["SAMPLE_SIZE"] = env.SAMPLE_SIZE
+
+
+class CompEstimatorName_:
+ def __init__(self, ce):
+ self.ce = ce
+
+ def __getitem__(self, e: str | List[str]):
+ if isinstance(e, str):
+ return self.ce._CompEstimator__get(e)[0]
+ elif isinstance(e, list):
+ return list(self.ce._CompEstimator__get(e).keys())
+
+
+class CompEstimatorFunc_:
+ def __init__(self, ce):
+ self.ce = ce
+
+ def __getitem__(self, e: str | List[str]):
+ if isinstance(e, str):
+ return self.ce._CompEstimator__get(e)[1]
+ elif isinstance(e, list):
+ return list(self.ce._CompEstimator__get(e).values())
+
+
+class CompEstimator:
+ __dict = method._methods | baseline._baselines
+
+ def __get(cls, e: str | List[str]):
+ if isinstance(e, str):
+ try:
+ return (e, cls.__dict[e])
+ except KeyError:
+ raise KeyError(f"Invalid estimator: estimator {e} does not exist")
+ elif isinstance(e, list):
+ _subtr = np.setdiff1d(e, list(cls.__dict.keys()))
+ if len(_subtr) > 0:
+ raise KeyError(
+ f"Invalid estimator: estimator {_subtr[0]} does not exist"
+ )
+
+ e_fun = {k: fun for k, fun in cls.__dict.items() if k in e}
+ if "ref" not in e:
+ e_fun["ref"] = cls.__dict["ref"]
+
+ return e_fun
+
+ @property
+ def name(self):
+ return CompEstimatorName_(self)
+
+ @property
+ def func(self):
+ return CompEstimatorFunc_(self)
+
+
+CE = CompEstimator()
+
+
+def evaluate_comparison(dataset: Dataset, estimators=None) -> EvaluationReport:
+ log = Logger.logger()
+ # with multiprocessing.Pool(1) as pool:
+ with multiprocessing.Pool(len(estimators)) as pool:
+ dr = DatasetReport(dataset.name)
+ log.info(f"dataset {dataset.name}")
+ for d in dataset():
+ log.info(
+ f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} started"
+ )
+ tstart = time.time()
+ tasks = [
+ (estim, d.train, d.validation, d.test) for estim in CE.func[estimators]
+ ]
+ results = [
+ pool.apply_async(estimate_worker, t, {"_env": env, "q": Logger.queue()})
+ for t in tasks
+ ]
+
+ results_got = []
+ for _r in results:
+ try:
+ r = _r.get()
+ if r["result"] is not None:
+ results_got.append(r)
+ except Exception as e:
+ log.warning(
+ f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} failed. Exception: {e}"
+ )
+
+ tend = time.time()
+ times = {r["name"]: r["time"] for r in results_got}
+ times["tot"] = tend - tstart
+ log.info(
+ f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} finished [took {times['tot']:.4f}s]"
+ )
+ try:
+ cr = CompReport(
+ [r["result"] for r in results_got],
+ name=dataset.name,
+ train_prev=d.train_prev,
+ valid_prev=d.validation_prev,
+ times=times,
+ )
+ except Exception as e:
+ log.warning(
+ f"Dataset sample {d.train_prev[1]:.2f} of dataset {dataset.name} failed. Exception: {e}"
+ )
+ traceback(e)
+ cr = None
+ dr += cr
+ return dr
diff --git a/quacc/evaluation/method.py b/quacc/evaluation/method.py
index 0caf9c3..8419c52 100644
--- a/quacc/evaluation/method.py
+++ b/quacc/evaluation/method.py
@@ -1,305 +1,305 @@
-import inspect
-from functools import wraps
-
-import numpy as np
-from quapy.method.aggregative import PACC, SLD, CC
-from quapy.protocol import UPP, AbstractProtocol
-from sklearn.linear_model import LogisticRegression
-
-import quacc as qc
-from quacc.evaluation.report import EvaluationReport
-from quacc.method.model_selection import BQAEgsq, GridSearchAE, MCAEgsq
-
-from ..method.base import BQAE, MCAE, BaseAccuracyEstimator
-
-_methods = {}
-_sld_param_grid = {
- "q__classifier__C": np.logspace(-3, 3, 7),
- "q__classifier__class_weight": [None, "balanced"],
- "q__recalib": [None, "bcts"],
- "q__exact_train_prev": [True],
- "confidence": [None, "max_conf", "entropy"],
-}
-_pacc_param_grid = {
- "q__classifier__C": np.logspace(-3, 3, 7),
- "q__classifier__class_weight": [None, "balanced"],
- "confidence": [None, "max_conf", "entropy"],
-}
-def method(func):
- @wraps(func)
- def wrapper(c_model, validation, protocol):
- return func(c_model, validation, protocol)
-
- _methods[func.__name__] = wrapper
-
- return wrapper
-
-
-def evaluation_report(
- estimator: BaseAccuracyEstimator,
- protocol: AbstractProtocol,
-) -> EvaluationReport:
- method_name = inspect.stack()[1].function
- report = EvaluationReport(name=method_name)
- for sample in protocol():
- e_sample = estimator.extend(sample)
- estim_prev = estimator.estimate(e_sample.X, ext=True)
- acc_score = qc.error.acc(estim_prev)
- f1_score = qc.error.f1(estim_prev)
- report.append_row(
- sample.prevalence(),
- acc_score=acc_score,
- acc=abs(qc.error.acc(e_sample.prevalence()) - acc_score),
- f1_score=f1_score,
- f1=abs(qc.error.f1(e_sample.prevalence()) - f1_score),
- )
-
- return report
-
-
-@method
-def bin_sld(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(c_model, SLD(LogisticRegression())).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mul_sld(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(c_model, SLD(LogisticRegression())).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def binmc_sld(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(
- c_model,
- SLD(LogisticRegression()),
- confidence="max_conf",
- ).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mulmc_sld(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(
- c_model,
- SLD(LogisticRegression()),
- confidence="max_conf",
- ).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def binne_sld(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(
- c_model,
- SLD(LogisticRegression()),
- confidence="entropy",
- ).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mulne_sld(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(
- c_model,
- SLD(LogisticRegression()),
- confidence="entropy",
- ).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def bin_sld_gs(c_model, validation, protocol) -> EvaluationReport:
- v_train, v_val = validation.split_stratified(0.6, random_state=0)
- model = BQAE(c_model, SLD(LogisticRegression()))
- est = GridSearchAE(
- model=model,
- param_grid=_sld_param_grid,
- refit=False,
- protocol=UPP(v_val, repeats=100),
- verbose=True,
- ).fit(v_train)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mul_sld_gs(c_model, validation, protocol) -> EvaluationReport:
- v_train, v_val = validation.split_stratified(0.6, random_state=0)
- model = MCAE(c_model, SLD(LogisticRegression()))
- est = GridSearchAE(
- model=model,
- param_grid=_sld_param_grid,
- refit=False,
- protocol=UPP(v_val, repeats=100),
- verbose=True,
- ).fit(v_train)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def bin_sld_gsq(c_model, validation, protocol) -> EvaluationReport:
- est = BQAEgsq(
- c_model,
- SLD(LogisticRegression()),
- param_grid={
- "classifier__C": np.logspace(-3, 3, 7),
- "classifier__class_weight": [None, "balanced"],
- "recalib": [None, "bcts", "vs"],
- },
- refit=False,
- verbose=False,
- ).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mul_sld_gsq(c_model, validation, protocol) -> EvaluationReport:
- est = MCAEgsq(
- c_model,
- SLD(LogisticRegression()),
- param_grid={
- "classifier__C": np.logspace(-3, 3, 7),
- "classifier__class_weight": [None, "balanced"],
- "recalib": [None, "bcts", "vs"],
- },
- refit=False,
- verbose=False,
- ).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def bin_pacc(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(c_model, PACC(LogisticRegression())).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mul_pacc(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(c_model, PACC(LogisticRegression())).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def binmc_pacc(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(c_model, PACC(LogisticRegression()), confidence="max_conf").fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mulmc_pacc(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(c_model, PACC(LogisticRegression()), confidence="max_conf").fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def binne_pacc(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(c_model, PACC(LogisticRegression()), confidence="entropy").fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mulne_pacc(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(c_model, PACC(LogisticRegression()), confidence="entropy").fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def bin_pacc_gs(c_model, validation, protocol) -> EvaluationReport:
- v_train, v_val = validation.split_stratified(0.6, random_state=0)
- model = BQAE(c_model, PACC(LogisticRegression()))
- est = GridSearchAE(
- model=model,
- param_grid=_pacc_param_grid,
- refit=False,
- protocol=UPP(v_val, repeats=100),
- verbose=False,
- ).fit(v_train)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mul_pacc_gs(c_model, validation, protocol) -> EvaluationReport:
- v_train, v_val = validation.split_stratified(0.6, random_state=0)
- model = MCAE(c_model, PACC(LogisticRegression()))
- est = GridSearchAE(
- model=model,
- param_grid=_pacc_param_grid,
- refit=False,
- protocol=UPP(v_val, repeats=100),
- verbose=False,
- ).fit(v_train)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def bin_cc(c_model, validation, protocol) -> EvaluationReport:
- est = BQAE(c_model, CC(LogisticRegression())).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
-
-
-@method
-def mul_cc(c_model, validation, protocol) -> EvaluationReport:
- est = MCAE(c_model, CC(LogisticRegression())).fit(validation)
- return evaluation_report(
- estimator=est,
- protocol=protocol,
- )
+import inspect
+from functools import wraps
+
+import numpy as np
+from quapy.method.aggregative import PACC, SLD, CC
+from quapy.protocol import UPP, AbstractProtocol
+from sklearn.linear_model import LogisticRegression
+
+import quacc as qc
+from quacc.evaluation.report import EvaluationReport
+from quacc.method.model_selection import BQAEgsq, GridSearchAE, MCAEgsq
+
+from ..method.base import BQAE, MCAE, BaseAccuracyEstimator
+
+_methods = {}
+_sld_param_grid = {
+ "q__classifier__C": np.logspace(-3, 3, 7),
+ "q__classifier__class_weight": [None, "balanced"],
+ "q__recalib": [None, "bcts"],
+ "q__exact_train_prev": [True],
+ "confidence": [None, "max_conf", "entropy"],
+}
+_pacc_param_grid = {
+ "q__classifier__C": np.logspace(-3, 3, 7),
+ "q__classifier__class_weight": [None, "balanced"],
+ "confidence": [None, "max_conf", "entropy"],
+}
+def method(func):
+ @wraps(func)
+ def wrapper(c_model, validation, protocol):
+ return func(c_model, validation, protocol)
+
+ _methods[func.__name__] = wrapper
+
+ return wrapper
+
+
+def evaluation_report(
+ estimator: BaseAccuracyEstimator,
+ protocol: AbstractProtocol,
+) -> EvaluationReport:
+ method_name = inspect.stack()[1].function
+ report = EvaluationReport(name=method_name)
+ for sample in protocol():
+ e_sample = estimator.extend(sample)
+ estim_prev = estimator.estimate(e_sample.X, ext=True)
+ acc_score = qc.error.acc(estim_prev)
+ f1_score = qc.error.f1(estim_prev)
+ report.append_row(
+ sample.prevalence(),
+ acc_score=acc_score,
+ acc=abs(qc.error.acc(e_sample.prevalence()) - acc_score),
+ f1_score=f1_score,
+ f1=abs(qc.error.f1(e_sample.prevalence()) - f1_score),
+ )
+
+ return report
+
+
+@method
+def bin_sld(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(c_model, SLD(LogisticRegression())).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mul_sld(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(c_model, SLD(LogisticRegression())).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def binmc_sld(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(
+ c_model,
+ SLD(LogisticRegression()),
+ confidence="max_conf",
+ ).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mulmc_sld(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(
+ c_model,
+ SLD(LogisticRegression()),
+ confidence="max_conf",
+ ).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def binne_sld(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(
+ c_model,
+ SLD(LogisticRegression()),
+ confidence="entropy",
+ ).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mulne_sld(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(
+ c_model,
+ SLD(LogisticRegression()),
+ confidence="entropy",
+ ).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def bin_sld_gs(c_model, validation, protocol) -> EvaluationReport:
+ v_train, v_val = validation.split_stratified(0.6, random_state=0)
+ model = BQAE(c_model, SLD(LogisticRegression()))
+ est = GridSearchAE(
+ model=model,
+ param_grid=_sld_param_grid,
+ refit=False,
+ protocol=UPP(v_val, repeats=100),
+ verbose=True,
+ ).fit(v_train)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mul_sld_gs(c_model, validation, protocol) -> EvaluationReport:
+ v_train, v_val = validation.split_stratified(0.6, random_state=0)
+ model = MCAE(c_model, SLD(LogisticRegression()))
+ est = GridSearchAE(
+ model=model,
+ param_grid=_sld_param_grid,
+ refit=False,
+ protocol=UPP(v_val, repeats=100),
+ verbose=True,
+ ).fit(v_train)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def bin_sld_gsq(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAEgsq(
+ c_model,
+ SLD(LogisticRegression()),
+ param_grid={
+ "classifier__C": np.logspace(-3, 3, 7),
+ "classifier__class_weight": [None, "balanced"],
+ "recalib": [None, "bcts", "vs"],
+ },
+ refit=False,
+ verbose=False,
+ ).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mul_sld_gsq(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAEgsq(
+ c_model,
+ SLD(LogisticRegression()),
+ param_grid={
+ "classifier__C": np.logspace(-3, 3, 7),
+ "classifier__class_weight": [None, "balanced"],
+ "recalib": [None, "bcts", "vs"],
+ },
+ refit=False,
+ verbose=False,
+ ).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def bin_pacc(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(c_model, PACC(LogisticRegression())).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mul_pacc(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(c_model, PACC(LogisticRegression())).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def binmc_pacc(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(c_model, PACC(LogisticRegression()), confidence="max_conf").fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mulmc_pacc(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(c_model, PACC(LogisticRegression()), confidence="max_conf").fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def binne_pacc(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(c_model, PACC(LogisticRegression()), confidence="entropy").fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mulne_pacc(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(c_model, PACC(LogisticRegression()), confidence="entropy").fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def bin_pacc_gs(c_model, validation, protocol) -> EvaluationReport:
+ v_train, v_val = validation.split_stratified(0.6, random_state=0)
+ model = BQAE(c_model, PACC(LogisticRegression()))
+ est = GridSearchAE(
+ model=model,
+ param_grid=_pacc_param_grid,
+ refit=False,
+ protocol=UPP(v_val, repeats=100),
+ verbose=False,
+ ).fit(v_train)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mul_pacc_gs(c_model, validation, protocol) -> EvaluationReport:
+ v_train, v_val = validation.split_stratified(0.6, random_state=0)
+ model = MCAE(c_model, PACC(LogisticRegression()))
+ est = GridSearchAE(
+ model=model,
+ param_grid=_pacc_param_grid,
+ refit=False,
+ protocol=UPP(v_val, repeats=100),
+ verbose=False,
+ ).fit(v_train)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def bin_cc(c_model, validation, protocol) -> EvaluationReport:
+ est = BQAE(c_model, CC(LogisticRegression())).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
+
+
+@method
+def mul_cc(c_model, validation, protocol) -> EvaluationReport:
+ est = MCAE(c_model, CC(LogisticRegression())).fit(validation)
+ return evaluation_report(
+ estimator=est,
+ protocol=protocol,
+ )
diff --git a/quacc/evaluation/report.py b/quacc/evaluation/report.py
index 7421a2b..22f16ad 100644
--- a/quacc/evaluation/report.py
+++ b/quacc/evaluation/report.py
@@ -1,565 +1,565 @@
-from pathlib import Path
-from typing import List, Tuple
-
-import numpy as np
-import pandas as pd
-
-from quacc import plot
-from quacc.environment import env
-from quacc.utils import fmt_line_md
-
-
-def _get_metric(metric: str):
- return slice(None) if metric is None else metric
-
-
-def _get_estimators(estimators: List[str], cols: np.ndarray):
- return slice(None) if estimators is None else cols[np.in1d(cols, estimators)]
-
-
-class EvaluationReport:
- def __init__(self, name=None):
- self.data: pd.DataFrame = None
- self.fit_score = None
- self.name = name if name is not None else "default"
-
- def append_row(self, basep: np.ndarray | Tuple, **row):
- bp = basep[1]
- _keys, _values = zip(*row.items())
- # _keys = list(row.keys())
- # _values = list(row.values())
-
- if self.data is None:
- _idx = 0
- self.data = pd.DataFrame(
- {k: [v] for k, v in row.items()},
- index=pd.MultiIndex.from_tuples([(bp, _idx)]),
- columns=_keys,
- )
- return
-
- _idx = len(self.data.loc[(bp,), :]) if (bp,) in self.data.index else 0
- not_in_data = np.setdiff1d(list(row.keys()), self.data.columns.unique(0))
- self.data.loc[:, not_in_data] = np.nan
- self.data.loc[(bp, _idx), :] = row
- return
-
- @property
- def columns(self) -> np.ndarray:
- return self.data.columns.unique(0)
-
- @property
- def prevs(self):
- return np.sort(self.data.index.unique(0))
-
-
-class CompReport:
- def __init__(
- self,
- reports: List[EvaluationReport],
- name="default",
- train_prev=None,
- valid_prev=None,
- times=None,
- ):
- self._data = (
- pd.concat(
- [er.data for er in reports],
- keys=[er.name for er in reports],
- axis=1,
- )
- .swaplevel(0, 1, axis=1)
- .sort_index(axis=1, level=0, sort_remaining=False)
- .sort_index(axis=0, level=0)
- )
-
- self.fit_scores = {
- er.name: er.fit_score for er in reports if er.fit_score is not None
- }
- self.train_prev = train_prev
- self.valid_prev = valid_prev
- self.times = times
-
- @property
- def prevs(self) -> np.ndarray:
- return np.sort(self._data.index.unique(0))
-
- @property
- def np_prevs(self) -> np.ndarray:
- return np.around([(1.0 - p, p) for p in self.prevs], decimals=2)
-
- def data(self, metric: str = None, estimators: List[str] = None) -> pd.DataFrame:
- _metric = _get_metric(metric)
- _estimators = _get_estimators(estimators, self._data.columns.unique(1))
- f_data: pd.DataFrame = self._data.copy().loc[:, (_metric, _estimators)]
-
- if len(f_data.columns.unique(0)) == 1:
- f_data = f_data.droplevel(level=0, axis=1)
-
- return f_data
-
- def shift_data(
- self, metric: str = None, estimators: List[str] = None
- ) -> pd.DataFrame:
- shift_idx_0 = np.around(
- np.abs(
- self._data.index.get_level_values(0).to_numpy() - self.train_prev[1]
- ),
- decimals=2,
- )
-
- shift_idx_1 = np.empty(shape=shift_idx_0.shape, dtype=" pd.DataFrame:
- f_dict = self.data(metric=metric, estimators=estimators)
- return f_dict.groupby(level=0).mean()
-
- def stdev_by_prevs(
- self, metric: str = None, estimators: List[str] = None
- ) -> pd.DataFrame:
- f_dict = self.data(metric=metric, estimators=estimators)
- return f_dict.groupby(level=0).std()
-
- def table(self, metric: str = None, estimators: List[str] = None) -> pd.DataFrame:
- f_data = self.data(metric=metric, estimators=estimators)
- avg_p = f_data.groupby(level=0).mean()
- avg_p.loc["avg", :] = f_data.mean()
- return avg_p
-
- def get_plots(
- self, mode="delta", metric="acc", estimators=None, conf="default", stdev=False
- ) -> List[Tuple[str, Path]]:
- if mode == "delta":
- avg_data = self.avg_by_prevs(metric=metric, estimators=estimators)
- return plot.plot_delta(
- base_prevs=self.np_prevs,
- columns=avg_data.columns.to_numpy(),
- data=avg_data.T.to_numpy(),
- metric=metric,
- name=conf,
- train_prev=self.train_prev,
- )
- elif mode == "delta_stdev":
- avg_data = self.avg_by_prevs(metric=metric, estimators=estimators)
- st_data = self.stdev_by_prevs(metric=metric, estimators=estimators)
- return plot.plot_delta(
- base_prevs=self.np_prevs,
- columns=avg_data.columns.to_numpy(),
- data=avg_data.T.to_numpy(),
- metric=metric,
- name=conf,
- train_prev=self.train_prev,
- stdevs=st_data.T.to_numpy(),
- )
- elif mode == "diagonal":
- f_data = self.data(metric=metric + "_score", estimators=estimators)
- ref: pd.Series = f_data.loc[:, "ref"]
- f_data.drop(columns=["ref"], inplace=True)
- return plot.plot_diagonal(
- reference=ref.to_numpy(),
- columns=f_data.columns.to_numpy(),
- data=f_data.T.to_numpy(),
- metric=metric,
- name=conf,
- train_prev=self.train_prev,
- )
- elif mode == "shift":
- _shift_data = self.shift_data(metric=metric, estimators=estimators)
- shift_avg = _shift_data.groupby(level=0).mean()
- shift_counts = _shift_data.groupby(level=0).count()
- shift_prevs = np.around(
- [(1.0 - p, p) for p in np.sort(shift_avg.index.unique(0))],
- decimals=2,
- )
- return plot.plot_shift(
- shift_prevs=shift_prevs,
- columns=shift_avg.columns.to_numpy(),
- data=shift_avg.T.to_numpy(),
- metric=metric,
- name=conf,
- train_prev=self.train_prev,
- counts=shift_counts.T.to_numpy(),
- )
-
- def to_md(self, conf="default", metric="acc", estimators=None, stdev=False) -> str:
- res = f"## {int(np.around(self.train_prev, decimals=2)[1]*100)}% positives\n"
- res += fmt_line_md(f"train: {str(self.train_prev)}")
- res += fmt_line_md(f"validation: {str(self.valid_prev)}")
- for k, v in self.times.items():
- res += fmt_line_md(f"{k}: {v:.3f}s")
- res += "\n"
- res += self.table(metric=metric, estimators=estimators).to_html() + "\n\n"
-
- plot_modes = np.array(["delta", "diagonal", "shift"], dtype="object")
- if stdev:
- whd = np.where(plot_modes == "delta")[0]
- if len(whd) > 0:
- plot_modes = np.insert(plot_modes, whd + 1, "delta_stdev")
- for mode in plot_modes:
- op = self.get_plots(
- mode=mode,
- metric=metric,
- estimators=estimators,
- conf=conf,
- stdev=stdev,
- )
- res += f".as_posix()})\n"
-
- return res
-
-
-class DatasetReport:
- def __init__(self, name, crs=None):
- self.name = name
- self.crs: List[CompReport] = [] if crs is None else crs
-
- def data(self, metric: str = None, estimators: str = None) -> pd.DataFrame:
- def _cr_train_prev(cr: CompReport):
- return cr.train_prev[1]
-
- def _cr_data(cr: CompReport):
- return cr.data(metric, estimators)
-
- _crs_sorted = sorted(
- [(_cr_train_prev(cr), _cr_data(cr)) for cr in self.crs],
- key=lambda cr: len(cr[1].columns),
- reverse=True,
- )
- _crs_train, _crs_data = zip(*_crs_sorted)
-
- _data = pd.concat(_crs_data, axis=0, keys=np.around(_crs_train, decimals=2))
- _data = _data.sort_index(axis=0, level=0)
- return _data
-
- def shift_data(self, metric: str = None, estimators: str = None) -> pd.DataFrame:
- _shift_data: pd.DataFrame = pd.concat(
- sorted(
- [cr.shift_data(metric, estimators) for cr in self.crs],
- key=lambda d: len(d.columns),
- reverse=True,
- ),
- axis=0,
- )
-
- shift_idx_0 = _shift_data.index.get_level_values(0)
-
- shift_idx_1 = np.empty(shape=shift_idx_0.shape, dtype=" 0:
- a = np.insert(a, whb + 1, "pippo")
- print(a)
- print("-" * 100)
-
- dff: pd.DataFrame = df.loc[:, ("a",)]
- print(dff.to_dict(orient="list"))
- dff = dff.drop(columns=["v"])
- print(dff)
- s: pd.Series = dff.loc[:, "e"]
- print(s)
- print(s.to_numpy())
- print(type(s.to_numpy()))
- print("-" * 100)
-
- df3 = pd.concat([df, df], axis=0, keys=[0.5, 0.3]).sort_index(axis=0, level=0)
- print(df3)
- df3n = pd.concat([df, df], axis=0).sort_index(axis=0, level=0)
- print(df3n)
- df = df3
- print("-" * 100)
-
- print(df.groupby(level=1).mean(), df.groupby(level=1).count())
- print("-" * 100)
-
- print(df)
- for ls in df.T.to_numpy():
- print(ls)
- print("-" * 100)
-
-
-if __name__ == "__main__":
- __test()
+from pathlib import Path
+from typing import List, Tuple
+
+import numpy as np
+import pandas as pd
+
+from quacc import plot
+from quacc.environment import env
+from quacc.utils import fmt_line_md
+
+
+def _get_metric(metric: str):
+ return slice(None) if metric is None else metric
+
+
+def _get_estimators(estimators: List[str], cols: np.ndarray):
+ return slice(None) if estimators is None else cols[np.in1d(cols, estimators)]
+
+
+class EvaluationReport:
+ def __init__(self, name=None):
+ self.data: pd.DataFrame = None
+ self.fit_score = None
+ self.name = name if name is not None else "default"
+
+ def append_row(self, basep: np.ndarray | Tuple, **row):
+ bp = basep[1]
+ _keys, _values = zip(*row.items())
+ # _keys = list(row.keys())
+ # _values = list(row.values())
+
+ if self.data is None:
+ _idx = 0
+ self.data = pd.DataFrame(
+ {k: [v] for k, v in row.items()},
+ index=pd.MultiIndex.from_tuples([(bp, _idx)]),
+ columns=_keys,
+ )
+ return
+
+ _idx = len(self.data.loc[(bp,), :]) if (bp,) in self.data.index else 0
+ not_in_data = np.setdiff1d(list(row.keys()), self.data.columns.unique(0))
+ self.data.loc[:, not_in_data] = np.nan
+ self.data.loc[(bp, _idx), :] = row
+ return
+
+ @property
+ def columns(self) -> np.ndarray:
+ return self.data.columns.unique(0)
+
+ @property
+ def prevs(self):
+ return np.sort(self.data.index.unique(0))
+
+
+class CompReport:
+ def __init__(
+ self,
+ reports: List[EvaluationReport],
+ name="default",
+ train_prev=None,
+ valid_prev=None,
+ times=None,
+ ):
+ self._data = (
+ pd.concat(
+ [er.data for er in reports],
+ keys=[er.name for er in reports],
+ axis=1,
+ )
+ .swaplevel(0, 1, axis=1)
+ .sort_index(axis=1, level=0, sort_remaining=False)
+ .sort_index(axis=0, level=0)
+ )
+
+ self.fit_scores = {
+ er.name: er.fit_score for er in reports if er.fit_score is not None
+ }
+ self.train_prev = train_prev
+ self.valid_prev = valid_prev
+ self.times = times
+
+ @property
+ def prevs(self) -> np.ndarray:
+ return np.sort(self._data.index.unique(0))
+
+ @property
+ def np_prevs(self) -> np.ndarray:
+ return np.around([(1.0 - p, p) for p in self.prevs], decimals=2)
+
+ def data(self, metric: str = None, estimators: List[str] = None) -> pd.DataFrame:
+ _metric = _get_metric(metric)
+ _estimators = _get_estimators(estimators, self._data.columns.unique(1))
+ f_data: pd.DataFrame = self._data.copy().loc[:, (_metric, _estimators)]
+
+ if len(f_data.columns.unique(0)) == 1:
+ f_data = f_data.droplevel(level=0, axis=1)
+
+ return f_data
+
+ def shift_data(
+ self, metric: str = None, estimators: List[str] = None
+ ) -> pd.DataFrame:
+ shift_idx_0 = np.around(
+ np.abs(
+ self._data.index.get_level_values(0).to_numpy() - self.train_prev[1]
+ ),
+ decimals=2,
+ )
+
+ shift_idx_1 = np.empty(shape=shift_idx_0.shape, dtype=" pd.DataFrame:
+ f_dict = self.data(metric=metric, estimators=estimators)
+ return f_dict.groupby(level=0).mean()
+
+ def stdev_by_prevs(
+ self, metric: str = None, estimators: List[str] = None
+ ) -> pd.DataFrame:
+ f_dict = self.data(metric=metric, estimators=estimators)
+ return f_dict.groupby(level=0).std()
+
+ def table(self, metric: str = None, estimators: List[str] = None) -> pd.DataFrame:
+ f_data = self.data(metric=metric, estimators=estimators)
+ avg_p = f_data.groupby(level=0).mean()
+ avg_p.loc["avg", :] = f_data.mean()
+ return avg_p
+
+ def get_plots(
+ self, mode="delta", metric="acc", estimators=None, conf="default", stdev=False
+ ) -> List[Tuple[str, Path]]:
+ if mode == "delta":
+ avg_data = self.avg_by_prevs(metric=metric, estimators=estimators)
+ return plot.plot_delta(
+ base_prevs=self.np_prevs,
+ columns=avg_data.columns.to_numpy(),
+ data=avg_data.T.to_numpy(),
+ metric=metric,
+ name=conf,
+ train_prev=self.train_prev,
+ )
+ elif mode == "delta_stdev":
+ avg_data = self.avg_by_prevs(metric=metric, estimators=estimators)
+ st_data = self.stdev_by_prevs(metric=metric, estimators=estimators)
+ return plot.plot_delta(
+ base_prevs=self.np_prevs,
+ columns=avg_data.columns.to_numpy(),
+ data=avg_data.T.to_numpy(),
+ metric=metric,
+ name=conf,
+ train_prev=self.train_prev,
+ stdevs=st_data.T.to_numpy(),
+ )
+ elif mode == "diagonal":
+ f_data = self.data(metric=metric + "_score", estimators=estimators)
+ ref: pd.Series = f_data.loc[:, "ref"]
+ f_data.drop(columns=["ref"], inplace=True)
+ return plot.plot_diagonal(
+ reference=ref.to_numpy(),
+ columns=f_data.columns.to_numpy(),
+ data=f_data.T.to_numpy(),
+ metric=metric,
+ name=conf,
+ train_prev=self.train_prev,
+ )
+ elif mode == "shift":
+ _shift_data = self.shift_data(metric=metric, estimators=estimators)
+ shift_avg = _shift_data.groupby(level=0).mean()
+ shift_counts = _shift_data.groupby(level=0).count()
+ shift_prevs = np.around(
+ [(1.0 - p, p) for p in np.sort(shift_avg.index.unique(0))],
+ decimals=2,
+ )
+ return plot.plot_shift(
+ shift_prevs=shift_prevs,
+ columns=shift_avg.columns.to_numpy(),
+ data=shift_avg.T.to_numpy(),
+ metric=metric,
+ name=conf,
+ train_prev=self.train_prev,
+ counts=shift_counts.T.to_numpy(),
+ )
+
+ def to_md(self, conf="default", metric="acc", estimators=None, stdev=False) -> str:
+ res = f"## {int(np.around(self.train_prev, decimals=2)[1]*100)}% positives\n"
+ res += fmt_line_md(f"train: {str(self.train_prev)}")
+ res += fmt_line_md(f"validation: {str(self.valid_prev)}")
+ for k, v in self.times.items():
+ res += fmt_line_md(f"{k}: {v:.3f}s")
+ res += "\n"
+ res += self.table(metric=metric, estimators=estimators).to_html() + "\n\n"
+
+ plot_modes = np.array(["delta", "diagonal", "shift"], dtype="object")
+ if stdev:
+ whd = np.where(plot_modes == "delta")[0]
+ if len(whd) > 0:
+ plot_modes = np.insert(plot_modes, whd + 1, "delta_stdev")
+ for mode in plot_modes:
+ op = self.get_plots(
+ mode=mode,
+ metric=metric,
+ estimators=estimators,
+ conf=conf,
+ stdev=stdev,
+ )
+ res += f".as_posix()})\n"
+
+ return res
+
+
+class DatasetReport:
+ def __init__(self, name, crs=None):
+ self.name = name
+ self.crs: List[CompReport] = [] if crs is None else crs
+
+ def data(self, metric: str = None, estimators: str = None) -> pd.DataFrame:
+ def _cr_train_prev(cr: CompReport):
+ return cr.train_prev[1]
+
+ def _cr_data(cr: CompReport):
+ return cr.data(metric, estimators)
+
+ _crs_sorted = sorted(
+ [(_cr_train_prev(cr), _cr_data(cr)) for cr in self.crs],
+ key=lambda cr: len(cr[1].columns),
+ reverse=True,
+ )
+ _crs_train, _crs_data = zip(*_crs_sorted)
+
+ _data = pd.concat(_crs_data, axis=0, keys=np.around(_crs_train, decimals=2))
+ _data = _data.sort_index(axis=0, level=0)
+ return _data
+
+ def shift_data(self, metric: str = None, estimators: str = None) -> pd.DataFrame:
+ _shift_data: pd.DataFrame = pd.concat(
+ sorted(
+ [cr.shift_data(metric, estimators) for cr in self.crs],
+ key=lambda d: len(d.columns),
+ reverse=True,
+ ),
+ axis=0,
+ )
+
+ shift_idx_0 = _shift_data.index.get_level_values(0)
+
+ shift_idx_1 = np.empty(shape=shift_idx_0.shape, dtype=" 0:
+ a = np.insert(a, whb + 1, "pippo")
+ print(a)
+ print("-" * 100)
+
+ dff: pd.DataFrame = df.loc[:, ("a",)]
+ print(dff.to_dict(orient="list"))
+ dff = dff.drop(columns=["v"])
+ print(dff)
+ s: pd.Series = dff.loc[:, "e"]
+ print(s)
+ print(s.to_numpy())
+ print(type(s.to_numpy()))
+ print("-" * 100)
+
+ df3 = pd.concat([df, df], axis=0, keys=[0.5, 0.3]).sort_index(axis=0, level=0)
+ print(df3)
+ df3n = pd.concat([df, df], axis=0).sort_index(axis=0, level=0)
+ print(df3n)
+ df = df3
+ print("-" * 100)
+
+ print(df.groupby(level=1).mean(), df.groupby(level=1).count())
+ print("-" * 100)
+
+ print(df)
+ for ls in df.T.to_numpy():
+ print(ls)
+ print("-" * 100)
+
+
+if __name__ == "__main__":
+ __test()
diff --git a/quacc/evaluation/worker.py b/quacc/evaluation/worker.py
index 2ff93f6..e1d02b0 100644
--- a/quacc/evaluation/worker.py
+++ b/quacc/evaluation/worker.py
@@ -1,44 +1,44 @@
-import time
-from traceback import print_exception as traceback
-
-import quapy as qp
-from quapy.protocol import APP
-from sklearn.linear_model import LogisticRegression
-
-from quacc.logger import SubLogger
-
-
-def estimate_worker(_estimate, train, validation, test, _env=None, q=None):
- qp.environ["SAMPLE_SIZE"] = _env.SAMPLE_SIZE
- SubLogger.setup(q)
- log = SubLogger.logger()
-
- model = LogisticRegression()
-
- model.fit(*train.Xy)
- protocol = APP(
- test,
- n_prevalences=_env.PROTOCOL_N_PREVS,
- repeats=_env.PROTOCOL_REPEATS,
- return_type="labelled_collection",
- )
- start = time.time()
- try:
- result = _estimate(model, validation, protocol)
- except Exception as e:
- log.warning(f"Method {_estimate.__name__} failed. Exception: {e}")
- traceback(e)
- return {
- "name": _estimate.__name__,
- "result": None,
- "time": 0,
- }
-
- end = time.time()
- log.info(f"{_estimate.__name__} finished [took {end-start:.4f}s]")
-
- return {
- "name": _estimate.__name__,
- "result": result,
- "time": end - start,
- }
+import time
+from traceback import print_exception as traceback
+
+import quapy as qp
+from quapy.protocol import APP
+from sklearn.linear_model import LogisticRegression
+
+from quacc.logger import SubLogger
+
+
+def estimate_worker(_estimate, train, validation, test, _env=None, q=None):
+ qp.environ["SAMPLE_SIZE"] = _env.SAMPLE_SIZE
+ SubLogger.setup(q)
+ log = SubLogger.logger()
+
+ model = LogisticRegression()
+
+ model.fit(*train.Xy)
+ protocol = APP(
+ test,
+ n_prevalences=_env.PROTOCOL_N_PREVS,
+ repeats=_env.PROTOCOL_REPEATS,
+ return_type="labelled_collection",
+ )
+ start = time.time()
+ try:
+ result = _estimate(model, validation, protocol)
+ except Exception as e:
+ log.warning(f"Method {_estimate.__name__} failed. Exception: {e}")
+ traceback(e)
+ return {
+ "name": _estimate.__name__,
+ "result": None,
+ "time": 0,
+ }
+
+ end = time.time()
+ log.info(f"{_estimate.__name__} finished [took {end-start:.4f}s]")
+
+ return {
+ "name": _estimate.__name__,
+ "result": result,
+ "time": end - start,
+ }
diff --git a/quacc/logger.py b/quacc/logger.py
index 5725606..acf7eb1 100644
--- a/quacc/logger.py
+++ b/quacc/logger.py
@@ -1,136 +1,136 @@
-import logging
-import logging.handlers
-import multiprocessing
-import threading
-from pathlib import Path
-
-
-class Logger:
- __logger_file = "quacc.log"
- __logger_name = "queue_logger"
- __manager = None
- __queue = None
- __thread = None
- __setup = False
- __handlers = []
-
- @classmethod
- def __logger_listener(cls, q):
- while True:
- record = q.get()
- if record is None:
- break
- root = logging.getLogger("listener")
- root.handle(record)
-
- @classmethod
- def setup(cls):
- if cls.__setup:
- return
-
- # setup root
- root = logging.getLogger("listener")
- root.setLevel(logging.DEBUG)
- rh = logging.FileHandler(cls.__logger_file, mode="a")
- rh.setLevel(logging.DEBUG)
- root.addHandler(rh)
-
- # setup logger
- if cls.__manager is None:
- cls.__manager = multiprocessing.Manager()
-
- if cls.__queue is None:
- cls.__queue = cls.__manager.Queue()
-
- logger = logging.getLogger(cls.__logger_name)
- logger.setLevel(logging.DEBUG)
- qh = logging.handlers.QueueHandler(cls.__queue)
- qh.setLevel(logging.DEBUG)
- qh.setFormatter(
- logging.Formatter(
- fmt="%(asctime)s| %(levelname)-8s %(message)s",
- datefmt="%d/%m/%y %H:%M:%S",
- )
- )
- logger.addHandler(qh)
-
- # start listener
- cls.__thread = threading.Thread(
- target=cls.__logger_listener,
- args=(cls.__queue,),
- )
- cls.__thread.start()
-
- cls.__setup = True
-
- @classmethod
- def add_handler(cls, path: Path):
- root = logging.getLogger("listener")
- rh = logging.FileHandler(path, mode="a")
- rh.setLevel(logging.DEBUG)
- cls.__handlers.append(rh)
- root.addHandler(rh)
-
- @classmethod
- def clear_handlers(cls):
- root = logging.getLogger("listener")
- for h in cls.__handlers:
- root.removeHandler(h)
- cls.__handlers.clear()
-
- @classmethod
- def queue(cls):
- if not cls.__setup:
- cls.setup()
-
- return cls.__queue
-
- @classmethod
- def logger(cls):
- if not cls.__setup:
- cls.setup()
-
- return logging.getLogger(cls.__logger_name)
-
- @classmethod
- def close(cls):
- if cls.__setup and cls.__thread is not None:
- root = logging.getLogger("listener")
- root.info("-" * 100)
- cls.__queue.put(None)
- cls.__thread.join()
- # cls.__manager.close()
-
-
-class SubLogger:
- __queue = None
- __setup = False
-
- @classmethod
- def setup(cls, q):
- if cls.__setup:
- return
-
- cls.__queue = q
-
- # setup root
- root = logging.getLogger()
- root.setLevel(logging.DEBUG)
- rh = logging.handlers.QueueHandler(q)
- rh.setLevel(logging.DEBUG)
- rh.setFormatter(
- logging.Formatter(
- fmt="%(asctime)s| %(levelname)-12s%(message)s",
- datefmt="%d/%m/%y %H:%M:%S",
- )
- )
- root.addHandler(rh)
-
- cls.__setup = True
-
- @classmethod
- def logger(cls):
- if not cls.__setup:
- return None
-
- return logging.getLogger()
+import logging
+import logging.handlers
+import multiprocessing
+import threading
+from pathlib import Path
+
+
+class Logger:
+ __logger_file = "quacc.log"
+ __logger_name = "queue_logger"
+ __manager = None
+ __queue = None
+ __thread = None
+ __setup = False
+ __handlers = []
+
+ @classmethod
+ def __logger_listener(cls, q):
+ while True:
+ record = q.get()
+ if record is None:
+ break
+ root = logging.getLogger("listener")
+ root.handle(record)
+
+ @classmethod
+ def setup(cls):
+ if cls.__setup:
+ return
+
+ # setup root
+ root = logging.getLogger("listener")
+ root.setLevel(logging.DEBUG)
+ rh = logging.FileHandler(cls.__logger_file, mode="a")
+ rh.setLevel(logging.DEBUG)
+ root.addHandler(rh)
+
+ # setup logger
+ if cls.__manager is None:
+ cls.__manager = multiprocessing.Manager()
+
+ if cls.__queue is None:
+ cls.__queue = cls.__manager.Queue()
+
+ logger = logging.getLogger(cls.__logger_name)
+ logger.setLevel(logging.DEBUG)
+ qh = logging.handlers.QueueHandler(cls.__queue)
+ qh.setLevel(logging.DEBUG)
+ qh.setFormatter(
+ logging.Formatter(
+ fmt="%(asctime)s| %(levelname)-8s %(message)s",
+ datefmt="%d/%m/%y %H:%M:%S",
+ )
+ )
+ logger.addHandler(qh)
+
+ # start listener
+ cls.__thread = threading.Thread(
+ target=cls.__logger_listener,
+ args=(cls.__queue,),
+ )
+ cls.__thread.start()
+
+ cls.__setup = True
+
+ @classmethod
+ def add_handler(cls, path: Path):
+ root = logging.getLogger("listener")
+ rh = logging.FileHandler(path, mode="a")
+ rh.setLevel(logging.DEBUG)
+ cls.__handlers.append(rh)
+ root.addHandler(rh)
+
+ @classmethod
+ def clear_handlers(cls):
+ root = logging.getLogger("listener")
+ for h in cls.__handlers:
+ root.removeHandler(h)
+ cls.__handlers.clear()
+
+ @classmethod
+ def queue(cls):
+ if not cls.__setup:
+ cls.setup()
+
+ return cls.__queue
+
+ @classmethod
+ def logger(cls):
+ if not cls.__setup:
+ cls.setup()
+
+ return logging.getLogger(cls.__logger_name)
+
+ @classmethod
+ def close(cls):
+ if cls.__setup and cls.__thread is not None:
+ root = logging.getLogger("listener")
+ root.info("-" * 100)
+ cls.__queue.put(None)
+ cls.__thread.join()
+ # cls.__manager.close()
+
+
+class SubLogger:
+ __queue = None
+ __setup = False
+
+ @classmethod
+ def setup(cls, q):
+ if cls.__setup:
+ return
+
+ cls.__queue = q
+
+ # setup root
+ root = logging.getLogger()
+ root.setLevel(logging.DEBUG)
+ rh = logging.handlers.QueueHandler(q)
+ rh.setLevel(logging.DEBUG)
+ rh.setFormatter(
+ logging.Formatter(
+ fmt="%(asctime)s| %(levelname)-12s%(message)s",
+ datefmt="%d/%m/%y %H:%M:%S",
+ )
+ )
+ root.addHandler(rh)
+
+ cls.__setup = True
+
+ @classmethod
+ def logger(cls):
+ if not cls.__setup:
+ return None
+
+ return logging.getLogger()
diff --git a/quacc/main.py b/quacc/main.py
index eaf4067..d8863ee 100644
--- a/quacc/main.py
+++ b/quacc/main.py
@@ -1,75 +1,75 @@
-from sys import platform
-from traceback import print_exception as traceback
-
-import quacc.evaluation.comp as comp
-from quacc.dataset import Dataset
-from quacc.environment import env
-from quacc.logger import Logger
-from quacc.utils import create_dataser_dir
-
-CE = comp.CompEstimator()
-
-
-def toast():
- if platform == "win32":
- import win11toast
-
- win11toast.notify("Comp", "Completed Execution")
-
-
-def estimate_comparison():
- log = Logger.logger()
- for conf in env.get_confs():
- dataset = Dataset(
- env.DATASET_NAME,
- target=env.DATASET_TARGET,
- n_prevalences=env.DATASET_N_PREVS,
- prevs=env.DATASET_PREVS,
- )
- create_dataser_dir(dataset.name, update=env.DATASET_DIR_UPDATE)
- Logger.add_handler(env.OUT_DIR / f"{dataset.name}.log")
- try:
- dr = comp.evaluate_comparison(
- dataset,
- estimators=CE.name[env.COMP_ESTIMATORS],
- )
- except Exception as e:
- log.error(f"Evaluation over {dataset.name} failed. Exception: {e}")
- traceback(e)
- for plot_conf in env.get_plot_confs():
- for m in env.METRICS:
- output_path = env.OUT_DIR / f"{plot_conf}_{m}.md"
- try:
- _repr = dr.to_md(
- conf=plot_conf,
- metric=m,
- estimators=CE.name[env.PLOT_ESTIMATORS],
- stdev=env.PLOT_STDEV,
- )
- with open(output_path, "w") as f:
- f.write(_repr)
- except Exception as e:
- log.error(
- f"Failed while saving configuration {plot_conf} of {dataset.name}. Exception: {e}"
- )
- traceback(e)
- Logger.clear_handlers()
-
- # print(df.to_latex(float_format="{:.4f}".format))
- # print(utils.avg_group_report(df).to_latex(float_format="{:.4f}".format))
-
-
-def main():
- log = Logger.logger()
- try:
- estimate_comparison()
- except Exception as e:
- log.error(f"estimate comparison failed. Exceprion: {e}")
- traceback(e)
-
- toast()
- Logger.close()
-
-
-if __name__ == "__main__":
- main()
+from sys import platform
+from traceback import print_exception as traceback
+
+import quacc.evaluation.comp as comp
+from quacc.dataset import Dataset
+from quacc.environment import env
+from quacc.logger import Logger
+from quacc.utils import create_dataser_dir
+
+CE = comp.CompEstimator()
+
+
+def toast():
+ if platform == "win32":
+ import win11toast
+
+ win11toast.notify("Comp", "Completed Execution")
+
+
+def estimate_comparison():
+ log = Logger.logger()
+ for conf in env.get_confs():
+ dataset = Dataset(
+ env.DATASET_NAME,
+ target=env.DATASET_TARGET,
+ n_prevalences=env.DATASET_N_PREVS,
+ prevs=env.DATASET_PREVS,
+ )
+ create_dataser_dir(dataset.name, update=env.DATASET_DIR_UPDATE)
+ Logger.add_handler(env.OUT_DIR / f"{dataset.name}.log")
+ try:
+ dr = comp.evaluate_comparison(
+ dataset,
+ estimators=CE.name[env.COMP_ESTIMATORS],
+ )
+ except Exception as e:
+ log.error(f"Evaluation over {dataset.name} failed. Exception: {e}")
+ traceback(e)
+ for plot_conf in env.get_plot_confs():
+ for m in env.METRICS:
+ output_path = env.OUT_DIR / f"{plot_conf}_{m}.md"
+ try:
+ _repr = dr.to_md(
+ conf=plot_conf,
+ metric=m,
+ estimators=CE.name[env.PLOT_ESTIMATORS],
+ stdev=env.PLOT_STDEV,
+ )
+ with open(output_path, "w") as f:
+ f.write(_repr)
+ except Exception as e:
+ log.error(
+ f"Failed while saving configuration {plot_conf} of {dataset.name}. Exception: {e}"
+ )
+ traceback(e)
+ Logger.clear_handlers()
+
+ # print(df.to_latex(float_format="{:.4f}".format))
+ # print(utils.avg_group_report(df).to_latex(float_format="{:.4f}".format))
+
+
+def main():
+ log = Logger.logger()
+ try:
+ estimate_comparison()
+ except Exception as e:
+ log.error(f"estimate comparison failed. Exceprion: {e}")
+ traceback(e)
+
+ toast()
+ Logger.close()
+
+
+if __name__ == "__main__":
+ main()
diff --git a/quacc/main_test.py b/quacc/main_test.py
index 6e47891..f5b2009 100644
--- a/quacc/main_test.py
+++ b/quacc/main_test.py
@@ -1,120 +1,120 @@
-from copy import deepcopy
-from time import time
-
-import numpy as np
-import win11toast
-from quapy.method.aggregative import SLD
-from quapy.protocol import APP, UPP
-from sklearn.linear_model import LogisticRegression
-
-import quacc as qc
-from quacc.dataset import Dataset
-from quacc.error import acc
-from quacc.evaluation.baseline import ref
-from quacc.evaluation.method import mulmc_sld
-from quacc.evaluation.report import CompReport, EvaluationReport
-from quacc.method.base import MCAE, BinaryQuantifierAccuracyEstimator
-from quacc.method.model_selection import GridSearchAE
-
-
-def test_gs():
- d = Dataset(name="rcv1", target="CCAT", n_prevalences=1).get_raw()
-
- classifier = LogisticRegression()
- classifier.fit(*d.train.Xy)
-
- quantifier = SLD(LogisticRegression())
- # estimator = MultiClassAccuracyEstimator(classifier, quantifier)
- estimator = BinaryQuantifierAccuracyEstimator(classifier, quantifier)
-
- v_train, v_val = d.validation.split_stratified(0.6, random_state=0)
- gs_protocol = UPP(v_val, sample_size=1000, repeats=100)
- gs_estimator = GridSearchAE(
- model=deepcopy(estimator),
- param_grid={
- "q__classifier__C": np.logspace(-3, 3, 7),
- "q__classifier__class_weight": [None, "balanced"],
- "q__recalib": [None, "bcts", "ts"],
- },
- refit=False,
- protocol=gs_protocol,
- verbose=True,
- ).fit(v_train)
-
- estimator.fit(d.validation)
-
- tstart = time()
- erb, ergs = EvaluationReport("base"), EvaluationReport("gs")
- protocol = APP(
- d.test,
- sample_size=1000,
- n_prevalences=21,
- repeats=100,
- return_type="labelled_collection",
- )
- for sample in protocol():
- e_sample = gs_estimator.extend(sample)
- estim_prev_b = estimator.estimate(e_sample.X, ext=True)
- estim_prev_gs = gs_estimator.estimate(e_sample.X, ext=True)
- erb.append_row(
- sample.prevalence(),
- acc=abs(acc(e_sample.prevalence()) - acc(estim_prev_b)),
- )
- ergs.append_row(
- sample.prevalence(),
- acc=abs(acc(e_sample.prevalence()) - acc(estim_prev_gs)),
- )
-
- cr = CompReport(
- [erb, ergs],
- "test",
- train_prev=d.train_prev,
- valid_prev=d.validation_prev,
- )
-
- print(cr.table())
- print(f"[took {time() - tstart:.3f}s]")
- win11toast.notify("Test", "completed")
-
-
-def test_mc():
- d = Dataset(name="rcv1", target="CCAT", prevs=[0.9]).get()[0]
- classifier = LogisticRegression().fit(*d.train.Xy)
- protocol = APP(
- d.test,
- sample_size=1000,
- repeats=100,
- n_prevalences=21,
- return_type="labelled_collection",
- )
-
- ref_er = ref(classifier, d.validation, protocol)
- mulmc_er = mulmc_sld(classifier, d.validation, protocol)
-
- cr = CompReport(
- [mulmc_er, ref_er],
- name="test_mc",
- train_prev=d.train_prev,
- valid_prev=d.validation_prev,
- )
-
- with open("test_mc.md", "w") as f:
- f.write(cr.data().to_markdown())
-
-
-def test_et():
- d = Dataset(name="imdb", prevs=[0.5]).get()[0]
- classifier = LogisticRegression().fit(*d.train.Xy)
- estimator = MCAE(
- classifier,
- SLD(LogisticRegression(), exact_train_prev=False),
- confidence="max_conf",
- ).fit(d.validation)
- e_test = estimator.extend(d.test)
- ep = estimator.estimate(e_test.X, ext=True)
- print(f"{qc.error.acc(ep) = }")
- print(f"{qc.error.acc(e_test.prevalence()) = }")
-
-
-if __name__ == "__main__":
- test_et()
+from copy import deepcopy
+from time import time
+
+import numpy as np
+import win11toast
+from quapy.method.aggregative import SLD
+from quapy.protocol import APP, UPP
+from sklearn.linear_model import LogisticRegression
+
+import quacc as qc
+from quacc.dataset import Dataset
+from quacc.error import acc
+from quacc.evaluation.baseline import ref
+from quacc.evaluation.method import mulmc_sld
+from quacc.evaluation.report import CompReport, EvaluationReport
+from quacc.method.base import MCAE, BinaryQuantifierAccuracyEstimator
+from quacc.method.model_selection import GridSearchAE
+
+
+def test_gs():
+ d = Dataset(name="rcv1", target="CCAT", n_prevalences=1).get_raw()
+
+ classifier = LogisticRegression()
+ classifier.fit(*d.train.Xy)
+
+ quantifier = SLD(LogisticRegression())
+ # estimator = MultiClassAccuracyEstimator(classifier, quantifier)
+ estimator = BinaryQuantifierAccuracyEstimator(classifier, quantifier)
+
+ v_train, v_val = d.validation.split_stratified(0.6, random_state=0)
+ gs_protocol = UPP(v_val, sample_size=1000, repeats=100)
+ gs_estimator = GridSearchAE(
+ model=deepcopy(estimator),
+ param_grid={
+ "q__classifier__C": np.logspace(-3, 3, 7),
+ "q__classifier__class_weight": [None, "balanced"],
+ "q__recalib": [None, "bcts", "ts"],
+ },
+ refit=False,
+ protocol=gs_protocol,
+ verbose=True,
+ ).fit(v_train)
+
+ estimator.fit(d.validation)
+
+ tstart = time()
+ erb, ergs = EvaluationReport("base"), EvaluationReport("gs")
+ protocol = APP(
+ d.test,
+ sample_size=1000,
+ n_prevalences=21,
+ repeats=100,
+ return_type="labelled_collection",
+ )
+ for sample in protocol():
+ e_sample = gs_estimator.extend(sample)
+ estim_prev_b = estimator.estimate(e_sample.X, ext=True)
+ estim_prev_gs = gs_estimator.estimate(e_sample.X, ext=True)
+ erb.append_row(
+ sample.prevalence(),
+ acc=abs(acc(e_sample.prevalence()) - acc(estim_prev_b)),
+ )
+ ergs.append_row(
+ sample.prevalence(),
+ acc=abs(acc(e_sample.prevalence()) - acc(estim_prev_gs)),
+ )
+
+ cr = CompReport(
+ [erb, ergs],
+ "test",
+ train_prev=d.train_prev,
+ valid_prev=d.validation_prev,
+ )
+
+ print(cr.table())
+ print(f"[took {time() - tstart:.3f}s]")
+ win11toast.notify("Test", "completed")
+
+
+def test_mc():
+ d = Dataset(name="rcv1", target="CCAT", prevs=[0.9]).get()[0]
+ classifier = LogisticRegression().fit(*d.train.Xy)
+ protocol = APP(
+ d.test,
+ sample_size=1000,
+ repeats=100,
+ n_prevalences=21,
+ return_type="labelled_collection",
+ )
+
+ ref_er = ref(classifier, d.validation, protocol)
+ mulmc_er = mulmc_sld(classifier, d.validation, protocol)
+
+ cr = CompReport(
+ [mulmc_er, ref_er],
+ name="test_mc",
+ train_prev=d.train_prev,
+ valid_prev=d.validation_prev,
+ )
+
+ with open("test_mc.md", "w") as f:
+ f.write(cr.data().to_markdown())
+
+
+def test_et():
+ d = Dataset(name="imdb", prevs=[0.5]).get()[0]
+ classifier = LogisticRegression().fit(*d.train.Xy)
+ estimator = MCAE(
+ classifier,
+ SLD(LogisticRegression(), exact_train_prev=False),
+ confidence="max_conf",
+ ).fit(d.validation)
+ e_test = estimator.extend(d.test)
+ ep = estimator.estimate(e_test.X, ext=True)
+ print(f"{qc.error.acc(ep) = }")
+ print(f"{qc.error.acc(e_test.prevalence()) = }")
+
+
+if __name__ == "__main__":
+ test_et()
diff --git a/quacc/method/base.py b/quacc/method/base.py
index 670abb7..89ed701 100644
--- a/quacc/method/base.py
+++ b/quacc/method/base.py
@@ -1,177 +1,177 @@
-import math
-from abc import abstractmethod
-from copy import deepcopy
-from typing import List
-
-import numpy as np
-from quapy.data import LabelledCollection
-from quapy.method.aggregative import BaseQuantifier
-from scipy.sparse import csr_matrix
-from sklearn.base import BaseEstimator
-
-from quacc.data import ExtendedCollection
-
-
-class BaseAccuracyEstimator(BaseQuantifier):
- def __init__(
- self,
- classifier: BaseEstimator,
- quantifier: BaseQuantifier,
- confidence=None,
- ):
- self.__check_classifier(classifier)
- self.quantifier = quantifier
- self.confidence = confidence
-
- def __check_classifier(self, classifier):
- if not hasattr(classifier, "predict_proba"):
- raise ValueError(
- f"Passed classifier {classifier.__class__.__name__} cannot predict probabilities."
- )
- self.classifier = classifier
-
- def __get_confidence(self):
- def max_conf(probas):
- _mc = np.max(probas, axis=-1)
- _min = 1.0 / probas.shape[1]
- _norm_mc = (_mc - _min) / (1.0 - _min)
- return _norm_mc
-
- def entropy(probas):
- _ent = np.sum(np.multiply(probas, np.log(probas + 1e-20)), axis=1)
- return _ent
-
- if self.confidence is None:
- return None
-
- __confs = {
- "max_conf": max_conf,
- "entropy": entropy,
- }
- return __confs.get(self.confidence, None)
-
- def __get_ext(self, pred_proba):
- _ext = pred_proba
- _f_conf = self.__get_confidence()
- if _f_conf is not None:
- _confs = _f_conf(pred_proba).reshape((len(pred_proba), 1))
- _ext = np.concatenate((_confs, pred_proba), axis=1)
-
- return _ext
-
- def extend(self, coll: LabelledCollection, pred_proba=None) -> ExtendedCollection:
- if pred_proba is None:
- pred_proba = self.classifier.predict_proba(coll.X)
-
- _ext = self.__get_ext(pred_proba)
- return ExtendedCollection.extend_collection(coll, pred_proba=_ext)
-
- def _extend_instances(self, instances: np.ndarray | csr_matrix, pred_proba=None):
- if pred_proba is None:
- pred_proba = self.classifier.predict_proba(instances)
-
- _ext = self.__get_ext(pred_proba)
- return ExtendedCollection.extend_instances(instances, _ext)
-
- @abstractmethod
- def fit(self, train: LabelledCollection | ExtendedCollection):
- ...
-
- @abstractmethod
- def estimate(self, instances, ext=False) -> np.ndarray:
- ...
-
-
-class MultiClassAccuracyEstimator(BaseAccuracyEstimator):
- def __init__(
- self,
- classifier: BaseEstimator,
- quantifier: BaseQuantifier,
- confidence: str = None,
- ):
- super().__init__(
- classifier=classifier,
- quantifier=quantifier,
- confidence=confidence,
- )
- self.e_train = None
-
- def fit(self, train: LabelledCollection):
- self.e_train = self.extend(train)
-
- self.quantifier.fit(self.e_train)
-
- return self
-
- def estimate(self, instances, ext=False) -> np.ndarray:
- e_inst = instances if ext else self._extend_instances(instances)
-
- estim_prev = self.quantifier.quantify(e_inst)
- return self._check_prevalence_classes(estim_prev, self.quantifier.classes_)
-
- def _check_prevalence_classes(self, estim_prev, estim_classes) -> np.ndarray:
- true_classes = self.e_train.classes_
- for _cls in true_classes:
- if _cls not in estim_classes:
- estim_prev = np.insert(estim_prev, _cls, [0.0], axis=0)
- return estim_prev
-
-
-class BinaryQuantifierAccuracyEstimator(BaseAccuracyEstimator):
- def __init__(
- self,
- classifier: BaseEstimator,
- quantifier: BaseAccuracyEstimator,
- confidence: str = None,
- ):
- super().__init__(
- classifier=classifier,
- quantifier=quantifier,
- confidence=confidence,
- )
- self.quantifiers = []
- self.e_trains = []
-
- def fit(self, train: LabelledCollection | ExtendedCollection):
- self.e_train = self.extend(train)
-
- self.n_classes = self.e_train.n_classes
- self.e_trains = self.e_train.split_by_pred()
-
- self.quantifiers = []
- for train in self.e_trains:
- quant = deepcopy(self.quantifier)
- quant.fit(train)
- self.quantifiers.append(quant)
-
- return self
-
- def estimate(self, instances, ext=False):
- # TODO: test
- e_inst = instances if ext else self._extend_instances(instances)
-
- _ncl = int(math.sqrt(self.n_classes))
- s_inst, norms = ExtendedCollection.split_inst_by_pred(_ncl, e_inst)
- estim_prevs = self._quantify_helper(s_inst, norms)
-
- estim_prev = np.array([prev_row for prev_row in zip(*estim_prevs)]).flatten()
- return estim_prev
-
- def _quantify_helper(
- self,
- s_inst: List[np.ndarray | csr_matrix],
- norms: List[float],
- ):
- estim_prevs = []
- for quant, inst, norm in zip(self.quantifiers, s_inst, norms):
- if inst.shape[0] > 0:
- estim_prevs.append(quant.quantify(inst) * norm)
- else:
- estim_prevs.append(np.asarray([0.0, 0.0]))
-
- return estim_prevs
-
-
-BAE = BaseAccuracyEstimator
-MCAE = MultiClassAccuracyEstimator
-BQAE = BinaryQuantifierAccuracyEstimator
+import math
+from abc import abstractmethod
+from copy import deepcopy
+from typing import List
+
+import numpy as np
+from quapy.data import LabelledCollection
+from quapy.method.aggregative import BaseQuantifier
+from scipy.sparse import csr_matrix
+from sklearn.base import BaseEstimator
+
+from quacc.data import ExtendedCollection
+
+
+class BaseAccuracyEstimator(BaseQuantifier):
+ def __init__(
+ self,
+ classifier: BaseEstimator,
+ quantifier: BaseQuantifier,
+ confidence=None,
+ ):
+ self.__check_classifier(classifier)
+ self.quantifier = quantifier
+ self.confidence = confidence
+
+ def __check_classifier(self, classifier):
+ if not hasattr(classifier, "predict_proba"):
+ raise ValueError(
+ f"Passed classifier {classifier.__class__.__name__} cannot predict probabilities."
+ )
+ self.classifier = classifier
+
+ def __get_confidence(self):
+ def max_conf(probas):
+ _mc = np.max(probas, axis=-1)
+ _min = 1.0 / probas.shape[1]
+ _norm_mc = (_mc - _min) / (1.0 - _min)
+ return _norm_mc
+
+ def entropy(probas):
+ _ent = np.sum(np.multiply(probas, np.log(probas + 1e-20)), axis=1)
+ return _ent
+
+ if self.confidence is None:
+ return None
+
+ __confs = {
+ "max_conf": max_conf,
+ "entropy": entropy,
+ }
+ return __confs.get(self.confidence, None)
+
+ def __get_ext(self, pred_proba):
+ _ext = pred_proba
+ _f_conf = self.__get_confidence()
+ if _f_conf is not None:
+ _confs = _f_conf(pred_proba).reshape((len(pred_proba), 1))
+ _ext = np.concatenate((_confs, pred_proba), axis=1)
+
+ return _ext
+
+ def extend(self, coll: LabelledCollection, pred_proba=None) -> ExtendedCollection:
+ if pred_proba is None:
+ pred_proba = self.classifier.predict_proba(coll.X)
+
+ _ext = self.__get_ext(pred_proba)
+ return ExtendedCollection.extend_collection(coll, pred_proba=_ext)
+
+ def _extend_instances(self, instances: np.ndarray | csr_matrix, pred_proba=None):
+ if pred_proba is None:
+ pred_proba = self.classifier.predict_proba(instances)
+
+ _ext = self.__get_ext(pred_proba)
+ return ExtendedCollection.extend_instances(instances, _ext)
+
+ @abstractmethod
+ def fit(self, train: LabelledCollection | ExtendedCollection):
+ ...
+
+ @abstractmethod
+ def estimate(self, instances, ext=False) -> np.ndarray:
+ ...
+
+
+class MultiClassAccuracyEstimator(BaseAccuracyEstimator):
+ def __init__(
+ self,
+ classifier: BaseEstimator,
+ quantifier: BaseQuantifier,
+ confidence: str = None,
+ ):
+ super().__init__(
+ classifier=classifier,
+ quantifier=quantifier,
+ confidence=confidence,
+ )
+ self.e_train = None
+
+ def fit(self, train: LabelledCollection):
+ self.e_train = self.extend(train)
+
+ self.quantifier.fit(self.e_train)
+
+ return self
+
+ def estimate(self, instances, ext=False) -> np.ndarray:
+ e_inst = instances if ext else self._extend_instances(instances)
+
+ estim_prev = self.quantifier.quantify(e_inst)
+ return self._check_prevalence_classes(estim_prev, self.quantifier.classes_)
+
+ def _check_prevalence_classes(self, estim_prev, estim_classes) -> np.ndarray:
+ true_classes = self.e_train.classes_
+ for _cls in true_classes:
+ if _cls not in estim_classes:
+ estim_prev = np.insert(estim_prev, _cls, [0.0], axis=0)
+ return estim_prev
+
+
+class BinaryQuantifierAccuracyEstimator(BaseAccuracyEstimator):
+ def __init__(
+ self,
+ classifier: BaseEstimator,
+ quantifier: BaseAccuracyEstimator,
+ confidence: str = None,
+ ):
+ super().__init__(
+ classifier=classifier,
+ quantifier=quantifier,
+ confidence=confidence,
+ )
+ self.quantifiers = []
+ self.e_trains = []
+
+ def fit(self, train: LabelledCollection | ExtendedCollection):
+ self.e_train = self.extend(train)
+
+ self.n_classes = self.e_train.n_classes
+ self.e_trains = self.e_train.split_by_pred()
+
+ self.quantifiers = []
+ for train in self.e_trains:
+ quant = deepcopy(self.quantifier)
+ quant.fit(train)
+ self.quantifiers.append(quant)
+
+ return self
+
+ def estimate(self, instances, ext=False):
+ # TODO: test
+ e_inst = instances if ext else self._extend_instances(instances)
+
+ _ncl = int(math.sqrt(self.n_classes))
+ s_inst, norms = ExtendedCollection.split_inst_by_pred(_ncl, e_inst)
+ estim_prevs = self._quantify_helper(s_inst, norms)
+
+ estim_prev = np.array([prev_row for prev_row in zip(*estim_prevs)]).flatten()
+ return estim_prev
+
+ def _quantify_helper(
+ self,
+ s_inst: List[np.ndarray | csr_matrix],
+ norms: List[float],
+ ):
+ estim_prevs = []
+ for quant, inst, norm in zip(self.quantifiers, s_inst, norms):
+ if inst.shape[0] > 0:
+ estim_prevs.append(quant.quantify(inst) * norm)
+ else:
+ estim_prevs.append(np.asarray([0.0, 0.0]))
+
+ return estim_prevs
+
+
+BAE = BaseAccuracyEstimator
+MCAE = MultiClassAccuracyEstimator
+BQAE = BinaryQuantifierAccuracyEstimator
diff --git a/quacc/method/model_selection.py b/quacc/method/model_selection.py
index ebc2fb8..4e4df34 100644
--- a/quacc/method/model_selection.py
+++ b/quacc/method/model_selection.py
@@ -1,307 +1,307 @@
-import itertools
-from copy import deepcopy
-from time import time
-from typing import Callable, Union
-import numpy as np
-
-import quapy as qp
-from quapy.data import LabelledCollection
-from quapy.model_selection import GridSearchQ
-from quapy.protocol import UPP, AbstractProtocol, OnLabelledCollectionProtocol
-from sklearn.base import BaseEstimator
-
-import quacc as qc
-import quacc.error
-from quacc.data import ExtendedCollection
-from quacc.evaluation import evaluate
-from quacc.logger import SubLogger
-from quacc.method.base import (
- BaseAccuracyEstimator,
- BinaryQuantifierAccuracyEstimator,
- MultiClassAccuracyEstimator,
-)
-
-
-class GridSearchAE(BaseAccuracyEstimator):
- def __init__(
- self,
- model: BaseAccuracyEstimator,
- param_grid: dict,
- protocol: AbstractProtocol,
- error: Union[Callable, str] = qc.error.maccd,
- refit=True,
- # timeout=-1,
- # n_jobs=None,
- verbose=False,
- ):
- self.model = model
- self.param_grid = self.__normalize_params(param_grid)
- self.protocol = protocol
- self.refit = refit
- # self.timeout = timeout
- # self.n_jobs = qp._get_njobs(n_jobs)
- self.verbose = verbose
- self.__check_error(error)
- assert isinstance(protocol, AbstractProtocol), "unknown protocol"
-
- def _sout(self, msg):
- if self.verbose:
- print(f"[{self.__class__.__name__}]: {msg}")
-
- def __normalize_params(self, params):
- __remap = {}
- for key in params.keys():
- k, delim, sub_key = key.partition("__")
- if delim and k == "q":
- __remap[key] = f"quantifier__{sub_key}"
-
- return {(__remap[k] if k in __remap else k): v for k, v in params.items()}
-
- def __check_error(self, error):
- if error in qc.error.ACCURACY_ERROR:
- self.error = error
- elif isinstance(error, str):
- self.error = qc.error.from_name(error)
- elif hasattr(error, "__call__"):
- self.error = error
- else:
- raise ValueError(
- f"unexpected error type; must either be a callable function or a str representing\n"
- f"the name of an error function in {qc.error.ACCURACY_ERROR_NAMES}"
- )
-
- def fit(self, training: LabelledCollection):
- """Learning routine. Fits methods with all combinations of hyperparameters and selects the one minimizing
- the error metric.
-
- :param training: the training set on which to optimize the hyperparameters
- :return: self
- """
- params_keys = list(self.param_grid.keys())
- params_values = list(self.param_grid.values())
-
- protocol = self.protocol
-
- self.param_scores_ = {}
- self.best_score_ = None
-
- tinit = time()
-
- hyper = [
- dict(zip(params_keys, val)) for val in itertools.product(*params_values)
- ]
-
- # self._sout(f"starting model selection with {self.n_jobs =}")
- self._sout("starting model selection")
-
- scores = [self.__params_eval(params, training) for params in hyper]
-
- for params, score, model in scores:
- if score is not None:
- if self.best_score_ is None or score < self.best_score_:
- self.best_score_ = score
- self.best_params_ = params
- self.best_model_ = model
- self.param_scores_[str(params)] = score
- else:
- self.param_scores_[str(params)] = "timeout"
-
- tend = time() - tinit
-
- if self.best_score_ is None:
- raise TimeoutError("no combination of hyperparameters seem to work")
-
- self._sout(
- f"optimization finished: best params {self.best_params_} (score={self.best_score_:.5f}) "
- f"[took {tend:.4f}s]"
- )
- log = SubLogger.logger()
- log.debug(
- f"[{self.model.__class__.__name__}] "
- f"optimization finished: best params {self.best_params_} (score={self.best_score_:.5f}) "
- f"[took {tend:.4f}s]"
- )
-
- if self.refit:
- if isinstance(protocol, OnLabelledCollectionProtocol):
- self._sout("refitting on the whole development set")
- self.best_model_.fit(training + protocol.get_labelled_collection())
- else:
- raise RuntimeWarning(
- f'"refit" was requested, but the protocol does not '
- f"implement the {OnLabelledCollectionProtocol.__name__} interface"
- )
-
- return self
-
- def __params_eval(self, params, training):
- protocol = self.protocol
- error = self.error
-
- # if self.timeout > 0:
-
- # def handler(signum, frame):
- # raise TimeoutError()
-
- # signal.signal(signal.SIGALRM, handler)
-
- tinit = time()
-
- # if self.timeout > 0:
- # signal.alarm(self.timeout)
-
- try:
- model = deepcopy(self.model)
- # overrides default parameters with the parameters being explored at this iteration
- model.set_params(**params)
- # print({k: v for k, v in model.get_params().items() if k in params})
- model.fit(training)
- score = evaluate(model, protocol=protocol, error_metric=error)
-
- ttime = time() - tinit
- self._sout(
- f"hyperparams={params}\t got score {score:.5f} [took {ttime:.4f}s]"
- )
-
- # if self.timeout > 0:
- # signal.alarm(0)
- # except TimeoutError:
- # self._sout(f"timeout ({self.timeout}s) reached for config {params}")
- # score = None
- except ValueError as e:
- self._sout(f"the combination of hyperparameters {params} is invalid")
- raise e
- except Exception as e:
- self._sout(f"something went wrong for config {params}; skipping:")
- self._sout(f"\tException: {e}")
- score = None
-
- return params, score, model
-
- def extend(self, coll: LabelledCollection, pred_proba=None) -> ExtendedCollection:
- assert hasattr(self, "best_model_"), "quantify called before fit"
- return self.best_model().extend(coll, pred_proba=pred_proba)
-
- def estimate(self, instances, ext=False):
- """Estimate class prevalence values using the best model found after calling the :meth:`fit` method.
-
- :param instances: sample contanining the instances
- :return: a ndarray of shape `(n_classes)` with class prevalence estimates as according to the best model found
- by the model selection process.
- """
-
- assert hasattr(self, "best_model_"), "estimate called before fit"
- return self.best_model().estimate(instances, ext=ext)
-
- def set_params(self, **parameters):
- """Sets the hyper-parameters to explore.
-
- :param parameters: a dictionary with keys the parameter names and values the list of values to explore
- """
- self.param_grid = parameters
-
- def get_params(self, deep=True):
- """Returns the dictionary of hyper-parameters to explore (`param_grid`)
-
- :param deep: Unused
- :return: the dictionary `param_grid`
- """
- return self.param_grid
-
- def best_model(self):
- """
- Returns the best model found after calling the :meth:`fit` method, i.e., the one trained on the combination
- of hyper-parameters that minimized the error function.
-
- :return: a trained quantifier
- """
- if hasattr(self, "best_model_"):
- return self.best_model_
- raise ValueError("best_model called before fit")
-
-
-
-class MCAEgsq(MultiClassAccuracyEstimator):
- def __init__(
- self,
- classifier: BaseEstimator,
- quantifier: BaseAccuracyEstimator,
- param_grid: dict,
- error: Union[Callable, str] = qp.error.mae,
- refit=True,
- timeout=-1,
- n_jobs=None,
- verbose=False,
- ):
- self.param_grid = param_grid
- self.refit = refit
- self.timeout = timeout
- self.n_jobs = n_jobs
- self.verbose = verbose
- self.error = error
- super().__init__(classifier, quantifier)
-
- def fit(self, train: LabelledCollection):
- self.e_train = self.extend(train)
- t_train, t_val = self.e_train.split_stratified(0.6, random_state=0)
- self.quantifier = GridSearchQ(
- deepcopy(self.quantifier),
- param_grid=self.param_grid,
- protocol=UPP(t_val, repeats=100),
- error=self.error,
- refit=self.refit,
- timeout=self.timeout,
- n_jobs=self.n_jobs,
- verbose=self.verbose,
- ).fit(self.e_train)
-
- return self
-
- def estimate(self, instances, ext=False) -> np.ndarray:
- e_inst = instances if ext else self._extend_instances(instances)
- estim_prev = self.quantifier.quantify(e_inst)
- return self._check_prevalence_classes(estim_prev, self.quantifier.best_model().classes_)
-
-
-class BQAEgsq(BinaryQuantifierAccuracyEstimator):
- def __init__(
- self,
- classifier: BaseEstimator,
- quantifier: BaseAccuracyEstimator,
- param_grid: dict,
- error: Union[Callable, str] = qp.error.mae,
- refit=True,
- timeout=-1,
- n_jobs=None,
- verbose=False,
- ):
- self.param_grid = param_grid
- self.refit = refit
- self.timeout = timeout
- self.n_jobs = n_jobs
- self.verbose = verbose
- self.error = error
- super().__init__(classifier=classifier, quantifier=quantifier)
-
- def fit(self, train: LabelledCollection):
- self.e_train = self.extend(train)
-
- self.n_classes = self.e_train.n_classes
- self.e_trains = self.e_train.split_by_pred()
-
- self.quantifiers = []
- for e_train in self.e_trains:
- t_train, t_val = e_train.split_stratified(0.6, random_state=0)
- quantifier = GridSearchQ(
- model=deepcopy(self.quantifier),
- param_grid=self.param_grid,
- protocol=UPP(t_val, repeats=100),
- error=self.error,
- refit=self.refit,
- timeout=self.timeout,
- n_jobs=self.n_jobs,
- verbose=self.verbose,
- ).fit(t_train)
- self.quantifiers.append(quantifier)
-
- return self
+import itertools
+from copy import deepcopy
+from time import time
+from typing import Callable, Union
+import numpy as np
+
+import quapy as qp
+from quapy.data import LabelledCollection
+from quapy.model_selection import GridSearchQ
+from quapy.protocol import UPP, AbstractProtocol, OnLabelledCollectionProtocol
+from sklearn.base import BaseEstimator
+
+import quacc as qc
+import quacc.error
+from quacc.data import ExtendedCollection
+from quacc.evaluation import evaluate
+from quacc.logger import SubLogger
+from quacc.method.base import (
+ BaseAccuracyEstimator,
+ BinaryQuantifierAccuracyEstimator,
+ MultiClassAccuracyEstimator,
+)
+
+
+class GridSearchAE(BaseAccuracyEstimator):
+ def __init__(
+ self,
+ model: BaseAccuracyEstimator,
+ param_grid: dict,
+ protocol: AbstractProtocol,
+ error: Union[Callable, str] = qc.error.maccd,
+ refit=True,
+ # timeout=-1,
+ # n_jobs=None,
+ verbose=False,
+ ):
+ self.model = model
+ self.param_grid = self.__normalize_params(param_grid)
+ self.protocol = protocol
+ self.refit = refit
+ # self.timeout = timeout
+ # self.n_jobs = qp._get_njobs(n_jobs)
+ self.verbose = verbose
+ self.__check_error(error)
+ assert isinstance(protocol, AbstractProtocol), "unknown protocol"
+
+ def _sout(self, msg):
+ if self.verbose:
+ print(f"[{self.__class__.__name__}]: {msg}")
+
+ def __normalize_params(self, params):
+ __remap = {}
+ for key in params.keys():
+ k, delim, sub_key = key.partition("__")
+ if delim and k == "q":
+ __remap[key] = f"quantifier__{sub_key}"
+
+ return {(__remap[k] if k in __remap else k): v for k, v in params.items()}
+
+ def __check_error(self, error):
+ if error in qc.error.ACCURACY_ERROR:
+ self.error = error
+ elif isinstance(error, str):
+ self.error = qc.error.from_name(error)
+ elif hasattr(error, "__call__"):
+ self.error = error
+ else:
+ raise ValueError(
+ f"unexpected error type; must either be a callable function or a str representing\n"
+ f"the name of an error function in {qc.error.ACCURACY_ERROR_NAMES}"
+ )
+
+ def fit(self, training: LabelledCollection):
+ """Learning routine. Fits methods with all combinations of hyperparameters and selects the one minimizing
+ the error metric.
+
+ :param training: the training set on which to optimize the hyperparameters
+ :return: self
+ """
+ params_keys = list(self.param_grid.keys())
+ params_values = list(self.param_grid.values())
+
+ protocol = self.protocol
+
+ self.param_scores_ = {}
+ self.best_score_ = None
+
+ tinit = time()
+
+ hyper = [
+ dict(zip(params_keys, val)) for val in itertools.product(*params_values)
+ ]
+
+ # self._sout(f"starting model selection with {self.n_jobs =}")
+ self._sout("starting model selection")
+
+ scores = [self.__params_eval(params, training) for params in hyper]
+
+ for params, score, model in scores:
+ if score is not None:
+ if self.best_score_ is None or score < self.best_score_:
+ self.best_score_ = score
+ self.best_params_ = params
+ self.best_model_ = model
+ self.param_scores_[str(params)] = score
+ else:
+ self.param_scores_[str(params)] = "timeout"
+
+ tend = time() - tinit
+
+ if self.best_score_ is None:
+ raise TimeoutError("no combination of hyperparameters seem to work")
+
+ self._sout(
+ f"optimization finished: best params {self.best_params_} (score={self.best_score_:.5f}) "
+ f"[took {tend:.4f}s]"
+ )
+ log = SubLogger.logger()
+ log.debug(
+ f"[{self.model.__class__.__name__}] "
+ f"optimization finished: best params {self.best_params_} (score={self.best_score_:.5f}) "
+ f"[took {tend:.4f}s]"
+ )
+
+ if self.refit:
+ if isinstance(protocol, OnLabelledCollectionProtocol):
+ self._sout("refitting on the whole development set")
+ self.best_model_.fit(training + protocol.get_labelled_collection())
+ else:
+ raise RuntimeWarning(
+ f'"refit" was requested, but the protocol does not '
+ f"implement the {OnLabelledCollectionProtocol.__name__} interface"
+ )
+
+ return self
+
+ def __params_eval(self, params, training):
+ protocol = self.protocol
+ error = self.error
+
+ # if self.timeout > 0:
+
+ # def handler(signum, frame):
+ # raise TimeoutError()
+
+ # signal.signal(signal.SIGALRM, handler)
+
+ tinit = time()
+
+ # if self.timeout > 0:
+ # signal.alarm(self.timeout)
+
+ try:
+ model = deepcopy(self.model)
+ # overrides default parameters with the parameters being explored at this iteration
+ model.set_params(**params)
+ # print({k: v for k, v in model.get_params().items() if k in params})
+ model.fit(training)
+ score = evaluate(model, protocol=protocol, error_metric=error)
+
+ ttime = time() - tinit
+ self._sout(
+ f"hyperparams={params}\t got score {score:.5f} [took {ttime:.4f}s]"
+ )
+
+ # if self.timeout > 0:
+ # signal.alarm(0)
+ # except TimeoutError:
+ # self._sout(f"timeout ({self.timeout}s) reached for config {params}")
+ # score = None
+ except ValueError as e:
+ self._sout(f"the combination of hyperparameters {params} is invalid")
+ raise e
+ except Exception as e:
+ self._sout(f"something went wrong for config {params}; skipping:")
+ self._sout(f"\tException: {e}")
+ score = None
+
+ return params, score, model
+
+ def extend(self, coll: LabelledCollection, pred_proba=None) -> ExtendedCollection:
+ assert hasattr(self, "best_model_"), "quantify called before fit"
+ return self.best_model().extend(coll, pred_proba=pred_proba)
+
+ def estimate(self, instances, ext=False):
+ """Estimate class prevalence values using the best model found after calling the :meth:`fit` method.
+
+ :param instances: sample contanining the instances
+ :return: a ndarray of shape `(n_classes)` with class prevalence estimates as according to the best model found
+ by the model selection process.
+ """
+
+ assert hasattr(self, "best_model_"), "estimate called before fit"
+ return self.best_model().estimate(instances, ext=ext)
+
+ def set_params(self, **parameters):
+ """Sets the hyper-parameters to explore.
+
+ :param parameters: a dictionary with keys the parameter names and values the list of values to explore
+ """
+ self.param_grid = parameters
+
+ def get_params(self, deep=True):
+ """Returns the dictionary of hyper-parameters to explore (`param_grid`)
+
+ :param deep: Unused
+ :return: the dictionary `param_grid`
+ """
+ return self.param_grid
+
+ def best_model(self):
+ """
+ Returns the best model found after calling the :meth:`fit` method, i.e., the one trained on the combination
+ of hyper-parameters that minimized the error function.
+
+ :return: a trained quantifier
+ """
+ if hasattr(self, "best_model_"):
+ return self.best_model_
+ raise ValueError("best_model called before fit")
+
+
+
+class MCAEgsq(MultiClassAccuracyEstimator):
+ def __init__(
+ self,
+ classifier: BaseEstimator,
+ quantifier: BaseAccuracyEstimator,
+ param_grid: dict,
+ error: Union[Callable, str] = qp.error.mae,
+ refit=True,
+ timeout=-1,
+ n_jobs=None,
+ verbose=False,
+ ):
+ self.param_grid = param_grid
+ self.refit = refit
+ self.timeout = timeout
+ self.n_jobs = n_jobs
+ self.verbose = verbose
+ self.error = error
+ super().__init__(classifier, quantifier)
+
+ def fit(self, train: LabelledCollection):
+ self.e_train = self.extend(train)
+ t_train, t_val = self.e_train.split_stratified(0.6, random_state=0)
+ self.quantifier = GridSearchQ(
+ deepcopy(self.quantifier),
+ param_grid=self.param_grid,
+ protocol=UPP(t_val, repeats=100),
+ error=self.error,
+ refit=self.refit,
+ timeout=self.timeout,
+ n_jobs=self.n_jobs,
+ verbose=self.verbose,
+ ).fit(self.e_train)
+
+ return self
+
+ def estimate(self, instances, ext=False) -> np.ndarray:
+ e_inst = instances if ext else self._extend_instances(instances)
+ estim_prev = self.quantifier.quantify(e_inst)
+ return self._check_prevalence_classes(estim_prev, self.quantifier.best_model().classes_)
+
+
+class BQAEgsq(BinaryQuantifierAccuracyEstimator):
+ def __init__(
+ self,
+ classifier: BaseEstimator,
+ quantifier: BaseAccuracyEstimator,
+ param_grid: dict,
+ error: Union[Callable, str] = qp.error.mae,
+ refit=True,
+ timeout=-1,
+ n_jobs=None,
+ verbose=False,
+ ):
+ self.param_grid = param_grid
+ self.refit = refit
+ self.timeout = timeout
+ self.n_jobs = n_jobs
+ self.verbose = verbose
+ self.error = error
+ super().__init__(classifier=classifier, quantifier=quantifier)
+
+ def fit(self, train: LabelledCollection):
+ self.e_train = self.extend(train)
+
+ self.n_classes = self.e_train.n_classes
+ self.e_trains = self.e_train.split_by_pred()
+
+ self.quantifiers = []
+ for e_train in self.e_trains:
+ t_train, t_val = e_train.split_stratified(0.6, random_state=0)
+ quantifier = GridSearchQ(
+ model=deepcopy(self.quantifier),
+ param_grid=self.param_grid,
+ protocol=UPP(t_val, repeats=100),
+ error=self.error,
+ refit=self.refit,
+ timeout=self.timeout,
+ n_jobs=self.n_jobs,
+ verbose=self.verbose,
+ ).fit(t_train)
+ self.quantifiers.append(quantifier)
+
+ return self
diff --git a/quacc/plot.py b/quacc/plot.py
index 4ccb3fe..471c1cb 100644
--- a/quacc/plot.py
+++ b/quacc/plot.py
@@ -1,239 +1,239 @@
-from pathlib import Path
-
-import matplotlib
-import matplotlib.pyplot as plt
-import numpy as np
-from cycler import cycler
-
-from quacc.environment import env
-
-matplotlib.use("agg")
-
-
-def _get_markers(n: int):
- ls = "ovx+sDph*^1234X><.Pd"
- if n > len(ls):
- ls = ls * (n / len(ls) + 1)
- return list(ls)[:n]
-
-
-def plot_delta(
- base_prevs,
- columns,
- data,
- *,
- stdevs=None,
- pos_class=1,
- metric="acc",
- name="default",
- train_prev=None,
- legend=True,
- avg=None,
-) -> Path:
- _base_title = "delta_stdev" if stdevs is not None else "delta"
- if train_prev is not None:
- t_prev_pos = int(round(train_prev[pos_class] * 100))
- title = f"{_base_title}_{name}_{t_prev_pos}_{metric}"
- else:
- title = f"{_base_title}_{name}_avg_{avg}_{metric}"
-
- fig, ax = plt.subplots()
- ax.set_aspect("auto")
- ax.grid()
-
- NUM_COLORS = len(data)
- cm = plt.get_cmap("tab10")
- if NUM_COLORS > 10:
- cm = plt.get_cmap("tab20")
- cy = cycler(color=[cm(i) for i in range(NUM_COLORS)])
-
- base_prevs = base_prevs[:, pos_class]
- for method, deltas, _cy in zip(columns, data, cy):
- ax.plot(
- base_prevs,
- deltas,
- label=method,
- color=_cy["color"],
- linestyle="-",
- marker="o",
- markersize=3,
- zorder=2,
- )
- if stdevs is not None:
- _col_idx = np.where(columns == method)[0]
- stdev = stdevs[_col_idx].flatten()
- nn_idx = np.intersect1d(
- np.where(deltas != np.nan)[0],
- np.where(stdev != np.nan)[0],
- )
- _bps, _ds, _st = base_prevs[nn_idx], deltas[nn_idx], stdev[nn_idx]
- ax.fill_between(
- _bps,
- _ds - _st,
- _ds + _st,
- color=_cy["color"],
- alpha=0.25,
- )
-
- x_label = "test" if avg is None or avg == "train" else "train"
- ax.set(
- xlabel=f"{x_label} prevalence",
- ylabel=metric,
- title=title,
- )
-
- if legend:
- ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))
- output_path = env.PLOT_OUT_DIR / f"{title}.png"
- fig.savefig(output_path, bbox_inches="tight")
-
- return output_path
-
-
-def plot_diagonal(
- reference,
- columns,
- data,
- *,
- pos_class=1,
- metric="acc",
- name="default",
- train_prev=None,
- legend=True,
-):
- if train_prev is not None:
- t_prev_pos = int(round(train_prev[pos_class] * 100))
- title = f"diagonal_{name}_{t_prev_pos}_{metric}"
- else:
- title = f"diagonal_{name}_{metric}"
-
- fig, ax = plt.subplots()
- ax.set_aspect("auto")
- ax.grid()
- ax.set_aspect("equal")
-
- NUM_COLORS = len(data)
- cm = plt.get_cmap("tab10")
- if NUM_COLORS > 10:
- cm = plt.get_cmap("tab20")
- cy = cycler(
- color=[cm(i) for i in range(NUM_COLORS)],
- marker=_get_markers(NUM_COLORS),
- )
-
- reference = np.array(reference)
- x_ticks = np.unique(reference)
- x_ticks.sort()
-
- for deltas, _cy in zip(data, cy):
- ax.plot(
- reference,
- deltas,
- color=_cy["color"],
- linestyle="None",
- marker=_cy["marker"],
- markersize=3,
- zorder=2,
- alpha=0.25,
- )
-
- # ensure limits are equal for both axes
- _alims = np.stack(((ax.get_xlim(), ax.get_ylim())), axis=-1)
- _lims = np.array([f(ls) for f, ls in zip([np.min, np.max], _alims)])
- ax.set(xlim=tuple(_lims), ylim=tuple(_lims))
-
- for method, deltas, _cy in zip(columns, data, cy):
- slope, interc = np.polyfit(reference, deltas, 1)
- y_lr = np.array([slope * x + interc for x in _lims])
- ax.plot(
- _lims,
- y_lr,
- label=method,
- color=_cy["color"],
- linestyle="-",
- markersize="0",
- zorder=1,
- )
-
- # plot reference line
- ax.plot(
- _lims,
- _lims,
- color="black",
- linestyle="--",
- markersize=0,
- zorder=1,
- )
-
- ax.set(xlabel=f"true {metric}", ylabel=f"estim. {metric}", title=title)
-
- if legend:
- ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))
- output_path = env.PLOT_OUT_DIR / f"{title}.png"
- fig.savefig(output_path, bbox_inches="tight")
- return output_path
-
-
-def plot_shift(
- shift_prevs,
- columns,
- data,
- *,
- counts=None,
- pos_class=1,
- metric="acc",
- name="default",
- train_prev=None,
- legend=True,
-) -> Path:
- if train_prev is not None:
- t_prev_pos = int(round(train_prev[pos_class] * 100))
- title = f"shift_{name}_{t_prev_pos}_{metric}"
- else:
- title = f"shift_{name}_avg_{metric}"
-
- fig, ax = plt.subplots()
- ax.set_aspect("auto")
- ax.grid()
-
- NUM_COLORS = len(data)
- cm = plt.get_cmap("tab10")
- if NUM_COLORS > 10:
- cm = plt.get_cmap("tab20")
- cy = cycler(color=[cm(i) for i in range(NUM_COLORS)])
-
- shift_prevs = shift_prevs[:, pos_class]
- for method, shifts, _cy in zip(columns, data, cy):
- ax.plot(
- shift_prevs,
- shifts,
- label=method,
- color=_cy["color"],
- linestyle="-",
- marker="o",
- markersize=3,
- zorder=2,
- )
- if counts is not None:
- _col_idx = np.where(columns == method)[0]
- count = counts[_col_idx].flatten()
- for prev, shift, cnt in zip(shift_prevs, shifts, count):
- label = f"{cnt}"
- plt.annotate(
- label,
- (prev, shift),
- textcoords="offset points",
- xytext=(0, 10),
- ha="center",
- color=_cy["color"],
- fontsize=12.0,
- )
-
- ax.set(xlabel="dataset shift", ylabel=metric, title=title)
-
- if legend:
- ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))
- output_path = env.PLOT_OUT_DIR / f"{title}.png"
- fig.savefig(output_path, bbox_inches="tight")
-
- return output_path
+from pathlib import Path
+
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+from cycler import cycler
+
+from quacc.environment import env
+
+matplotlib.use("agg")
+
+
+def _get_markers(n: int):
+ ls = "ovx+sDph*^1234X><.Pd"
+ if n > len(ls):
+ ls = ls * (n / len(ls) + 1)
+ return list(ls)[:n]
+
+
+def plot_delta(
+ base_prevs,
+ columns,
+ data,
+ *,
+ stdevs=None,
+ pos_class=1,
+ metric="acc",
+ name="default",
+ train_prev=None,
+ legend=True,
+ avg=None,
+) -> Path:
+ _base_title = "delta_stdev" if stdevs is not None else "delta"
+ if train_prev is not None:
+ t_prev_pos = int(round(train_prev[pos_class] * 100))
+ title = f"{_base_title}_{name}_{t_prev_pos}_{metric}"
+ else:
+ title = f"{_base_title}_{name}_avg_{avg}_{metric}"
+
+ fig, ax = plt.subplots()
+ ax.set_aspect("auto")
+ ax.grid()
+
+ NUM_COLORS = len(data)
+ cm = plt.get_cmap("tab10")
+ if NUM_COLORS > 10:
+ cm = plt.get_cmap("tab20")
+ cy = cycler(color=[cm(i) for i in range(NUM_COLORS)])
+
+ base_prevs = base_prevs[:, pos_class]
+ for method, deltas, _cy in zip(columns, data, cy):
+ ax.plot(
+ base_prevs,
+ deltas,
+ label=method,
+ color=_cy["color"],
+ linestyle="-",
+ marker="o",
+ markersize=3,
+ zorder=2,
+ )
+ if stdevs is not None:
+ _col_idx = np.where(columns == method)[0]
+ stdev = stdevs[_col_idx].flatten()
+ nn_idx = np.intersect1d(
+ np.where(deltas != np.nan)[0],
+ np.where(stdev != np.nan)[0],
+ )
+ _bps, _ds, _st = base_prevs[nn_idx], deltas[nn_idx], stdev[nn_idx]
+ ax.fill_between(
+ _bps,
+ _ds - _st,
+ _ds + _st,
+ color=_cy["color"],
+ alpha=0.25,
+ )
+
+ x_label = "test" if avg is None or avg == "train" else "train"
+ ax.set(
+ xlabel=f"{x_label} prevalence",
+ ylabel=metric,
+ title=title,
+ )
+
+ if legend:
+ ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))
+ output_path = env.PLOT_OUT_DIR / f"{title}.png"
+ fig.savefig(output_path, bbox_inches="tight")
+
+ return output_path
+
+
+def plot_diagonal(
+ reference,
+ columns,
+ data,
+ *,
+ pos_class=1,
+ metric="acc",
+ name="default",
+ train_prev=None,
+ legend=True,
+):
+ if train_prev is not None:
+ t_prev_pos = int(round(train_prev[pos_class] * 100))
+ title = f"diagonal_{name}_{t_prev_pos}_{metric}"
+ else:
+ title = f"diagonal_{name}_{metric}"
+
+ fig, ax = plt.subplots()
+ ax.set_aspect("auto")
+ ax.grid()
+ ax.set_aspect("equal")
+
+ NUM_COLORS = len(data)
+ cm = plt.get_cmap("tab10")
+ if NUM_COLORS > 10:
+ cm = plt.get_cmap("tab20")
+ cy = cycler(
+ color=[cm(i) for i in range(NUM_COLORS)],
+ marker=_get_markers(NUM_COLORS),
+ )
+
+ reference = np.array(reference)
+ x_ticks = np.unique(reference)
+ x_ticks.sort()
+
+ for deltas, _cy in zip(data, cy):
+ ax.plot(
+ reference,
+ deltas,
+ color=_cy["color"],
+ linestyle="None",
+ marker=_cy["marker"],
+ markersize=3,
+ zorder=2,
+ alpha=0.25,
+ )
+
+ # ensure limits are equal for both axes
+ _alims = np.stack(((ax.get_xlim(), ax.get_ylim())), axis=-1)
+ _lims = np.array([f(ls) for f, ls in zip([np.min, np.max], _alims)])
+ ax.set(xlim=tuple(_lims), ylim=tuple(_lims))
+
+ for method, deltas, _cy in zip(columns, data, cy):
+ slope, interc = np.polyfit(reference, deltas, 1)
+ y_lr = np.array([slope * x + interc for x in _lims])
+ ax.plot(
+ _lims,
+ y_lr,
+ label=method,
+ color=_cy["color"],
+ linestyle="-",
+ markersize="0",
+ zorder=1,
+ )
+
+ # plot reference line
+ ax.plot(
+ _lims,
+ _lims,
+ color="black",
+ linestyle="--",
+ markersize=0,
+ zorder=1,
+ )
+
+ ax.set(xlabel=f"true {metric}", ylabel=f"estim. {metric}", title=title)
+
+ if legend:
+ ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))
+ output_path = env.PLOT_OUT_DIR / f"{title}.png"
+ fig.savefig(output_path, bbox_inches="tight")
+ return output_path
+
+
+def plot_shift(
+ shift_prevs,
+ columns,
+ data,
+ *,
+ counts=None,
+ pos_class=1,
+ metric="acc",
+ name="default",
+ train_prev=None,
+ legend=True,
+) -> Path:
+ if train_prev is not None:
+ t_prev_pos = int(round(train_prev[pos_class] * 100))
+ title = f"shift_{name}_{t_prev_pos}_{metric}"
+ else:
+ title = f"shift_{name}_avg_{metric}"
+
+ fig, ax = plt.subplots()
+ ax.set_aspect("auto")
+ ax.grid()
+
+ NUM_COLORS = len(data)
+ cm = plt.get_cmap("tab10")
+ if NUM_COLORS > 10:
+ cm = plt.get_cmap("tab20")
+ cy = cycler(color=[cm(i) for i in range(NUM_COLORS)])
+
+ shift_prevs = shift_prevs[:, pos_class]
+ for method, shifts, _cy in zip(columns, data, cy):
+ ax.plot(
+ shift_prevs,
+ shifts,
+ label=method,
+ color=_cy["color"],
+ linestyle="-",
+ marker="o",
+ markersize=3,
+ zorder=2,
+ )
+ if counts is not None:
+ _col_idx = np.where(columns == method)[0]
+ count = counts[_col_idx].flatten()
+ for prev, shift, cnt in zip(shift_prevs, shifts, count):
+ label = f"{cnt}"
+ plt.annotate(
+ label,
+ (prev, shift),
+ textcoords="offset points",
+ xytext=(0, 10),
+ ha="center",
+ color=_cy["color"],
+ fontsize=12.0,
+ )
+
+ ax.set(xlabel="dataset shift", ylabel=metric, title=title)
+
+ if legend:
+ ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))
+ output_path = env.PLOT_OUT_DIR / f"{title}.png"
+ fig.savefig(output_path, bbox_inches="tight")
+
+ return output_path
diff --git a/quacc/utils.py b/quacc/utils.py
index 7989154..52d8e2f 100644
--- a/quacc/utils.py
+++ b/quacc/utils.py
@@ -1,59 +1,59 @@
-import functools
-import os
-import shutil
-from pathlib import Path
-
-import pandas as pd
-
-from quacc.environment import env
-
-
-def combine_dataframes(dfs, df_index=[]) -> pd.DataFrame:
- if len(dfs) < 1:
- raise ValueError
- if len(dfs) == 1:
- return dfs[0]
- df = dfs[0]
- for ndf in dfs[1:]:
- df = df.join(ndf.set_index(df_index), on=df_index)
-
- return df
-
-
-def avg_group_report(df: pd.DataFrame) -> pd.DataFrame:
- def _reduce_func(s1, s2):
- return {(n1, n2): v + s2[(n1, n2)] for ((n1, n2), v) in s1.items()}
-
- lst = df.to_dict(orient="records")[1:-1]
- summed_series = functools.reduce(_reduce_func, lst)
- idx = df.columns.drop([("base", "T"), ("base", "F")])
- avg_report = {
- (n1, n2): (v / len(lst))
- for ((n1, n2), v) in summed_series.items()
- if n1 != "base"
- }
- return pd.DataFrame([avg_report], columns=idx)
-
-
-def fmt_line_md(s):
- return f"> {s} \n"
-
-
-def create_dataser_dir(dir_name, update=False):
- base_out_dir = Path(env.OUT_DIR_NAME)
- if not base_out_dir.exists():
- os.mkdir(base_out_dir)
-
- dataset_dir = base_out_dir / dir_name
- env.OUT_DIR = dataset_dir
- if update:
- if not dataset_dir.exists():
- os.mkdir(dataset_dir)
- else:
- shutil.rmtree(dataset_dir, ignore_errors=True)
- os.mkdir(dataset_dir)
-
- plot_dir_path = dataset_dir / "plot"
- env.PLOT_OUT_DIR = plot_dir_path
- if not plot_dir_path.exists():
- os.mkdir(plot_dir_path)
+import functools
+import os
+import shutil
+from pathlib import Path
+
+import pandas as pd
+
+from quacc.environment import env
+
+
+def combine_dataframes(dfs, df_index=[]) -> pd.DataFrame:
+ if len(dfs) < 1:
+ raise ValueError
+ if len(dfs) == 1:
+ return dfs[0]
+ df = dfs[0]
+ for ndf in dfs[1:]:
+ df = df.join(ndf.set_index(df_index), on=df_index)
+
+ return df
+
+
+def avg_group_report(df: pd.DataFrame) -> pd.DataFrame:
+ def _reduce_func(s1, s2):
+ return {(n1, n2): v + s2[(n1, n2)] for ((n1, n2), v) in s1.items()}
+
+ lst = df.to_dict(orient="records")[1:-1]
+ summed_series = functools.reduce(_reduce_func, lst)
+ idx = df.columns.drop([("base", "T"), ("base", "F")])
+ avg_report = {
+ (n1, n2): (v / len(lst))
+ for ((n1, n2), v) in summed_series.items()
+ if n1 != "base"
+ }
+ return pd.DataFrame([avg_report], columns=idx)
+
+
+def fmt_line_md(s):
+ return f"> {s} \n"
+
+
+def create_dataser_dir(dir_name, update=False):
+ base_out_dir = Path(env.OUT_DIR_NAME)
+ if not base_out_dir.exists():
+ os.mkdir(base_out_dir)
+
+ dataset_dir = base_out_dir / dir_name
+ env.OUT_DIR = dataset_dir
+ if update:
+ if not dataset_dir.exists():
+ os.mkdir(dataset_dir)
+ else:
+ shutil.rmtree(dataset_dir, ignore_errors=True)
+ os.mkdir(dataset_dir)
+
+ plot_dir_path = dataset_dir / "plot"
+ env.PLOT_OUT_DIR = plot_dir_path
+ if not plot_dir_path.exists():
+ os.mkdir(plot_dir_path)
diff --git a/roadmap.md b/roadmap.md
index 1be8275..f7d7784 100644
--- a/roadmap.md
+++ b/roadmap.md
@@ -1,40 +1,40 @@
-
-## Roadmap
-
-#### quantificator domain
-
- - single multilabel quantificator
-
- - vector of binary quantificators
-
- | quantificator | | |
- |:-------------------:|:--------------:|:--------------:|
- | true quantificator | true positive | false positive |
- | false quantificator | false negative | true negative |
-
-#### dataset split
-
- - train | test
- - classificator C is fit on train
- - quantificator Q is fit on cross validation of C over train
- - train | validation | test
- - classificator C is fit on train
- - quantificator Q is fit on validation
-
-#### classificator origin
-
- - black box
- - crystal box
-
-#### test metrics
-
- - f1_score
- - K
-
-#### models
-
- - classificator
- - quantificator
-
-
-
+
+## Roadmap
+
+#### quantificator domain
+
+ - single multilabel quantificator
+
+ - vector of binary quantificators
+
+ | quantificator | | |
+ |:-------------------:|:--------------:|:--------------:|
+ | true quantificator | true positive | false positive |
+ | false quantificator | false negative | true negative |
+
+#### dataset split
+
+ - train | test
+ - classificator C is fit on train
+ - quantificator Q is fit on cross validation of C over train
+ - train | validation | test
+ - classificator C is fit on train
+ - quantificator Q is fit on validation
+
+#### classificator origin
+
+ - black box
+ - crystal box
+
+#### test metrics
+
+ - f1_score
+ - K
+
+#### models
+
+ - classificator
+ - quantificator
+
+
+
diff --git a/test_mc.md b/test_mc.md
index c022a66..7ff99bd 100644
--- a/test_mc.md
+++ b/test_mc.md
@@ -1,2102 +1,2102 @@
-| | ('acc', 'mulmc_sld') | ('acc_score', 'mulmc_sld') | ('acc_score', 'ref') | ('eprevs', 'mulmc_sld') | ('f1', 'mulmc_sld') | ('f1_score', 'mulmc_sld') | ('f1_score', 'ref') | ('prevs', 'mulmc_sld') | ('ref', 'mulmc_sld') |
-|:-----------|-----------------------:|-----------------------------:|-----------------------:|:--------------------------|----------------------:|----------------------------:|----------------------:|:-------------------------|-----------------------:|
-| (0.0, 0) | 0.117723 | 0.0322767 | 0.15 | [0.15 0.85 0. 0. ] | 1.07331e-70 | 1.07331e-70 | 0 | [0.15 0.85] | 0.15 |
-| (0.0, 1) | 0.104077 | 0.0449229 | 0.149 | [0.149 0.851 0. 0. ] | 8.53968e-74 | 8.53968e-74 | 0 | [0.149 0.851] | 0.149 |
-| (0.0, 2) | 0.087328 | 0.046672 | 0.134 | [0.134 0.866 0. 0. ] | 1.42651e-85 | 1.42651e-85 | 0 | [0.134 0.866] | 0.134 |
-| (0.0, 3) | 0.111971 | 0.0340294 | 0.146 | [0.146 0.854 0. 0. ] | 6.79989e-84 | 6.79989e-84 | 0 | [0.146 0.854] | 0.146 |
-| (0.0, 4) | 0.114691 | 0.0233089 | 0.138 | [0.138 0.862 0. 0. ] | 1.46993e-84 | 1.46993e-84 | 0 | [0.138 0.862] | 0.138 |
-| (0.0, 5) | 0.103348 | 0.0556519 | 0.159 | [0.159 0.841 0. 0. ] | 3.0317e-73 | 3.0317e-73 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 6) | 0.0685699 | 0.0654301 | 0.134 | [0.134 0.866 0. 0. ] | 1.41915e-80 | 1.41915e-80 | 0 | [0.134 0.866] | 0.134 |
-| (0.0, 7) | 0.0672097 | 0.0867903 | 0.154 | [0.154 0.846 0. 0. ] | 1.58212e-72 | 1.58212e-72 | 0 | [0.154 0.846] | 0.154 |
-| (0.0, 8) | 0.0906741 | 0.0343259 | 0.125 | [0.125 0.875 0. 0. ] | 2.35037e-81 | 2.35037e-81 | 0 | [0.125 0.875] | 0.125 |
-| (0.0, 9) | 0.108344 | 0.0456563 | 0.154 | [0.154 0.846 0. 0. ] | 1.61876e-89 | 1.61876e-89 | 0 | [0.154 0.846] | 0.154 |
-| (0.0, 10) | 0.111637 | 0.0303634 | 0.142 | [0.142 0.858 0. 0. ] | 2.34042e-76 | 2.34042e-76 | 0 | [0.142 0.858] | 0.142 |
-| (0.0, 11) | 0.0818937 | 0.0631063 | 0.145 | [0.145 0.855 0. 0. ] | 8.88464e-76 | 8.88464e-76 | 0 | [0.145 0.855] | 0.145 |
-| (0.0, 12) | 0.080566 | 0.053434 | 0.134 | [0.134 0.866 0. 0. ] | 2.06441e-85 | 2.06441e-85 | 0 | [0.134 0.866] | 0.134 |
-| (0.0, 13) | 0.109082 | 0.0259184 | 0.135 | [0.135 0.865 0. 0. ] | 6.90501e-68 | 6.90501e-68 | 0 | [0.135 0.865] | 0.135 |
-| (0.0, 14) | 0.104661 | 0.0563386 | 0.161 | [0.161 0.839 0. 0. ] | 1.20084e-80 | 1.20084e-80 | 0 | [0.161 0.839] | 0.161 |
-| (0.0, 15) | 0.110168 | 0.0358321 | 0.146 | [0.146 0.854 0. 0. ] | 5.13457e-80 | 5.13457e-80 | 0 | [0.146 0.854] | 0.146 |
-| (0.0, 16) | 0.0821699 | 0.0548301 | 0.137 | [0.137 0.863 0. 0. ] | 1.23927e-107 | 1.23927e-107 | 0 | [0.137 0.863] | 0.137 |
-| (0.0, 17) | 0.152954 | 0.00104645 | 0.154 | [0.154 0.846 0. 0. ] | 7.76874e-67 | 7.76874e-67 | 0 | [0.154 0.846] | 0.154 |
-| (0.0, 18) | 0.101295 | 0.0507053 | 0.152 | [0.152 0.848 0. 0. ] | 5.41613e-70 | 5.41613e-70 | 0 | [0.152 0.848] | 0.152 |
-| (0.0, 19) | 0.101427 | 0.0475729 | 0.149 | [0.149 0.851 0. 0. ] | 7.82058e-75 | 7.82058e-75 | 0 | [0.149 0.851] | 0.149 |
-| (0.0, 20) | 0.0552487 | 0.111751 | 0.167 | [0.167 0.833 0. 0. ] | 1.48613e-85 | 1.48613e-85 | 0 | [0.167 0.833] | 0.167 |
-| (0.0, 21) | 0.105907 | 0.0250927 | 0.131 | [0.131 0.869 0. 0. ] | 4.52759e-74 | 4.52759e-74 | 0 | [0.131 0.869] | 0.131 |
-| (0.0, 22) | 0.0702368 | 0.0837632 | 0.154 | [0.154 0.846 0. 0. ] | 4.82942e-111 | 4.82942e-111 | 0 | [0.154 0.846] | 0.154 |
-| (0.0, 23) | 0.121287 | 0.0297134 | 0.151 | [0.151 0.849 0. 0. ] | 5.89441e-65 | 5.89441e-65 | 0 | [0.151 0.849] | 0.151 |
-| (0.0, 24) | 0.0834857 | 0.0645143 | 0.148 | [0.148 0.852 0. 0. ] | 3.59591e-72 | 3.59591e-72 | 0 | [0.148 0.852] | 0.148 |
-| (0.0, 25) | 0.0948862 | 0.0471138 | 0.142 | [0.142 0.858 0. 0. ] | 4.1855e-77 | 4.1855e-77 | 0 | [0.142 0.858] | 0.142 |
-| (0.0, 26) | 0.084485 | 0.066515 | 0.151 | [0.151 0.849 0. 0. ] | 3.53958e-93 | 3.53958e-93 | 0 | [0.151 0.849] | 0.151 |
-| (0.0, 27) | 0.0788194 | 0.0781806 | 0.157 | [0.157 0.843 0. 0. ] | 7.26205e-93 | 7.26205e-93 | 0 | [0.157 0.843] | 0.157 |
-| (0.0, 28) | 0.100112 | 0.0588884 | 0.159 | [0.159 0.841 0. 0. ] | 3.99054e-87 | 3.99054e-87 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 29) | 0.0964799 | 0.0535201 | 0.15 | [0.15 0.85 0. 0. ] | 6.532e-82 | 6.532e-82 | 0 | [0.15 0.85] | 0.15 |
-| (0.0, 30) | 0.119753 | 0.0272469 | 0.147 | [0.147 0.853 0. 0. ] | 4.10831e-75 | 4.10831e-75 | 0 | [0.147 0.853] | 0.147 |
-| (0.0, 31) | 0.0706346 | 0.0883654 | 0.159 | [0.159 0.841 0. 0. ] | 1.27863e-72 | 1.27863e-72 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 32) | 0.0988101 | 0.0491899 | 0.148 | [0.148 0.852 0. 0. ] | 2.07851e-74 | 2.07851e-74 | 0 | [0.148 0.852] | 0.148 |
-| (0.0, 33) | 0.0783135 | 0.0846865 | 0.163 | [0.163 0.837 0. 0. ] | 2.39408e-90 | 2.39408e-90 | 0 | [0.163 0.837] | 0.163 |
-| (0.0, 34) | 0.0902689 | 0.0557311 | 0.146 | [0.146 0.854 0. 0. ] | 6.57654e-81 | 6.57654e-81 | 0 | [0.146 0.854] | 0.146 |
-| (0.0, 35) | 0.0917235 | 0.0572765 | 0.149 | [0.149 0.851 0. 0. ] | 1.93739e-83 | 1.93739e-83 | 0 | [0.149 0.851] | 0.149 |
-| (0.0, 36) | 0.0600061 | 0.108994 | 0.169 | [0.169 0.831 0. 0. ] | 1.4334e-110 | 1.4334e-110 | 0 | [0.169 0.831] | 0.169 |
-| (0.0, 37) | 0.0939152 | 0.0700848 | 0.164 | [0.164 0.836 0. 0. ] | 3.97301e-77 | 3.97301e-77 | 0 | [0.164 0.836] | 0.164 |
-| (0.0, 38) | 0.0713029 | 0.0846971 | 0.156 | [0.156 0.844 0. 0. ] | 1.62578e-85 | 1.62578e-85 | 0 | [0.156 0.844] | 0.156 |
-| (0.0, 39) | 0.10238 | 0.0696199 | 0.172 | [0.172 0.828 0. 0. ] | 1.64608e-71 | 1.64608e-71 | 0 | [0.172 0.828] | 0.172 |
-| (0.0, 40) | 0.0808104 | 0.0661896 | 0.147 | [0.147 0.853 0. 0. ] | 7.03173e-76 | 7.03173e-76 | 0 | [0.147 0.853] | 0.147 |
-| (0.0, 41) | 0.0477844 | 0.105216 | 0.153 | [0.153 0.847 0. 0. ] | 1.94212e-97 | 1.94212e-97 | 0 | [0.153 0.847] | 0.153 |
-| (0.0, 42) | 0.0755388 | 0.0734612 | 0.149 | [0.149 0.851 0. 0. ] | 9.58123e-82 | 9.58123e-82 | 0 | [0.149 0.851] | 0.149 |
-| (0.0, 43) | 0.0541017 | 0.0788983 | 0.133 | [0.133 0.867 0. 0. ] | 3.21118e-74 | 3.21118e-74 | 0 | [0.133 0.867] | 0.133 |
-| (0.0, 44) | 0.0856808 | 0.0713192 | 0.157 | [0.157 0.843 0. 0. ] | 1.72404e-73 | 1.72404e-73 | 0 | [0.157 0.843] | 0.157 |
-| (0.0, 45) | 0.0736663 | 0.0893337 | 0.163 | [0.163 0.837 0. 0. ] | 5.94041e-97 | 5.94041e-97 | 0 | [0.163 0.837] | 0.163 |
-| (0.0, 46) | 0.118402 | 0.038598 | 0.157 | [0.157 0.843 0. 0. ] | 6.0959e-69 | 6.0959e-69 | 0 | [0.157 0.843] | 0.157 |
-| (0.0, 47) | 0.11078 | 0.0342197 | 0.145 | [0.145 0.855 0. 0. ] | 4.06314e-72 | 4.06314e-72 | 0 | [0.145 0.855] | 0.145 |
-| (0.0, 48) | 0.0831503 | 0.0478497 | 0.131 | [0.131 0.869 0. 0. ] | 5.42314e-85 | 5.42314e-85 | 0 | [0.131 0.869] | 0.131 |
-| (0.0, 49) | 0.0916819 | 0.0513181 | 0.143 | [0.143 0.857 0. 0. ] | 5.04478e-81 | 5.04478e-81 | 0 | [0.143 0.857] | 0.143 |
-| (0.0, 50) | 0.11094 | 0.03506 | 0.146 | [0.146 0.854 0. 0. ] | 2.9869e-75 | 2.9869e-75 | 0 | [0.146 0.854] | 0.146 |
-| (0.0, 51) | 0.0908154 | 0.0471846 | 0.138 | [0.138 0.862 0. 0. ] | 7.09617e-64 | 7.09617e-64 | 0 | [0.138 0.862] | 0.138 |
-| (0.0, 52) | 0.116686 | 0.0233143 | 0.14 | [0.14 0.86 0. 0. ] | 1.53735e-66 | 1.53735e-66 | 0 | [0.14 0.86] | 0.14 |
-| (0.0, 53) | 0.0621283 | 0.104872 | 0.167 | [0.167 0.833 0. 0. ] | 1.32848e-95 | 1.32848e-95 | 0 | [0.167 0.833] | 0.167 |
-| (0.0, 54) | 0.0971333 | 0.0688667 | 0.166 | [0.166 0.834 0. 0. ] | 1.60209e-77 | 1.60209e-77 | 0 | [0.166 0.834] | 0.166 |
-| (0.0, 55) | 0.0930373 | 0.0839627 | 0.177 | [0.177 0.823 0. 0. ] | 1.6235e-87 | 1.6235e-87 | 0 | [0.177 0.823] | 0.177 |
-| (0.0, 56) | 0.0757822 | 0.0812178 | 0.157 | [0.157 0.843 0. 0. ] | 4.25804e-75 | 4.25804e-75 | 0 | [0.157 0.843] | 0.157 |
-| (0.0, 57) | 0.0938824 | 0.0411176 | 0.135 | [0.135 0.865 0. 0. ] | 2.09063e-71 | 2.09063e-71 | 0 | [0.135 0.865] | 0.135 |
-| (0.0, 58) | 0.106571 | 0.0524287 | 0.159 | [0.159 0.841 0. 0. ] | 7.73697e-68 | 7.73697e-68 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 59) | 0.0897803 | 0.0692197 | 0.159 | [0.159 0.841 0. 0. ] | 9.83727e-73 | 9.83727e-73 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 60) | 0.111984 | 0.0160161 | 0.128 | [0.128 0.872 0. 0. ] | 3.54758e-79 | 3.54758e-79 | 0 | [0.128 0.872] | 0.128 |
-| (0.0, 61) | 0.101143 | 0.0308567 | 0.132 | [0.132 0.868 0. 0. ] | 1.72902e-77 | 1.72902e-77 | 0 | [0.132 0.868] | 0.132 |
-| (0.0, 62) | 0.115279 | 0.0377211 | 0.153 | [0.153 0.847 0. 0. ] | 7.03603e-77 | 7.03603e-77 | 0 | [0.153 0.847] | 0.153 |
-| (0.0, 63) | 0.0948507 | 0.0621493 | 0.157 | [0.157 0.843 0. 0. ] | 1.29883e-86 | 1.29883e-86 | 0 | [0.157 0.843] | 0.157 |
-| (0.0, 64) | 0.103509 | 0.0334913 | 0.137 | [0.137 0.863 0. 0. ] | 3.80986e-80 | 3.80986e-80 | 0 | [0.137 0.863] | 0.137 |
-| (0.0, 65) | 0.0781409 | 0.0808591 | 0.159 | [0.159 0.841 0. 0. ] | 1.80981e-71 | 1.80981e-71 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 66) | 0.0757231 | 0.0592769 | 0.135 | [0.135 0.865 0. 0. ] | 3.5588e-95 | 3.5588e-95 | 0 | [0.135 0.865] | 0.135 |
-| (0.0, 67) | 0.0728872 | 0.0881128 | 0.161 | [0.161 0.839 0. 0. ] | 5.99213e-89 | 5.99213e-89 | 0 | [0.161 0.839] | 0.161 |
-| (0.0, 68) | 0.0639539 | 0.0750461 | 0.139 | [0.139 0.861 0. 0. ] | 6.04828e-84 | 6.04828e-84 | 0 | [0.139 0.861] | 0.139 |
-| (0.0, 69) | 0.126742 | 0.0192578 | 0.146 | [0.146 0.854 0. 0. ] | 3.02779e-81 | 3.02779e-81 | 0 | [0.146 0.854] | 0.146 |
-| (0.0, 70) | 0.0826081 | 0.0673919 | 0.15 | [0.15 0.85 0. 0. ] | 1.46215e-89 | 1.46215e-89 | 0 | [0.15 0.85] | 0.15 |
-| (0.0, 71) | 0.0866534 | 0.0793466 | 0.166 | [0.166 0.834 0. 0. ] | 4.1842e-87 | 4.1842e-87 | 0 | [0.166 0.834] | 0.166 |
-| (0.0, 72) | 0.0756651 | 0.0873349 | 0.163 | [0.163 0.837 0. 0. ] | 4.15436e-100 | 4.15436e-100 | 0 | [0.163 0.837] | 0.163 |
-| (0.0, 73) | 0.0842012 | 0.0727988 | 0.157 | [0.157 0.843 0. 0. ] | 4.33554e-72 | 4.33554e-72 | 0 | [0.157 0.843] | 0.157 |
-| (0.0, 74) | 0.0732343 | 0.0537657 | 0.127 | [0.127 0.873 0. 0. ] | 5.78521e-65 | 5.78521e-65 | 0 | [0.127 0.873] | 0.127 |
-| (0.0, 75) | 0.0436204 | 0.10138 | 0.145 | [0.145 0.855 0. 0. ] | 5.99248e-08 | 5.99248e-08 | 0 | [0.145 0.855] | 0.145 |
-| (0.0, 76) | 0.073634 | 0.071366 | 0.145 | [0.145 0.855 0. 0. ] | 1.33422e-86 | 1.33422e-86 | 0 | [0.145 0.855] | 0.145 |
-| (0.0, 77) | 0.114722 | 0.0242778 | 0.139 | [0.139 0.861 0. 0. ] | 1.22296e-69 | 1.22296e-69 | 0 | [0.139 0.861] | 0.139 |
-| (0.0, 78) | 0.0910729 | 0.0529271 | 0.144 | [0.144 0.856 0. 0. ] | 3.20385e-81 | 3.20385e-81 | 0 | [0.144 0.856] | 0.144 |
-| (0.0, 79) | 0.1199 | 0.0391 | 0.159 | [0.159 0.841 0. 0. ] | 4.88611e-80 | 4.88611e-80 | 0 | [0.159 0.841] | 0.159 |
-| (0.0, 80) | 0.101953 | 0.0500466 | 0.152 | [0.152 0.848 0. 0. ] | 1.89129e-75 | 1.89129e-75 | 0 | [0.152 0.848] | 0.152 |
-| (0.0, 81) | 0.0889951 | 0.0510049 | 0.14 | [0.14 0.86 0. 0. ] | 1.37045e-70 | 1.37045e-70 | 0 | [0.14 0.86] | 0.14 |
-| (0.0, 82) | 0.0998662 | 0.0471338 | 0.147 | [0.147 0.853 0. 0. ] | 3.1581e-76 | 3.1581e-76 | 0 | [0.147 0.853] | 0.147 |
-| (0.0, 83) | 0.0831914 | 0.0558086 | 0.139 | [0.139 0.861 0. 0. ] | 1.71931e-86 | 1.71931e-86 | 0 | [0.139 0.861] | 0.139 |
-| (0.0, 84) | 0.120851 | 0.0331487 | 0.154 | [0.154 0.846 0. 0. ] | 7.23765e-74 | 7.23765e-74 | 0 | [0.154 0.846] | 0.154 |
-| (0.0, 85) | 0.100605 | 0.0433947 | 0.144 | [0.144 0.856 0. 0. ] | 2.67006e-82 | 2.67006e-82 | 0 | [0.144 0.856] | 0.144 |
-| (0.0, 86) | 0.0765061 | 0.0734939 | 0.15 | [0.15 0.85 0. 0. ] | 1.61559e-83 | 1.61559e-83 | 0 | [0.15 0.85] | 0.15 |
-| (0.0, 87) | 0.0705979 | 0.0724021 | 0.143 | [0.143 0.857 0. 0. ] | 6.80161e-90 | 6.80161e-90 | 0 | [0.143 0.857] | 0.143 |
-| (0.0, 88) | 0.133956 | 0.0270437 | 0.161 | [0.161 0.839 0. 0. ] | 4.02932e-85 | 4.02932e-85 | 0 | [0.161 0.839] | 0.161 |
-| (0.0, 89) | 0.0874214 | 0.0665786 | 0.154 | [0.154 0.846 0. 0. ] | 5.57476e-68 | 5.57476e-68 | 0 | [0.154 0.846] | 0.154 |
-| (0.0, 90) | 0.0715817 | 0.0634183 | 0.135 | [0.135 0.865 0. 0. ] | 4.40147e-76 | 4.40147e-76 | 0 | [0.135 0.865] | 0.135 |
-| (0.0, 91) | 0.0905213 | 0.0544787 | 0.145 | [0.145 0.855 0. 0. ] | 5.28556e-78 | 5.28556e-78 | 0 | [0.145 0.855] | 0.145 |
-| (0.0, 92) | 0.0795437 | 0.0964563 | 0.176 | [0.176 0.824 0. 0. ] | 1.1435e-87 | 1.1435e-87 | 0 | [0.176 0.824] | 0.176 |
-| (0.0, 93) | 0.118409 | 0.0365913 | 0.155 | [0.155 0.845 0. 0. ] | 3.5294e-95 | 3.5294e-95 | 0 | [0.155 0.845] | 0.155 |
-| (0.0, 94) | 0.109805 | 0.0591953 | 0.169 | [0.169 0.831 0. 0. ] | 1.80285e-76 | 1.80285e-76 | 0 | [0.169 0.831] | 0.169 |
-| (0.0, 95) | 0.098196 | 0.052804 | 0.151 | [0.151 0.849 0. 0. ] | 2.818e-84 | 2.818e-84 | 0 | [0.151 0.849] | 0.151 |
-| (0.0, 96) | 0.112439 | 0.0345615 | 0.147 | [0.147 0.853 0. 0. ] | 3.6936e-71 | 3.6936e-71 | 0 | [0.147 0.853] | 0.147 |
-| (0.0, 97) | 0.0904939 | 0.0645061 | 0.155 | [0.155 0.845 0. 0. ] | 8.14262e-94 | 8.14262e-94 | 0 | [0.155 0.845] | 0.155 |
-| (0.0, 98) | 0.107304 | 0.028696 | 0.136 | [0.136 0.864 0. 0. ] | 7.45097e-62 | 7.45097e-62 | 0 | [0.136 0.864] | 0.136 |
-| (0.0, 99) | 0.0726854 | 0.0783146 | 0.151 | [0.151 0.849 0. 0. ] | 1.27965e-92 | 1.27965e-92 | 0 | [0.151 0.849] | 0.151 |
-| (0.05, 0) | 0.139695 | 0.0533047 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 1.14176e-19 | 0.110254 | [0.143 0.857] | 0.193 |
-| (0.05, 1) | 0.135563 | 0.0344375 | 0.17 | [0.12 0.83 0. 0.05] | 0.107527 | 3.58656e-10 | 0.107527 | [0.12 0.88] | 0.17 |
-| (0.05, 2) | 0.140995 | 0.0510053 | 0.192 | [0.142 0.808 0. 0.05 ] | 0.110132 | 2.74753e-22 | 0.110132 | [0.142 0.858] | 0.192 |
-| (0.05, 3) | 0.137862 | 0.0681381 | 0.206 | [0.156 0.794 0. 0.05 ] | 0.111857 | 1.58351e-10 | 0.111857 | [0.156 0.844] | 0.206 |
-| (0.05, 4) | 0.106135 | 0.0828645 | 0.189 | [0.139 0.811 0. 0.05 ] | 0.109234 | 0.000535505 | 0.109769 | [0.139 0.861] | 0.189 |
-| (0.05, 5) | 0.122517 | 0.0634832 | 0.186 | [0.136 0.814 0. 0.05 ] | 0.109409 | 4.44136e-17 | 0.109409 | [0.136 0.864] | 0.186 |
-| (0.05, 6) | 0.156419 | 0.0255809 | 0.182 | [0.132 0.818 0. 0.05 ] | 0.108932 | 3.43807e-18 | 0.108932 | [0.132 0.868] | 0.182 |
-| (0.05, 7) | 0.145084 | 0.0439162 | 0.189 | [0.139 0.811 0. 0.05 ] | 0.109769 | 2.65993e-14 | 0.109769 | [0.139 0.861] | 0.189 |
-| (0.05, 8) | 0.155093 | 0.0359071 | 0.191 | [0.142 0.808 0.001 0.049] | 0.108049 | 4.59776e-11 | 0.108049 | [0.143 0.857] | 0.191 |
-| (0.05, 9) | 0.182126 | 0.00487421 | 0.187 | [0.137 0.813 0. 0.05 ] | 0.109529 | 1.84496e-14 | 0.109529 | [0.137 0.863] | 0.187 |
-| (0.05, 10) | 0.0998061 | 0.0921939 | 0.192 | [0.142 0.808 0. 0.05 ] | 0.110132 | 4.03461e-21 | 0.110132 | [0.142 0.858] | 0.192 |
-| (0.05, 11) | 0.135749 | 0.0592513 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 3.16984e-21 | 0.110497 | [0.145 0.855] | 0.195 |
-| (0.05, 12) | 0.115695 | 0.087305 | 0.203 | [0.153 0.797 0. 0.05 ] | 0.111483 | 1.33398e-15 | 0.111483 | [0.153 0.847] | 0.203 |
-| (0.05, 13) | 0.132882 | 0.0491177 | 0.182 | [0.132 0.818 0. 0.05 ] | 0.108932 | 3.836e-24 | 0.108932 | [0.132 0.868] | 0.182 |
-| (0.05, 14) | 0.10577 | 0.0692296 | 0.175 | [0.125 0.825 0. 0.05 ] | 0.108108 | 9.72476e-12 | 0.108108 | [0.125 0.875] | 0.175 |
-| (0.05, 15) | 0.156678 | 0.036322 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 2.07272e-23 | 0.110254 | [0.143 0.857] | 0.193 |
-| (0.05, 16) | 0.104347 | 0.0826534 | 0.187 | [0.137 0.813 0. 0.05 ] | 0.107933 | 0.00159586 | 0.109529 | [0.137 0.863] | 0.187 |
-| (0.05, 17) | 0.169004 | 0.00799577 | 0.177 | [0.127 0.823 0. 0.05 ] | 0.108342 | 7.79333e-11 | 0.108342 | [0.127 0.873] | 0.177 |
-| (0.05, 18) | 0.128698 | 0.0653016 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 1.77321e-22 | 0.110375 | [0.144 0.856] | 0.194 |
-| (0.05, 19) | 0.111877 | 0.0971234 | 0.209 | [0.159 0.791 0. 0.05 ] | 0.112233 | 2.68131e-19 | 0.112233 | [0.159 0.841] | 0.209 |
-| (0.05, 20) | 0.155026 | 0.0209742 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.108225 | 3.94502e-18 | 0.108225 | [0.126 0.874] | 0.176 |
-| (0.05, 21) | 0.124618 | 0.0773818 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111359 | 9.0121e-31 | 0.111359 | [0.152 0.848] | 0.202 |
-| (0.05, 22) | 0.130664 | 0.0603363 | 0.191 | [0.141 0.809 0. 0.05 ] | 0.110011 | 3.03675e-22 | 0.110011 | [0.141 0.859] | 0.191 |
-| (0.05, 23) | 0.154081 | 0.0469192 | 0.201 | [0.151 0.799 0. 0.05 ] | 0.111235 | 2.16643e-11 | 0.111235 | [0.151 0.849] | 0.201 |
-| (0.05, 24) | 0.122652 | 0.059348 | 0.182 | [0.132 0.818 0. 0.05 ] | 0.108932 | 1.6966e-14 | 0.108932 | [0.132 0.868] | 0.182 |
-| (0.05, 25) | 0.146311 | 0.055689 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111355 | 3.46681e-06 | 0.111359 | [0.152 0.848] | 0.202 |
-| (0.05, 26) | 0.140658 | 0.0373423 | 0.178 | [0.128 0.822 0. 0.05 ] | 0.10846 | 2.48311e-18 | 0.10846 | [0.128 0.872] | 0.178 |
-| (0.05, 27) | 0.134002 | 0.0429984 | 0.177 | [0.127 0.823 0. 0.05 ] | 0.108342 | 9.19174e-20 | 0.108342 | [0.127 0.873] | 0.177 |
-| (0.05, 28) | 0.157105 | 0.0368953 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 4.83413e-18 | 0.110375 | [0.144 0.856] | 0.194 |
-| (0.05, 29) | 0.149111 | 0.0308887 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 1.16102e-21 | 0.108696 | [0.13 0.87] | 0.18 |
-| (0.05, 30) | 0.104365 | 0.0786353 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 1.10507e-14 | 0.109051 | [0.133 0.867] | 0.183 |
-| (0.05, 31) | 0.158109 | 0.041891 | 0.2 | [0.151 0.799 0.001 0.049] | 0.109131 | 8.10113e-19 | 0.109131 | [0.152 0.848] | 0.2 |
-| (0.05, 32) | 0.14954 | 0.0294602 | 0.179 | [0.129 0.821 0. 0.05 ] | 0.108578 | 1.28469e-14 | 0.108578 | [0.129 0.871] | 0.179 |
-| (0.05, 33) | 0.157869 | 0.0161307 | 0.174 | [0.124 0.826 0. 0.05 ] | 0.107991 | 7.84528e-18 | 0.107991 | [0.124 0.876] | 0.174 |
-| (0.05, 34) | 0.157753 | 0.039247 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 2.2032e-17 | 0.110742 | [0.147 0.853] | 0.197 |
-| (0.05, 35) | 0.134724 | 0.0462759 | 0.181 | [0.131 0.819 0. 0.05 ] | 0.108814 | 1.46e-14 | 0.108814 | [0.131 0.869] | 0.181 |
-| (0.05, 36) | 0.14284 | 0.0331603 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.108225 | 3.56508e-16 | 0.108225 | [0.126 0.874] | 0.176 |
-| (0.05, 37) | 0.135851 | 0.0541488 | 0.19 | [0.14 0.81 0. 0.05] | 0.10989 | 1.37439e-14 | 0.10989 | [0.14 0.86] | 0.19 |
-| (0.05, 38) | 0.120848 | 0.0871521 | 0.208 | [0.158 0.792 0. 0.05 ] | 0.112108 | 3.07361e-10 | 0.112108 | [0.158 0.842] | 0.208 |
-| (0.05, 39) | 0.108411 | 0.071589 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 9.4529e-12 | 0.108696 | [0.13 0.87] | 0.18 |
-| (0.05, 40) | 0.138167 | 0.0358328 | 0.174 | [0.124 0.826 0. 0.05 ] | 0.107991 | 3.92459e-22 | 0.107991 | [0.124 0.876] | 0.174 |
-| (0.05, 41) | 0.134067 | 0.0729327 | 0.207 | [0.157 0.793 0. 0.05 ] | 0.111982 | 6.75036e-30 | 0.111982 | [0.157 0.843] | 0.207 |
-| (0.05, 42) | 0.172425 | 0.0235747 | 0.196 | [0.146 0.804 0. 0.05 ] | 0.110619 | 1.7918e-18 | 0.110619 | [0.146 0.854] | 0.196 |
-| (0.05, 43) | 0.137972 | 0.0540283 | 0.192 | [0.142 0.808 0. 0.05 ] | 0.110132 | 6.253e-19 | 0.110132 | [0.142 0.858] | 0.192 |
-| (0.05, 44) | 0.128741 | 0.0542591 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 1.05882e-23 | 0.109051 | [0.133 0.867] | 0.183 |
-| (0.05, 45) | 0.138375 | 0.0376248 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.108225 | 4.84466e-15 | 0.108225 | [0.126 0.874] | 0.176 |
-| (0.05, 46) | 0.162737 | 0.0232628 | 0.186 | [0.136 0.814 0. 0.05 ] | 0.109389 | 2.06901e-05 | 0.109409 | [0.136 0.864] | 0.186 |
-| (0.05, 47) | 0.145798 | 0.0382015 | 0.184 | [0.134 0.816 0. 0.05 ] | 0.10917 | 2.78441e-27 | 0.10917 | [0.134 0.866] | 0.184 |
-| (0.05, 48) | 0.137354 | 0.0726463 | 0.21 | [0.16 0.79 0. 0.05] | 0.11236 | 2.97923e-25 | 0.11236 | [0.16 0.84] | 0.21 |
-| (0.05, 49) | 0.155531 | 0.0394693 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 3.57224e-19 | 0.110497 | [0.145 0.855] | 0.195 |
-| (0.05, 50) | 0.165329 | 0.0146715 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 7.05554e-15 | 0.108696 | [0.13 0.87] | 0.18 |
-| (0.05, 51) | 0.107478 | 0.0715223 | 0.179 | [0.129 0.821 0. 0.05 ] | 0.108578 | 2.33682e-16 | 0.108578 | [0.129 0.871] | 0.179 |
-| (0.05, 52) | 0.0938284 | 0.0901716 | 0.184 | [0.134 0.816 0. 0.05 ] | 0.108422 | 0.000747907 | 0.10917 | [0.134 0.866] | 0.184 |
-| (0.05, 53) | 0.137715 | 0.0582849 | 0.196 | [0.146 0.804 0. 0.05 ] | 0.110619 | 9.415e-15 | 0.110619 | [0.146 0.854] | 0.196 |
-| (0.05, 54) | 0.152119 | 0.0308814 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 3.14673e-08 | 0.109051 | [0.133 0.867] | 0.183 |
-| (0.05, 55) | 0.17551 | 0.0224896 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 2.44773e-14 | 0.110865 | [0.148 0.852] | 0.198 |
-| (0.05, 56) | 0.180796 | 0.0172042 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 7.30979e-13 | 0.110865 | [0.148 0.852] | 0.198 |
-| (0.05, 57) | 0.129629 | 0.0533714 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 7.45796e-26 | 0.109051 | [0.133 0.867] | 0.183 |
-| (0.05, 58) | 0.163147 | 0.016853 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 2.66764e-19 | 0.108696 | [0.13 0.87] | 0.18 |
-| (0.05, 59) | 0.0869485 | 0.103052 | 0.19 | [0.14 0.81 0. 0.05] | 0.109035 | 0.000854853 | 0.10989 | [0.14 0.86] | 0.19 |
-| (0.05, 60) | 0.149196 | 0.0458035 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 1.89128e-15 | 0.110497 | [0.145 0.855] | 0.195 |
-| (0.05, 61) | 0.126469 | 0.0565306 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 1.04909e-16 | 0.109051 | [0.133 0.867] | 0.183 |
-| (0.05, 62) | 0.172479 | 0.0155209 | 0.188 | [0.139 0.811 0.001 0.049] | 0.107692 | 3.99895e-09 | 0.107692 | [0.14 0.86] | 0.188 |
-| (0.05, 63) | 0.0976526 | 0.0803474 | 0.178 | [0.128 0.822 0. 0.05 ] | 0.10846 | 1.72691e-33 | 0.10846 | [0.128 0.872] | 0.178 |
-| (0.05, 64) | 0.118217 | 0.0667828 | 0.185 | [0.135 0.815 0. 0.05 ] | 0.10929 | 3.28193e-14 | 0.10929 | [0.135 0.865] | 0.185 |
-| (0.05, 65) | 0.0917532 | 0.0912468 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.1084 | 0.000651129 | 0.109051 | [0.133 0.867] | 0.183 |
-| (0.05, 66) | 0.0971105 | 0.0788895 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.107692 | 0.000532613 | 0.108225 | [0.126 0.874] | 0.176 |
-| (0.05, 67) | 0.107754 | 0.0802459 | 0.188 | [0.138 0.812 0. 0.05 ] | 0.109269 | 0.000379747 | 0.109649 | [0.138 0.862] | 0.188 |
-| (0.05, 68) | 0.153214 | 0.0267861 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 1.06491e-21 | 0.108696 | [0.13 0.87] | 0.18 |
-| (0.05, 69) | 0.140475 | 0.0495245 | 0.19 | [0.14 0.81 0. 0.05] | 0.10989 | 2.79207e-20 | 0.10989 | [0.14 0.86] | 0.19 |
-| (0.05, 70) | 0.145541 | 0.0454591 | 0.191 | [0.141 0.809 0. 0.05 ] | 0.110011 | 2.75263e-10 | 0.110011 | [0.141 0.859] | 0.191 |
-| (0.05, 71) | 0.155227 | 0.0187734 | 0.174 | [0.124 0.826 0. 0.05 ] | 0.107991 | 4.71961e-12 | 0.107991 | [0.124 0.876] | 0.174 |
-| (0.05, 72) | 0.154241 | 0.0667593 | 0.221 | [0.171 0.779 0. 0.05 ] | 0.113766 | 6.45733e-22 | 0.113766 | [0.171 0.829] | 0.221 |
-| (0.05, 73) | 0.149282 | 0.0537176 | 0.203 | [0.153 0.797 0. 0.05 ] | 0.111483 | 5.42307e-08 | 0.111483 | [0.153 0.847] | 0.203 |
-| (0.05, 74) | 0.112973 | 0.0600274 | 0.173 | [0.123 0.827 0. 0.05 ] | 0.107875 | 3.72521e-13 | 0.107875 | [0.123 0.877] | 0.173 |
-| (0.05, 75) | 0.118677 | 0.0783229 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 2.40661e-16 | 0.110742 | [0.147 0.853] | 0.197 |
-| (0.05, 76) | 0.118952 | 0.0800475 | 0.199 | [0.149 0.801 0. 0.05 ] | 0.110988 | 6.3083e-23 | 0.110988 | [0.149 0.851] | 0.199 |
-| (0.05, 77) | 0.147543 | 0.0464572 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 1.67292e-16 | 0.110375 | [0.144 0.856] | 0.194 |
-| (0.05, 78) | 0.157932 | 0.0350678 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 1.80691e-27 | 0.110254 | [0.143 0.857] | 0.193 |
-| (0.05, 79) | 0.10977 | 0.0872304 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 4.64983e-19 | 0.110742 | [0.147 0.853] | 0.197 |
-| (0.05, 80) | 0.110754 | 0.0802464 | 0.191 | [0.141 0.809 0. 0.05 ] | 0.110011 | 6.39424e-18 | 0.110011 | [0.141 0.859] | 0.191 |
-| (0.05, 81) | 0.156431 | 0.041569 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 7.35924e-18 | 0.110865 | [0.148 0.852] | 0.198 |
-| (0.05, 82) | 0.154779 | 0.0442212 | 0.199 | [0.149 0.801 0. 0.05 ] | 0.110988 | 6.42816e-10 | 0.110988 | [0.149 0.851] | 0.199 |
-| (0.05, 83) | 0.126509 | 0.0814906 | 0.208 | [0.158 0.792 0. 0.05 ] | 0.112108 | 1.30576e-17 | 0.112108 | [0.158 0.842] | 0.208 |
-| (0.05, 84) | 0.136929 | 0.0700712 | 0.207 | [0.158 0.792 0.001 0.049] | 0.109989 | 1.45571e-22 | 0.109989 | [0.159 0.841] | 0.207 |
-| (0.05, 85) | 0.150736 | 0.0462638 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 1.26775e-15 | 0.110742 | [0.147 0.853] | 0.197 |
-| (0.05, 86) | 0.13535 | 0.0666503 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111359 | 1.52258e-16 | 0.111359 | [0.152 0.848] | 0.202 |
-| (0.05, 87) | 0.154934 | 0.0240656 | 0.179 | [0.129 0.821 0. 0.05 ] | 0.108578 | 7.65988e-15 | 0.108578 | [0.129 0.871] | 0.179 |
-| (0.05, 88) | 0.107502 | 0.0654985 | 0.173 | [0.123 0.827 0. 0.05 ] | 0.107875 | 1.44443e-19 | 0.107875 | [0.123 0.877] | 0.173 |
-| (0.05, 89) | 0.148545 | 0.0474553 | 0.196 | [0.146 0.804 0. 0.05 ] | 0.110619 | 1.7763e-27 | 0.110619 | [0.146 0.854] | 0.196 |
-| (0.05, 90) | 0.118629 | 0.0533714 | 0.172 | [0.122 0.828 0. 0.05 ] | 0.107759 | 1.68968e-12 | 0.107759 | [0.122 0.878] | 0.172 |
-| (0.05, 91) | 0.120002 | 0.0739985 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 2.31969e-15 | 0.110375 | [0.144 0.856] | 0.194 |
-| (0.05, 92) | 0.11476 | 0.0782402 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 3.75623e-20 | 0.110254 | [0.143 0.857] | 0.193 |
-| (0.05, 93) | 0.128018 | 0.0719818 | 0.2 | [0.15 0.8 0. 0.05] | 0.111111 | 3.18359e-20 | 0.111111 | [0.15 0.85] | 0.2 |
-| (0.05, 94) | 0.104735 | 0.0972647 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111359 | 4.15272e-22 | 0.111359 | [0.152 0.848] | 0.202 |
-| (0.05, 95) | 0.14863 | 0.0313704 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 5.0643e-17 | 0.108696 | [0.13 0.87] | 0.18 |
-| (0.05, 96) | 0.155999 | 0.0390008 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 3.38826e-17 | 0.110497 | [0.145 0.855] | 0.195 |
-| (0.05, 97) | 0.121559 | 0.0774405 | 0.199 | [0.149 0.801 0. 0.05 ] | 0.110988 | 8.6301e-15 | 0.110988 | [0.149 0.851] | 0.199 |
-| (0.05, 98) | 0.107171 | 0.0908294 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 2.90772e-18 | 0.110865 | [0.148 0.852] | 0.198 |
-| (0.05, 99) | 0.155625 | 0.0373746 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 2.24989e-10 | 0.110254 | [0.143 0.857] | 0.193 |
-| (0.1, 0) | 0.178993 | 0.0430075 | 0.222 | [0.122 0.778 0. 0.1 ] | 0.144324 | 0.0601746 | 0.204499 | [0.122 0.878] | 0.222 |
-| (0.1, 1) | 0.152454 | 0.0715457 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.143947 | 0.0609715 | 0.204918 | [0.124 0.876] | 0.224 |
-| (0.1, 2) | 0.157962 | 0.0720383 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.189546 | 0.0166395 | 0.206186 | [0.13 0.87] | 0.23 |
-| (0.1, 3) | 0.140091 | 0.103909 | 0.244 | [0.144 0.756 0. 0.1 ] | 0.16705 | 0.042155 | 0.209205 | [0.144 0.856] | 0.244 |
-| (0.1, 4) | 0.146193 | 0.0908066 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.144253 | 0.063431 | 0.207684 | [0.137 0.863] | 0.237 |
-| (0.1, 5) | 0.149072 | 0.0789285 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.166733 | 0.0390282 | 0.205761 | [0.128 0.872] | 0.228 |
-| (0.1, 6) | 0.138868 | 0.0971322 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.146507 | 0.0609615 | 0.207469 | [0.136 0.864] | 0.236 |
-| (0.1, 7) | 0.155198 | 0.0728022 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.166977 | 0.0387839 | 0.205761 | [0.128 0.872] | 0.228 |
-| (0.1, 8) | 0.155993 | 0.0650068 | 0.221 | [0.121 0.779 0. 0.1 ] | 0.142876 | 0.0614141 | 0.20429 | [0.121 0.879] | 0.221 |
-| (0.1, 9) | 0.142102 | 0.0838979 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.161065 | 0.0442743 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 10) | 0.173001 | 0.0689987 | 0.242 | [0.142 0.758 0. 0.1 ] | 0.158182 | 0.0505862 | 0.208768 | [0.142 0.858] | 0.242 |
-| (0.1, 11) | 0.137157 | 0.114843 | 0.252 | [0.152 0.748 0. 0.1 ] | 0.17158 | 0.0393908 | 0.21097 | [0.152 0.848] | 0.252 |
-| (0.1, 12) | 0.139662 | 0.103338 | 0.243 | [0.143 0.757 0. 0.1 ] | 0.138507 | 0.0704791 | 0.208986 | [0.143 0.857] | 0.243 |
-| (0.1, 13) | 0.158423 | 0.0895769 | 0.248 | [0.149 0.751 0.001 0.099] | 0.190184 | 0.0182375 | 0.208421 | [0.15 0.85] | 0.248 |
-| (0.1, 14) | 0.12466 | 0.10934 | 0.234 | [0.134 0.766 0. 0.1 ] | 0.139225 | 0.0678139 | 0.207039 | [0.134 0.866] | 0.234 |
-| (0.1, 15) | 0.159436 | 0.0755636 | 0.235 | [0.135 0.765 0. 0.1 ] | 0.136966 | 0.0702877 | 0.207254 | [0.135 0.865] | 0.235 |
-| (0.1, 16) | 0.140571 | 0.0874287 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.1321 | 0.073661 | 0.205761 | [0.128 0.872] | 0.228 |
-| (0.1, 17) | 0.133351 | 0.0936495 | 0.227 | [0.127 0.773 0. 0.1 ] | 0.145652 | 0.0598978 | 0.20555 | [0.127 0.873] | 0.227 |
-| (0.1, 18) | 0.153178 | 0.074822 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.15928 | 0.0464809 | 0.205761 | [0.128 0.872] | 0.228 |
-| (0.1, 19) | 0.16243 | 0.0635701 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.14073 | 0.0646092 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 20) | 0.162509 | 0.0814913 | 0.244 | [0.144 0.756 0. 0.1 ] | 0.160787 | 0.0484177 | 0.209205 | [0.144 0.856] | 0.244 |
-| (0.1, 21) | 0.122019 | 0.109981 | 0.232 | [0.133 0.767 0.001 0.099] | 0.146363 | 0.058606 | 0.204969 | [0.134 0.866] | 0.232 |
-| (0.1, 22) | 0.164098 | 0.0729024 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.142794 | 0.0648901 | 0.207684 | [0.137 0.863] | 0.237 |
-| (0.1, 23) | 0.13655 | 0.10945 | 0.246 | [0.146 0.754 0. 0.1 ] | 0.133593 | 0.0760508 | 0.209644 | [0.146 0.854] | 0.246 |
-| (0.1, 24) | 0.156787 | 0.0702127 | 0.227 | [0.127 0.773 0. 0.1 ] | 0.162406 | 0.0431439 | 0.20555 | [0.127 0.873] | 0.227 |
-| (0.1, 25) | 0.142566 | 0.103434 | 0.246 | [0.146 0.754 0. 0.1 ] | 0.161656 | 0.0479876 | 0.209644 | [0.146 0.854] | 0.246 |
-| (0.1, 26) | 0.16276 | 0.0772395 | 0.24 | [0.14 0.76 0. 0.1 ] | 0.128966 | 0.0793677 | 0.208333 | [0.14 0.86] | 0.24 |
-| (0.1, 27) | 0.125019 | 0.0889812 | 0.214 | [0.114 0.786 0. 0.1 ] | 0.169924 | 0.0329159 | 0.20284 | [0.114 0.886] | 0.214 |
-| (0.1, 28) | 0.141623 | 0.101377 | 0.243 | [0.143 0.757 0. 0.1 ] | 0.131695 | 0.077291 | 0.208986 | [0.143 0.857] | 0.243 |
-| (0.1, 29) | 0.196429 | 0.0525706 | 0.249 | [0.149 0.751 0. 0.1 ] | 0.155012 | 0.0552926 | 0.210305 | [0.149 0.851] | 0.249 |
-| (0.1, 30) | 0.14666 | 0.10034 | 0.247 | [0.147 0.753 0. 0.1 ] | 0.134494 | 0.0753696 | 0.209864 | [0.147 0.853] | 0.247 |
-| (0.1, 31) | 0.138889 | 0.111111 | 0.25 | [0.151 0.749 0.001 0.099] | 0.122134 | 0.0867272 | 0.208861 | [0.152 0.848] | 0.25 |
-| (0.1, 32) | 0.14235 | 0.10065 | 0.243 | [0.144 0.756 0.001 0.099] | 0.125462 | 0.0818674 | 0.20733 | [0.145 0.855] | 0.243 |
-| (0.1, 33) | 0.149198 | 0.0748024 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.138851 | 0.0660671 | 0.204918 | [0.124 0.876] | 0.224 |
-| (0.1, 34) | 0.183632 | 0.0423683 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.165968 | 0.0393708 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 35) | 0.109742 | 0.131258 | 0.241 | [0.141 0.759 0. 0.1 ] | 0.124891 | 0.0836592 | 0.208551 | [0.141 0.859] | 0.241 |
-| (0.1, 36) | 0.119279 | 0.103721 | 0.223 | [0.123 0.777 0. 0.1 ] | 0.158427 | 0.0462817 | 0.204708 | [0.123 0.877] | 0.223 |
-| (0.1, 37) | 0.176492 | 0.0365084 | 0.213 | [0.113 0.787 0. 0.1 ] | 0.158593 | 0.0440417 | 0.202634 | [0.113 0.887] | 0.213 |
-| (0.1, 38) | 0.13036 | 0.09864 | 0.229 | [0.129 0.771 0. 0.1 ] | 0.151765 | 0.0542087 | 0.205973 | [0.129 0.871] | 0.229 |
-| (0.1, 39) | 0.143694 | 0.0773055 | 0.221 | [0.121 0.779 0. 0.1 ] | 0.152654 | 0.0516359 | 0.20429 | [0.121 0.879] | 0.221 |
-| (0.1, 40) | 0.176925 | 0.0620751 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.173127 | 0.0349899 | 0.208117 | [0.139 0.861] | 0.239 |
-| (0.1, 41) | 0.161501 | 0.0714994 | 0.233 | [0.133 0.767 0. 0.1 ] | 0.141467 | 0.0653583 | 0.206825 | [0.133 0.867] | 0.233 |
-| (0.1, 42) | 0.174647 | 0.0573527 | 0.232 | [0.133 0.767 0.001 0.099] | 0.163408 | 0.0415608 | 0.204969 | [0.134 0.866] | 0.232 |
-| (0.1, 43) | 0.167175 | 0.0718247 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.144039 | 0.0640772 | 0.208117 | [0.139 0.861] | 0.239 |
-| (0.1, 44) | 0.178495 | 0.0705051 | 0.249 | [0.149 0.751 0. 0.1 ] | 0.167393 | 0.0429116 | 0.210305 | [0.149 0.851] | 0.249 |
-| (0.1, 45) | 0.136153 | 0.0988467 | 0.235 | [0.135 0.765 0. 0.1 ] | 0.143173 | 0.0640808 | 0.207254 | [0.135 0.865] | 0.235 |
-| (0.1, 46) | 0.160061 | 0.0699394 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.160817 | 0.045369 | 0.206186 | [0.13 0.87] | 0.23 |
-| (0.1, 47) | 0.14961 | 0.0743897 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.125738 | 0.07918 | 0.204918 | [0.124 0.876] | 0.224 |
-| (0.1, 48) | 0.151283 | 0.0817166 | 0.233 | [0.133 0.767 0. 0.1 ] | 0.15867 | 0.0481552 | 0.206825 | [0.133 0.867] | 0.233 |
-| (0.1, 49) | 0.104849 | 0.132151 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.145601 | 0.062083 | 0.207684 | [0.137 0.863] | 0.237 |
-| (0.1, 50) | 0.137846 | 0.0781539 | 0.216 | [0.116 0.784 0. 0.1 ] | 0.159667 | 0.0435852 | 0.203252 | [0.116 0.884] | 0.216 |
-| (0.1, 51) | 0.165942 | 0.066058 | 0.232 | [0.132 0.768 0. 0.1 ] | 0.172122 | 0.0344898 | 0.206612 | [0.132 0.868] | 0.232 |
-| (0.1, 52) | 0.171149 | 0.042851 | 0.214 | [0.114 0.786 0. 0.1 ] | 0.162734 | 0.0401054 | 0.20284 | [0.114 0.886] | 0.214 |
-| (0.1, 53) | 0.154402 | 0.0895978 | 0.244 | [0.144 0.756 0. 0.1 ] | 0.145084 | 0.0641207 | 0.209205 | [0.144 0.856] | 0.244 |
-| (0.1, 54) | 0.142341 | 0.0896587 | 0.232 | [0.132 0.768 0. 0.1 ] | 0.15741 | 0.0492015 | 0.206612 | [0.132 0.868] | 0.232 |
-| (0.1, 55) | 0.125124 | 0.120876 | 0.246 | [0.146 0.754 0. 0.1 ] | 0.152008 | 0.0576355 | 0.209644 | [0.146 0.854] | 0.246 |
-| (0.1, 56) | 0.123448 | 0.106552 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.142112 | 0.0640739 | 0.206186 | [0.13 0.87] | 0.23 |
-| (0.1, 57) | 0.142486 | 0.0985143 | 0.241 | [0.142 0.758 0.001 0.099] | 0.172454 | 0.0344422 | 0.206897 | [0.143 0.857] | 0.241 |
-| (0.1, 58) | 0.1401 | 0.0999001 | 0.24 | [0.14 0.76 0. 0.1 ] | 0.162622 | 0.0457112 | 0.208333 | [0.14 0.86] | 0.24 |
-| (0.1, 59) | 0.136005 | 0.0989948 | 0.235 | [0.135 0.765 0. 0.1 ] | 0.113088 | 0.0941657 | 0.207254 | [0.135 0.865] | 0.235 |
-| (0.1, 60) | 0.164363 | 0.0656372 | 0.23 | [0.132 0.768 0.002 0.098] | 0.144721 | 0.0581779 | 0.202899 | [0.134 0.866] | 0.23 |
-| (0.1, 61) | 0.147789 | 0.102211 | 0.25 | [0.15 0.75 0. 0.1 ] | 0.120903 | 0.0896233 | 0.210526 | [0.15 0.85] | 0.25 |
-| (0.1, 62) | 0.171044 | 0.0549561 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.178233 | 0.0271061 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 63) | 0.163507 | 0.0704927 | 0.234 | [0.134 0.766 0. 0.1 ] | 0.158086 | 0.048953 | 0.207039 | [0.134 0.866] | 0.234 |
-| (0.1, 64) | 0.110106 | 0.136894 | 0.247 | [0.147 0.753 0. 0.1 ] | 0.131224 | 0.07864 | 0.209864 | [0.147 0.853] | 0.247 |
-| (0.1, 65) | 0.116124 | 0.113876 | 0.23 | [0.132 0.768 0.002 0.098] | 0.160052 | 0.0428462 | 0.202899 | [0.134 0.866] | 0.23 |
-| (0.1, 66) | 0.148545 | 0.0964552 | 0.245 | [0.145 0.755 0. 0.1 ] | 0.153694 | 0.0557301 | 0.209424 | [0.145 0.855] | 0.245 |
-| (0.1, 67) | 0.147949 | 0.0880511 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.120853 | 0.086616 | 0.207469 | [0.136 0.864] | 0.236 |
-| (0.1, 68) | 0.159105 | 0.066895 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.166105 | 0.0392333 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 69) | 0.133635 | 0.0993651 | 0.233 | [0.133 0.767 0. 0.1 ] | 0.13905 | 0.0677752 | 0.206825 | [0.133 0.867] | 0.233 |
-| (0.1, 70) | 0.136221 | 0.0947786 | 0.231 | [0.131 0.769 0. 0.1 ] | 0.158557 | 0.0478413 | 0.206398 | [0.131 0.869] | 0.231 |
-| (0.1, 71) | 0.173515 | 0.0564854 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.154365 | 0.0518201 | 0.206186 | [0.13 0.87] | 0.23 |
-| (0.1, 72) | 0.16392 | 0.0540796 | 0.218 | [0.118 0.782 0. 0.1 ] | 0.145843 | 0.0578235 | 0.203666 | [0.118 0.882] | 0.218 |
-| (0.1, 73) | 0.15042 | 0.0985805 | 0.249 | [0.149 0.751 0. 0.1 ] | 0.160302 | 0.0500027 | 0.210305 | [0.149 0.851] | 0.249 |
-| (0.1, 74) | 0.162813 | 0.0761868 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.158843 | 0.0492734 | 0.208117 | [0.139 0.861] | 0.239 |
-| (0.1, 75) | 0.13747 | 0.10053 | 0.238 | [0.138 0.762 0. 0.1 ] | 0.161175 | 0.046725 | 0.2079 | [0.138 0.862] | 0.238 |
-| (0.1, 76) | 0.145291 | 0.0577093 | 0.203 | [0.103 0.797 0. 0.1 ] | 0.149275 | 0.0513268 | 0.200602 | [0.103 0.897] | 0.203 |
-| (0.1, 77) | 0.162521 | 0.0464792 | 0.209 | [0.109 0.791 0. 0.1 ] | 0.160017 | 0.041799 | 0.201816 | [0.109 0.891] | 0.209 |
-| (0.1, 78) | 0.173875 | 0.0691247 | 0.243 | [0.143 0.757 0. 0.1 ] | 0.172443 | 0.0365437 | 0.208986 | [0.143 0.857] | 0.243 |
-| (0.1, 79) | 0.167891 | 0.0681092 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.164834 | 0.0426348 | 0.207469 | [0.136 0.864] | 0.236 |
-| (0.1, 80) | 0.105674 | 0.122326 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.141365 | 0.0643962 | 0.205761 | [0.128 0.872] | 0.228 |
-| (0.1, 81) | 0.146952 | 0.0890479 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.146061 | 0.0614083 | 0.207469 | [0.136 0.864] | 0.236 |
-| (0.1, 82) | 0.161609 | 0.0743909 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.157538 | 0.0499308 | 0.207469 | [0.136 0.864] | 0.236 |
-| (0.1, 83) | 0.133117 | 0.103883 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.140087 | 0.0675969 | 0.207684 | [0.137 0.863] | 0.237 |
-| (0.1, 84) | 0.105845 | 0.133155 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.134486 | 0.0736308 | 0.208117 | [0.139 0.861] | 0.239 |
-| (0.1, 85) | 0.149457 | 0.0795428 | 0.229 | [0.129 0.771 0. 0.1 ] | 0.152163 | 0.05381 | 0.205973 | [0.129 0.871] | 0.229 |
-| (0.1, 86) | 0.155383 | 0.075617 | 0.231 | [0.131 0.769 0. 0.1 ] | 0.142288 | 0.0641102 | 0.206398 | [0.131 0.869] | 0.231 |
-| (0.1, 87) | 0.152283 | 0.0677166 | 0.22 | [0.12 0.78 0. 0.1 ] | 0.136019 | 0.0680626 | 0.204082 | [0.12 0.88] | 0.22 |
-| (0.1, 88) | 0.155228 | 0.0857723 | 0.241 | [0.141 0.759 0. 0.1 ] | 0.159894 | 0.0486562 | 0.208551 | [0.141 0.859] | 0.241 |
-| (0.1, 89) | 0.173025 | 0.0519748 | 0.225 | [0.125 0.775 0. 0.1 ] | 0.149647 | 0.0554812 | 0.205128 | [0.125 0.875] | 0.225 |
-| (0.1, 90) | 0.161536 | 0.0644643 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.164452 | 0.0408866 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 91) | 0.19674 | 0.0392595 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.152299 | 0.0551697 | 0.207469 | [0.136 0.864] | 0.236 |
-| (0.1, 92) | 0.1473 | 0.0766998 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.125015 | 0.0799031 | 0.204918 | [0.124 0.876] | 0.224 |
-| (0.1, 93) | 0.157492 | 0.0725084 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.161964 | 0.0442218 | 0.206186 | [0.13 0.87] | 0.23 |
-| (0.1, 94) | 0.166779 | 0.0672206 | 0.234 | [0.134 0.766 0. 0.1 ] | 0.168283 | 0.0387559 | 0.207039 | [0.134 0.866] | 0.234 |
-| (0.1, 95) | 0.170211 | 0.0797889 | 0.25 | [0.15 0.75 0. 0.1 ] | 0.151857 | 0.0586692 | 0.210526 | [0.15 0.85] | 0.25 |
-| (0.1, 96) | 0.137124 | 0.0808765 | 0.218 | [0.118 0.782 0. 0.1 ] | 0.154015 | 0.0496513 | 0.203666 | [0.118 0.882] | 0.218 |
-| (0.1, 97) | 0.153298 | 0.0727017 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.165413 | 0.0399255 | 0.205339 | [0.126 0.874] | 0.226 |
-| (0.1, 98) | 0.141298 | 0.120702 | 0.262 | [0.162 0.738 0. 0.1 ] | 0.135892 | 0.0773272 | 0.21322 | [0.162 0.838] | 0.262 |
-| (0.1, 99) | 0.175225 | 0.0527751 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.16037 | 0.045391 | 0.205761 | [0.128 0.872] | 0.228 |
-| (0.15, 0) | 0.1203 | 0.1657 | 0.286 | [0.137 0.713 0.001 0.149] | 0.127121 | 0.167346 | 0.294466 | [0.138 0.862] | 0.286 |
-| (0.15, 1) | 0.119526 | 0.167474 | 0.287 | [0.137 0.713 0. 0.15 ] | 0.135734 | 0.160416 | 0.29615 | [0.137 0.863] | 0.287 |
-| (0.15, 2) | 0.137288 | 0.133712 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.123291 | 0.168254 | 0.291545 | [0.121 0.879] | 0.271 |
-| (0.15, 3) | 0.142731 | 0.113269 | 0.256 | [0.106 0.744 0. 0.15 ] | 0.13131 | 0.156047 | 0.287356 | [0.106 0.894] | 0.256 |
-| (0.15, 4) | 0.166618 | 0.105382 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.161107 | 0.130722 | 0.291829 | [0.122 0.878] | 0.272 |
-| (0.15, 5) | 0.139421 | 0.139579 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.176782 | 0.117048 | 0.29383 | [0.129 0.871] | 0.279 |
-| (0.15, 6) | 0.170222 | 0.099778 | 0.27 | [0.12 0.73 0. 0.15] | 0.148121 | 0.143141 | 0.291262 | [0.12 0.88] | 0.27 |
-| (0.15, 7) | 0.158061 | 0.114939 | 0.273 | [0.123 0.727 0. 0.15 ] | 0.176748 | 0.115365 | 0.292113 | [0.123 0.877] | 0.273 |
-| (0.15, 8) | 0.17871 | 0.11629 | 0.295 | [0.145 0.705 0. 0.15 ] | 0.132824 | 0.165683 | 0.298507 | [0.145 0.855] | 0.295 |
-| (0.15, 9) | 0.151538 | 0.119462 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.149422 | 0.142123 | 0.291545 | [0.121 0.879] | 0.271 |
-| (0.15, 10) | 0.139049 | 0.130951 | 0.27 | [0.121 0.729 0.001 0.149] | 0.13676 | 0.153123 | 0.289883 | [0.122 0.878] | 0.27 |
-| (0.15, 11) | 0.116244 | 0.156756 | 0.273 | [0.124 0.726 0.001 0.149] | 0.141815 | 0.148916 | 0.290732 | [0.125 0.875] | 0.273 |
-| (0.15, 12) | 0.162998 | 0.126002 | 0.289 | [0.139 0.711 0. 0.15 ] | 0.156127 | 0.140609 | 0.296736 | [0.139 0.861] | 0.289 |
-| (0.15, 13) | 0.128238 | 0.150762 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.134349 | 0.159481 | 0.29383 | [0.129 0.871] | 0.279 |
-| (0.15, 14) | 0.117776 | 0.132224 | 0.25 | [0.1 0.75 0. 0.15] | 0.139297 | 0.146418 | 0.285714 | [0.1 0.9] | 0.25 |
-| (0.15, 15) | 0.104416 | 0.179584 | 0.284 | [0.134 0.716 0. 0.15 ] | 0.131122 | 0.164154 | 0.295276 | [0.134 0.866] | 0.284 |
-| (0.15, 16) | 0.137068 | 0.134932 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.166223 | 0.125605 | 0.291829 | [0.122 0.878] | 0.272 |
-| (0.15, 17) | 0.158429 | 0.111571 | 0.27 | [0.12 0.73 0. 0.15] | 0.17491 | 0.116352 | 0.291262 | [0.12 0.88] | 0.27 |
-| (0.15, 18) | 0.168285 | 0.0947153 | 0.263 | [0.113 0.737 0. 0.15 ] | 0.173726 | 0.11557 | 0.289296 | [0.113 0.887] | 0.263 |
-| (0.15, 19) | 0.171027 | 0.120973 | 0.292 | [0.142 0.708 0. 0.15 ] | 0.142831 | 0.154788 | 0.297619 | [0.142 0.858] | 0.292 |
-| (0.15, 20) | 0.148659 | 0.131341 | 0.28 | [0.13 0.72 0. 0.15] | 0.155957 | 0.138161 | 0.294118 | [0.13 0.87] | 0.28 |
-| (0.15, 21) | 0.110694 | 0.147306 | 0.258 | [0.108 0.742 0. 0.15 ] | 0.132425 | 0.155482 | 0.287908 | [0.108 0.892] | 0.258 |
-| (0.15, 22) | 0.13145 | 0.14855 | 0.28 | [0.13 0.72 0. 0.15] | 0.134374 | 0.159744 | 0.294118 | [0.13 0.87] | 0.28 |
-| (0.15, 23) | 0.146038 | 0.126962 | 0.273 | [0.123 0.727 0. 0.15 ] | 0.130698 | 0.161415 | 0.292113 | [0.123 0.877] | 0.273 |
-| (0.15, 24) | 0.181347 | 0.108653 | 0.29 | [0.141 0.709 0.001 0.149] | 0.149705 | 0.14593 | 0.295635 | [0.142 0.858] | 0.29 |
-| (0.15, 25) | 0.146943 | 0.144057 | 0.291 | [0.141 0.709 0. 0.15 ] | 0.136203 | 0.161121 | 0.297324 | [0.141 0.859] | 0.291 |
-| (0.15, 26) | 0.147795 | 0.116205 | 0.264 | [0.114 0.736 0. 0.15 ] | 0.157537 | 0.132038 | 0.289575 | [0.114 0.886] | 0.264 |
-| (0.15, 27) | 0.128014 | 0.138986 | 0.267 | [0.117 0.733 0. 0.15 ] | 0.148528 | 0.141888 | 0.290416 | [0.117 0.883] | 0.267 |
-| (0.15, 28) | 0.143207 | 0.128793 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.138262 | 0.153567 | 0.291829 | [0.122 0.878] | 0.272 |
-| (0.15, 29) | 0.148872 | 0.145128 | 0.294 | [0.144 0.706 0. 0.15 ] | 0.135484 | 0.162727 | 0.298211 | [0.144 0.856] | 0.294 |
-| (0.15, 30) | 0.144965 | 0.113035 | 0.258 | [0.108 0.742 0. 0.15 ] | 0.147562 | 0.140346 | 0.287908 | [0.108 0.892] | 0.258 |
-| (0.15, 31) | 0.145971 | 0.119029 | 0.265 | [0.115 0.735 0. 0.15 ] | 0.161121 | 0.128734 | 0.289855 | [0.115 0.885] | 0.265 |
-| (0.15, 32) | 0.137751 | 0.124249 | 0.262 | [0.113 0.737 0.001 0.149] | 0.145534 | 0.142111 | 0.287645 | [0.114 0.886] | 0.262 |
-| (0.15, 33) | 0.11238 | 0.15762 | 0.27 | [0.12 0.73 0. 0.15] | 0.130286 | 0.160976 | 0.291262 | [0.12 0.88] | 0.27 |
-| (0.15, 34) | 0.0966508 | 0.179349 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.117277 | 0.175692 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 35) | 0.157902 | 0.113098 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.152535 | 0.13901 | 0.291545 | [0.121 0.879] | 0.271 |
-| (0.15, 36) | 0.125849 | 0.166151 | 0.292 | [0.142 0.708 0. 0.15 ] | 0.15111 | 0.146509 | 0.297619 | [0.142 0.858] | 0.292 |
-| (0.15, 37) | 0.167764 | 0.137236 | 0.305 | [0.155 0.695 0. 0.15 ] | 0.179681 | 0.121826 | 0.301508 | [0.155 0.845] | 0.305 |
-| (0.15, 38) | 0.154211 | 0.128789 | 0.283 | [0.133 0.717 0. 0.15 ] | 0.166432 | 0.128554 | 0.294985 | [0.133 0.867] | 0.283 |
-| (0.15, 39) | 0.132705 | 0.143295 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.14616 | 0.146809 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 40) | 0.152512 | 0.123488 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.141054 | 0.151915 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 41) | 0.135058 | 0.127942 | 0.263 | [0.113 0.737 0. 0.15 ] | 0.16119 | 0.128106 | 0.289296 | [0.113 0.887] | 0.263 |
-| (0.15, 42) | 0.123784 | 0.152216 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.142844 | 0.150125 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 43) | 0.171101 | 0.0878989 | 0.259 | [0.109 0.741 0. 0.15 ] | 0.164715 | 0.123469 | 0.288184 | [0.109 0.891] | 0.259 |
-| (0.15, 44) | 0.16704 | 0.0949603 | 0.262 | [0.114 0.736 0.002 0.148] | 0.142699 | 0.143568 | 0.286267 | [0.116 0.884] | 0.262 |
-| (0.15, 45) | 0.116311 | 0.171689 | 0.288 | [0.138 0.712 0. 0.15 ] | 0.141653 | 0.15479 | 0.296443 | [0.138 0.862] | 0.288 |
-| (0.15, 46) | 0.154616 | 0.104384 | 0.259 | [0.109 0.741 0. 0.15 ] | 0.138548 | 0.149637 | 0.288184 | [0.109 0.891] | 0.259 |
-| (0.15, 47) | 0.144754 | 0.133246 | 0.278 | [0.128 0.722 0. 0.15 ] | 0.12734 | 0.166202 | 0.293542 | [0.128 0.872] | 0.278 |
-| (0.15, 48) | 0.175836 | 0.110164 | 0.286 | [0.136 0.714 0. 0.15 ] | 0.153911 | 0.141947 | 0.295858 | [0.136 0.864] | 0.286 |
-| (0.15, 49) | 0.162022 | 0.111978 | 0.274 | [0.124 0.726 0. 0.15 ] | 0.150176 | 0.142221 | 0.292398 | [0.124 0.876] | 0.274 |
-| (0.15, 50) | 0.177202 | 0.0937983 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.158743 | 0.132803 | 0.291545 | [0.121 0.879] | 0.271 |
-| (0.15, 51) | 0.153076 | 0.111924 | 0.265 | [0.115 0.735 0. 0.15 ] | 0.134545 | 0.15531 | 0.289855 | [0.115 0.885] | 0.265 |
-| (0.15, 52) | 0.138063 | 0.151937 | 0.29 | [0.14 0.71 0. 0.15] | 0.137941 | 0.159089 | 0.29703 | [0.14 0.86] | 0.29 |
-| (0.15, 53) | 0.153557 | 0.122443 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.132467 | 0.160502 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 54) | 0.151345 | 0.114655 | 0.266 | [0.116 0.734 0. 0.15 ] | 0.138179 | 0.151956 | 0.290135 | [0.116 0.884] | 0.266 |
-| (0.15, 55) | 0.13427 | 0.14873 | 0.283 | [0.133 0.717 0. 0.15 ] | 0.157275 | 0.137711 | 0.294985 | [0.133 0.867] | 0.283 |
-| (0.15, 56) | 0.137219 | 0.134781 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.158478 | 0.133351 | 0.291829 | [0.122 0.878] | 0.272 |
-| (0.15, 57) | 0.160927 | 0.140073 | 0.301 | [0.151 0.699 0. 0.15 ] | 0.146971 | 0.153329 | 0.3003 | [0.151 0.849] | 0.301 |
-| (0.15, 58) | 0.120219 | 0.163781 | 0.284 | [0.134 0.716 0. 0.15 ] | 0.145434 | 0.149842 | 0.295276 | [0.134 0.866] | 0.284 |
-| (0.15, 59) | 0.154083 | 0.126917 | 0.281 | [0.131 0.719 0. 0.15 ] | 0.154977 | 0.139429 | 0.294406 | [0.131 0.869] | 0.281 |
-| (0.15, 60) | 0.157883 | 0.111117 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.172352 | 0.118627 | 0.29098 | [0.119 0.881] | 0.269 |
-| (0.15, 61) | 0.136203 | 0.143797 | 0.28 | [0.13 0.72 0. 0.15] | 0.156749 | 0.137369 | 0.294118 | [0.13 0.87] | 0.28 |
-| (0.15, 62) | 0.121822 | 0.177178 | 0.299 | [0.149 0.701 0. 0.15 ] | 0.158284 | 0.141416 | 0.2997 | [0.149 0.851] | 0.299 |
-| (0.15, 63) | 0.134564 | 0.151436 | 0.286 | [0.136 0.714 0. 0.15 ] | 0.122765 | 0.173093 | 0.295858 | [0.136 0.864] | 0.286 |
-| (0.15, 64) | 0.138566 | 0.136434 | 0.275 | [0.125 0.725 0. 0.15 ] | 0.164812 | 0.127871 | 0.292683 | [0.125 0.875] | 0.275 |
-| (0.15, 65) | 0.141594 | 0.132406 | 0.274 | [0.125 0.725 0.001 0.149] | 0.130073 | 0.160943 | 0.291016 | [0.126 0.874] | 0.274 |
-| (0.15, 66) | 0.144607 | 0.135393 | 0.28 | [0.13 0.72 0. 0.15] | 0.119498 | 0.174619 | 0.294118 | [0.13 0.87] | 0.28 |
-| (0.15, 67) | 0.178893 | 0.090107 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.171713 | 0.119267 | 0.29098 | [0.119 0.881] | 0.269 |
-| (0.15, 68) | 0.139628 | 0.145372 | 0.285 | [0.135 0.715 0. 0.15 ] | 0.135852 | 0.159714 | 0.295567 | [0.135 0.865] | 0.285 |
-| (0.15, 69) | 0.1838 | 0.0922 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.172546 | 0.120423 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 70) | 0.125644 | 0.138356 | 0.264 | [0.114 0.736 0. 0.15 ] | 0.160992 | 0.128583 | 0.289575 | [0.114 0.886] | 0.264 |
-| (0.15, 71) | 0.160764 | 0.101236 | 0.262 | [0.112 0.738 0. 0.15 ] | 0.161154 | 0.127864 | 0.289017 | [0.112 0.888] | 0.262 |
-| (0.15, 72) | 0.161464 | 0.107536 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.159812 | 0.131167 | 0.29098 | [0.119 0.881] | 0.269 |
-| (0.15, 73) | 0.121342 | 0.153658 | 0.275 | [0.125 0.725 0. 0.15 ] | 0.107444 | 0.185239 | 0.292683 | [0.125 0.875] | 0.275 |
-| (0.15, 74) | 0.145367 | 0.133633 | 0.279 | [0.13 0.72 0.001 0.149] | 0.129848 | 0.162596 | 0.292444 | [0.131 0.869] | 0.279 |
-| (0.15, 75) | 0.155114 | 0.117886 | 0.273 | [0.124 0.726 0.001 0.149] | 0.15948 | 0.131252 | 0.290732 | [0.125 0.875] | 0.273 |
-| (0.15, 76) | 0.1274 | 0.1606 | 0.288 | [0.138 0.712 0. 0.15 ] | 0.14193 | 0.154513 | 0.296443 | [0.138 0.862] | 0.288 |
-| (0.15, 77) | 0.152264 | 0.143736 | 0.296 | [0.146 0.704 0. 0.15 ] | 0.155979 | 0.142826 | 0.298805 | [0.146 0.854] | 0.296 |
-| (0.15, 78) | 0.10929 | 0.17271 | 0.282 | [0.132 0.718 0. 0.15 ] | 0.129038 | 0.165657 | 0.294695 | [0.132 0.868] | 0.282 |
-| (0.15, 79) | 0.1422 | 0.1328 | 0.275 | [0.125 0.725 0. 0.15 ] | 0.150535 | 0.142148 | 0.292683 | [0.125 0.875] | 0.275 |
-| (0.15, 80) | 0.168582 | 0.0974178 | 0.266 | [0.117 0.733 0.001 0.149] | 0.161824 | 0.126936 | 0.28876 | [0.118 0.882] | 0.266 |
-| (0.15, 81) | 0.148811 | 0.130189 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.118403 | 0.175427 | 0.29383 | [0.129 0.871] | 0.279 |
-| (0.15, 82) | 0.133344 | 0.134656 | 0.268 | [0.118 0.732 0. 0.15 ] | 0.151254 | 0.139444 | 0.290698 | [0.118 0.882] | 0.268 |
-| (0.15, 83) | 0.124459 | 0.126541 | 0.251 | [0.101 0.749 0. 0.15 ] | 0.13409 | 0.151896 | 0.285987 | [0.101 0.899] | 0.251 |
-| (0.15, 84) | 0.141318 | 0.137682 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.154315 | 0.139515 | 0.29383 | [0.129 0.871] | 0.279 |
-| (0.15, 85) | 0.163049 | 0.117951 | 0.281 | [0.131 0.719 0. 0.15 ] | 0.140319 | 0.154088 | 0.294406 | [0.131 0.869] | 0.281 |
-| (0.15, 86) | 0.152419 | 0.133581 | 0.286 | [0.136 0.714 0. 0.15 ] | 0.137388 | 0.15847 | 0.295858 | [0.136 0.864] | 0.286 |
-| (0.15, 87) | 0.106809 | 0.176191 | 0.283 | [0.133 0.717 0. 0.15 ] | 0.102393 | 0.192592 | 0.294985 | [0.133 0.867] | 0.283 |
-| (0.15, 88) | 0.160406 | 0.104594 | 0.265 | [0.115 0.735 0. 0.15 ] | 0.15609 | 0.133765 | 0.289855 | [0.115 0.885] | 0.265 |
-| (0.15, 89) | 0.123011 | 0.149989 | 0.273 | [0.123 0.727 0. 0.15 ] | 0.145604 | 0.146509 | 0.292113 | [0.123 0.877] | 0.273 |
-| (0.15, 90) | 0.159302 | 0.112698 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.139501 | 0.152328 | 0.291829 | [0.122 0.878] | 0.272 |
-| (0.15, 91) | 0.146535 | 0.147465 | 0.294 | [0.144 0.706 0. 0.15 ] | 0.160389 | 0.137822 | 0.298211 | [0.144 0.856] | 0.294 |
-| (0.15, 92) | 0.174056 | 0.089944 | 0.264 | [0.114 0.736 0. 0.15 ] | 0.154888 | 0.134687 | 0.289575 | [0.114 0.886] | 0.264 |
-| (0.15, 93) | 0.132952 | 0.145048 | 0.278 | [0.128 0.722 0. 0.15 ] | 0.153029 | 0.140513 | 0.293542 | [0.128 0.872] | 0.278 |
-| (0.15, 94) | 0.148742 | 0.131258 | 0.28 | [0.131 0.719 0.001 0.149] | 0.15407 | 0.138661 | 0.292731 | [0.132 0.868] | 0.28 |
-| (0.15, 95) | 0.160161 | 0.102839 | 0.263 | [0.114 0.736 0.001 0.149] | 0.135026 | 0.152896 | 0.287923 | [0.115 0.885] | 0.263 |
-| (0.15, 96) | 0.123638 | 0.160362 | 0.284 | [0.134 0.716 0. 0.15 ] | 0.138609 | 0.156667 | 0.295276 | [0.134 0.866] | 0.284 |
-| (0.15, 97) | 0.161662 | 0.105338 | 0.267 | [0.117 0.733 0. 0.15 ] | 0.146184 | 0.144233 | 0.290416 | [0.117 0.883] | 0.267 |
-| (0.15, 98) | 0.147239 | 0.128761 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.165486 | 0.127483 | 0.292969 | [0.126 0.874] | 0.276 |
-| (0.15, 99) | 0.127231 | 0.141769 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.137447 | 0.153533 | 0.29098 | [0.119 0.881] | 0.269 |
-| (0.2, 0) | 0.0932749 | 0.232725 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.107742 | 0.264698 | 0.372439 | [0.126 0.874] | 0.326 |
-| (0.2, 1) | 0.103595 | 0.225405 | 0.329 | [0.129 0.671 0. 0.2 ] | 0.11693 | 0.256553 | 0.373483 | [0.129 0.871] | 0.329 |
-| (0.2, 2) | 0.146266 | 0.174734 | 0.321 | [0.121 0.679 0. 0.2 ] | 0.13068 | 0.240034 | 0.370714 | [0.121 0.879] | 0.321 |
-| (0.2, 3) | 0.158612 | 0.158388 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.140197 | 0.229147 | 0.369344 | [0.117 0.883] | 0.317 |
-| (0.2, 4) | 0.13548 | 0.18852 | 0.324 | [0.125 0.675 0.001 0.199] | 0.123131 | 0.247446 | 0.370577 | [0.126 0.874] | 0.324 |
-| (0.2, 5) | 0.184383 | 0.139617 | 0.324 | [0.124 0.676 0. 0.2 ] | 0.16367 | 0.208077 | 0.371747 | [0.124 0.876] | 0.324 |
-| (0.2, 6) | 0.119201 | 0.191799 | 0.311 | [0.111 0.689 0. 0.2 ] | 0.12538 | 0.24193 | 0.367309 | [0.111 0.889] | 0.311 |
-| (0.2, 7) | 0.13074 | 0.18826 | 0.319 | [0.12 0.68 0.001 0.199] | 0.1483 | 0.22056 | 0.36886 | [0.121 0.879] | 0.319 |
-| (0.2, 8) | 0.158339 | 0.154661 | 0.313 | [0.113 0.687 0. 0.2 ] | 0.141924 | 0.226061 | 0.367985 | [0.113 0.887] | 0.313 |
-| (0.2, 9) | 0.133184 | 0.171816 | 0.305 | [0.107 0.693 0.002 0.198] | 0.155369 | 0.207601 | 0.36297 | [0.109 0.891] | 0.305 |
-| (0.2, 10) | 0.152238 | 0.170762 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.141301 | 0.230101 | 0.371402 | [0.123 0.877] | 0.323 |
-| (0.2, 11) | 0.147096 | 0.187904 | 0.335 | [0.135 0.665 0. 0.2 ] | 0.126492 | 0.249094 | 0.375587 | [0.135 0.865] | 0.335 |
-| (0.2, 12) | 0.139379 | 0.187621 | 0.327 | [0.127 0.673 0. 0.2 ] | 0.140083 | 0.232704 | 0.372787 | [0.127 0.873] | 0.327 |
-| (0.2, 13) | 0.157408 | 0.164592 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.128326 | 0.242732 | 0.371058 | [0.122 0.878] | 0.322 |
-| (0.2, 14) | 0.165325 | 0.154675 | 0.32 | [0.12 0.68 0. 0.2 ] | 0.141291 | 0.229079 | 0.37037 | [0.12 0.88] | 0.32 |
-| (0.2, 15) | 0.155916 | 0.162084 | 0.318 | [0.119 0.681 0.001 0.199] | 0.136168 | 0.232351 | 0.368519 | [0.12 0.88] | 0.318 |
-| (0.2, 16) | 0.126583 | 0.190417 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.0939205 | 0.275424 | 0.369344 | [0.117 0.883] | 0.317 |
-| (0.2, 17) | 0.132189 | 0.202811 | 0.335 | [0.135 0.665 0. 0.2 ] | 0.109183 | 0.266403 | 0.375587 | [0.135 0.865] | 0.335 |
-| (0.2, 18) | 0.129466 | 0.189534 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.115286 | 0.254741 | 0.370028 | [0.119 0.881] | 0.319 |
-| (0.2, 19) | 0.128175 | 0.177825 | 0.306 | [0.106 0.694 0. 0.2 ] | 0.133787 | 0.231843 | 0.365631 | [0.106 0.894] | 0.306 |
-| (0.2, 20) | 0.145426 | 0.187574 | 0.333 | [0.133 0.667 0. 0.2 ] | 0.151205 | 0.223677 | 0.374883 | [0.133 0.867] | 0.333 |
-| (0.2, 21) | 0.163454 | 0.154546 | 0.318 | [0.119 0.681 0.001 0.199] | 0.139559 | 0.228959 | 0.368519 | [0.12 0.88] | 0.318 |
-| (0.2, 22) | 0.114168 | 0.215832 | 0.33 | [0.131 0.669 0.001 0.199] | 0.114659 | 0.258001 | 0.372659 | [0.132 0.868] | 0.33 |
-| (0.2, 23) | 0.156559 | 0.173441 | 0.33 | [0.13 0.67 0. 0.2 ] | 0.150894 | 0.222937 | 0.373832 | [0.13 0.87] | 0.33 |
-| (0.2, 24) | 0.110103 | 0.206897 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.109295 | 0.260049 | 0.369344 | [0.117 0.883] | 0.317 |
-| (0.2, 25) | 0.153082 | 0.174918 | 0.328 | [0.128 0.672 0. 0.2 ] | 0.159335 | 0.213799 | 0.373134 | [0.128 0.872] | 0.328 |
-| (0.2, 26) | 0.126215 | 0.187785 | 0.314 | [0.114 0.686 0. 0.2 ] | 0.114362 | 0.253962 | 0.368324 | [0.114 0.886] | 0.314 |
-| (0.2, 27) | 0.145636 | 0.172364 | 0.318 | [0.118 0.682 0. 0.2 ] | 0.154729 | 0.214956 | 0.369686 | [0.118 0.882] | 0.318 |
-| (0.2, 28) | 0.113045 | 0.191955 | 0.305 | [0.105 0.695 0. 0.2 ] | 0.103814 | 0.261482 | 0.365297 | [0.105 0.895] | 0.305 |
-| (0.2, 29) | 0.151512 | 0.171488 | 0.323 | [0.124 0.676 0.001 0.199] | 0.134941 | 0.235291 | 0.370233 | [0.125 0.875] | 0.323 |
-| (0.2, 30) | 0.124049 | 0.206951 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.130243 | 0.243939 | 0.374181 | [0.131 0.869] | 0.331 |
-| (0.2, 31) | 0.14276 | 0.17924 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.147474 | 0.223583 | 0.371058 | [0.122 0.878] | 0.322 |
-| (0.2, 32) | 0.184874 | 0.137126 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.162763 | 0.208295 | 0.371058 | [0.122 0.878] | 0.322 |
-| (0.2, 33) | 0.113052 | 0.205948 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.125327 | 0.2447 | 0.370028 | [0.119 0.881] | 0.319 |
-| (0.2, 34) | 0.11022 | 0.20578 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.134172 | 0.234831 | 0.369004 | [0.116 0.884] | 0.316 |
-| (0.2, 35) | 0.15689 | 0.16811 | 0.325 | [0.125 0.675 0. 0.2 ] | 0.139515 | 0.232578 | 0.372093 | [0.125 0.875] | 0.325 |
-| (0.2, 36) | 0.12372 | 0.19828 | 0.322 | [0.123 0.677 0.001 0.199] | 0.144416 | 0.225473 | 0.369888 | [0.124 0.876] | 0.322 |
-| (0.2, 37) | 0.156173 | 0.149827 | 0.306 | [0.106 0.694 0. 0.2 ] | 0.140543 | 0.225087 | 0.365631 | [0.106 0.894] | 0.306 |
-| (0.2, 38) | 0.123178 | 0.191822 | 0.315 | [0.115 0.685 0. 0.2 ] | 0.124918 | 0.243745 | 0.368664 | [0.115 0.885] | 0.315 |
-| (0.2, 39) | 0.149818 | 0.155182 | 0.305 | [0.105 0.695 0. 0.2 ] | 0.153473 | 0.211824 | 0.365297 | [0.105 0.895] | 0.305 |
-| (0.2, 40) | 0.146996 | 0.151004 | 0.298 | [0.098 0.702 0. 0.2 ] | 0.136716 | 0.226261 | 0.362976 | [0.098 0.902] | 0.298 |
-| (0.2, 41) | 0.134983 | 0.174017 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.130812 | 0.235824 | 0.366636 | [0.109 0.891] | 0.309 |
-| (0.2, 42) | 0.130339 | 0.204661 | 0.335 | [0.135 0.665 0. 0.2 ] | 0.132934 | 0.242653 | 0.375587 | [0.135 0.865] | 0.335 |
-| (0.2, 43) | 0.131752 | 0.197248 | 0.329 | [0.129 0.671 0. 0.2 ] | 0.122563 | 0.25092 | 0.373483 | [0.129 0.871] | 0.329 |
-| (0.2, 44) | 0.104892 | 0.213108 | 0.318 | [0.118 0.682 0. 0.2 ] | 0.101844 | 0.267842 | 0.369686 | [0.118 0.882] | 0.318 |
-| (0.2, 45) | 0.108924 | 0.208076 | 0.317 | [0.118 0.682 0.001 0.199] | 0.112634 | 0.255543 | 0.368178 | [0.119 0.881] | 0.317 |
-| (0.2, 46) | 0.158723 | 0.146277 | 0.305 | [0.106 0.694 0.001 0.199] | 0.14642 | 0.217715 | 0.364135 | [0.107 0.893] | 0.305 |
-| (0.2, 47) | 0.181864 | 0.130136 | 0.312 | [0.113 0.687 0.001 0.199] | 0.162233 | 0.204249 | 0.366483 | [0.114 0.886] | 0.312 |
-| (0.2, 48) | 0.139857 | 0.177143 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.130469 | 0.238875 | 0.369344 | [0.117 0.883] | 0.317 |
-| (0.2, 49) | 0.130555 | 0.185445 | 0.316 | [0.117 0.683 0.001 0.199] | 0.129553 | 0.238285 | 0.367837 | [0.118 0.882] | 0.316 |
-| (0.2, 50) | 0.126112 | 0.184888 | 0.311 | [0.111 0.689 0. 0.2 ] | 0.116336 | 0.250973 | 0.367309 | [0.111 0.889] | 0.311 |
-| (0.2, 51) | 0.126804 | 0.189196 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.134586 | 0.234417 | 0.369004 | [0.116 0.884] | 0.316 |
-| (0.2, 52) | 0.1149 | 0.1861 | 0.301 | [0.101 0.699 0. 0.2 ] | 0.131898 | 0.232069 | 0.363967 | [0.101 0.899] | 0.301 |
-| (0.2, 53) | 0.147138 | 0.163862 | 0.311 | [0.112 0.688 0.001 0.199] | 0.130518 | 0.235628 | 0.366145 | [0.113 0.887] | 0.311 |
-| (0.2, 54) | 0.126953 | 0.204047 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.103391 | 0.270791 | 0.374181 | [0.131 0.869] | 0.331 |
-| (0.2, 55) | 0.154759 | 0.161241 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.143336 | 0.225668 | 0.369004 | [0.116 0.884] | 0.316 |
-| (0.2, 56) | 0.148069 | 0.154931 | 0.303 | [0.103 0.697 0. 0.2 ] | 0.13299 | 0.23164 | 0.364631 | [0.103 0.897] | 0.303 |
-| (0.2, 57) | 0.14951 | 0.17349 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.124754 | 0.246648 | 0.371402 | [0.123 0.877] | 0.323 |
-| (0.2, 58) | 0.124588 | 0.182412 | 0.307 | [0.107 0.693 0. 0.2 ] | 0.135337 | 0.230628 | 0.365965 | [0.107 0.893] | 0.307 |
-| (0.2, 59) | 0.106309 | 0.219691 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.124609 | 0.247831 | 0.372439 | [0.126 0.874] | 0.326 |
-| (0.2, 60) | 0.163061 | 0.148939 | 0.312 | [0.112 0.688 0. 0.2 ] | 0.125001 | 0.242646 | 0.367647 | [0.112 0.888] | 0.312 |
-| (0.2, 61) | 0.098016 | 0.220984 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.111374 | 0.258654 | 0.370028 | [0.119 0.881] | 0.319 |
-| (0.2, 62) | 0.133823 | 0.192177 | 0.326 | [0.127 0.673 0.001 0.199] | 0.138711 | 0.232558 | 0.371269 | [0.128 0.872] | 0.326 |
-| (0.2, 63) | 0.132592 | 0.193408 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.168652 | 0.203787 | 0.372439 | [0.126 0.874] | 0.326 |
-| (0.2, 64) | 0.146847 | 0.167153 | 0.314 | [0.114 0.686 0. 0.2 ] | 0.134352 | 0.233973 | 0.368324 | [0.114 0.886] | 0.314 |
-| (0.2, 65) | 0.123678 | 0.209322 | 0.333 | [0.134 0.666 0.001 0.199] | 0.139748 | 0.233961 | 0.373709 | [0.135 0.865] | 0.333 |
-| (0.2, 66) | 0.153441 | 0.166559 | 0.32 | [0.12 0.68 0. 0.2 ] | 0.168793 | 0.201578 | 0.37037 | [0.12 0.88] | 0.32 |
-| (0.2, 67) | 0.102558 | 0.206442 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.129257 | 0.237379 | 0.366636 | [0.109 0.891] | 0.309 |
-| (0.2, 68) | 0.113796 | 0.181204 | 0.295 | [0.095 0.705 0. 0.2 ] | 0.125855 | 0.236136 | 0.361991 | [0.095 0.905] | 0.295 |
-| (0.2, 69) | 0.130216 | 0.186784 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.154798 | 0.214547 | 0.369344 | [0.117 0.883] | 0.317 |
-| (0.2, 70) | 0.140137 | 0.173863 | 0.314 | [0.114 0.686 0. 0.2 ] | 0.133952 | 0.234372 | 0.368324 | [0.114 0.886] | 0.314 |
-| (0.2, 71) | 0.118374 | 0.173626 | 0.292 | [0.093 0.707 0.001 0.199] | 0.102911 | 0.256944 | 0.359855 | [0.094 0.906] | 0.292 |
-| (0.2, 72) | 0.142998 | 0.173002 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.13498 | 0.234024 | 0.369004 | [0.116 0.884] | 0.316 |
-| (0.2, 73) | 0.11727 | 0.20573 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.100748 | 0.270654 | 0.371402 | [0.123 0.877] | 0.323 |
-| (0.2, 74) | 0.13782 | 0.17518 | 0.313 | [0.114 0.686 0.001 0.199] | 0.113838 | 0.252982 | 0.36682 | [0.115 0.885] | 0.313 |
-| (0.2, 75) | 0.127086 | 0.203914 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.124813 | 0.249369 | 0.374181 | [0.131 0.869] | 0.331 |
-| (0.2, 76) | 0.110385 | 0.192615 | 0.303 | [0.104 0.696 0.001 0.199] | 0.117311 | 0.246159 | 0.36347 | [0.105 0.895] | 0.303 |
-| (0.2, 77) | 0.169946 | 0.156054 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.154318 | 0.218121 | 0.372439 | [0.126 0.874] | 0.326 |
-| (0.2, 78) | 0.125895 | 0.184105 | 0.31 | [0.11 0.69 0. 0.2 ] | 0.137846 | 0.229127 | 0.366972 | [0.11 0.89] | 0.31 |
-| (0.2, 79) | 0.106497 | 0.195503 | 0.302 | [0.102 0.698 0. 0.2 ] | 0.108174 | 0.256124 | 0.364299 | [0.102 0.898] | 0.302 |
-| (0.2, 80) | 0.153481 | 0.163519 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.136076 | 0.233269 | 0.369344 | [0.117 0.883] | 0.317 |
-| (0.2, 81) | 0.139622 | 0.180378 | 0.32 | [0.121 0.679 0.001 0.199] | 0.126998 | 0.242204 | 0.369202 | [0.122 0.878] | 0.32 |
-| (0.2, 82) | 0.131272 | 0.188728 | 0.32 | [0.121 0.679 0.001 0.199] | 0.125249 | 0.243954 | 0.369202 | [0.122 0.878] | 0.32 |
-| (0.2, 83) | 0.150497 | 0.172503 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.154524 | 0.216878 | 0.371402 | [0.123 0.877] | 0.323 |
-| (0.2, 84) | 0.138086 | 0.180914 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.125401 | 0.244626 | 0.370028 | [0.119 0.881] | 0.319 |
-| (0.2, 85) | 0.139788 | 0.187212 | 0.327 | [0.127 0.673 0. 0.2 ] | 0.157005 | 0.215781 | 0.372787 | [0.127 0.873] | 0.327 |
-| (0.2, 86) | 0.0908716 | 0.216128 | 0.307 | [0.107 0.693 0. 0.2 ] | 0.0962838 | 0.269681 | 0.365965 | [0.107 0.893] | 0.307 |
-| (0.2, 87) | 0.147758 | 0.161242 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.129789 | 0.236848 | 0.366636 | [0.109 0.891] | 0.309 |
-| (0.2, 88) | 0.137745 | 0.187255 | 0.325 | [0.125 0.675 0. 0.2 ] | 0.16326 | 0.208833 | 0.372093 | [0.125 0.875] | 0.325 |
-| (0.2, 89) | 0.147468 | 0.161532 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.132114 | 0.234522 | 0.366636 | [0.109 0.891] | 0.309 |
-| (0.2, 90) | 0.0964468 | 0.224553 | 0.321 | [0.121 0.679 0. 0.2 ] | 0.102582 | 0.268131 | 0.370714 | [0.121 0.879] | 0.321 |
-| (0.2, 91) | 0.101547 | 0.214453 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.112843 | 0.25616 | 0.369004 | [0.116 0.884] | 0.316 |
-| (0.2, 92) | 0.162379 | 0.157621 | 0.32 | [0.12 0.68 0. 0.2 ] | 0.132839 | 0.237531 | 0.37037 | [0.12 0.88] | 0.32 |
-| (0.2, 93) | 0.141758 | 0.189242 | 0.331 | [0.132 0.668 0.001 0.199] | 0.144896 | 0.228113 | 0.373008 | [0.133 0.867] | 0.331 |
-| (0.2, 94) | 0.169261 | 0.152739 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.166465 | 0.204593 | 0.371058 | [0.122 0.878] | 0.322 |
-| (0.2, 95) | 0.122537 | 0.200463 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.111265 | 0.260137 | 0.371402 | [0.123 0.877] | 0.323 |
-| (0.2, 96) | 0.126137 | 0.193863 | 0.32 | [0.121 0.679 0.001 0.199] | 0.130176 | 0.239026 | 0.369202 | [0.122 0.878] | 0.32 |
-| (0.2, 97) | 0.0939801 | 0.23702 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.103706 | 0.270476 | 0.374181 | [0.131 0.869] | 0.331 |
-| (0.2, 98) | 0.105674 | 0.208326 | 0.314 | [0.115 0.685 0.001 0.199] | 0.115848 | 0.251311 | 0.367159 | [0.116 0.884] | 0.314 |
-| (0.2, 99) | 0.107548 | 0.207452 | 0.315 | [0.115 0.685 0. 0.2 ] | 0.118836 | 0.249828 | 0.368664 | [0.115 0.885] | 0.315 |
-| (0.25, 0) | 0.124355 | 0.219645 | 0.344 | [0.094 0.656 0. 0.25 ] | 0.128487 | 0.304039 | 0.432526 | [0.094 0.906] | 0.344 |
-| (0.25, 1) | 0.123549 | 0.242451 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.123781 | 0.317136 | 0.440917 | [0.116 0.884] | 0.366 |
-| (0.25, 2) | 0.11547 | 0.24653 | 0.362 | [0.113 0.637 0.001 0.249] | 0.108391 | 0.32999 | 0.43838 | [0.114 0.886] | 0.362 |
-| (0.25, 3) | 0.14217 | 0.23583 | 0.378 | [0.128 0.622 0. 0.25 ] | 0.13991 | 0.305723 | 0.445633 | [0.128 0.872] | 0.378 |
-| (0.25, 4) | 0.115606 | 0.240394 | 0.356 | [0.106 0.644 0. 0.25 ] | 0.10033 | 0.336733 | 0.437063 | [0.106 0.894] | 0.356 |
-| (0.25, 5) | 0.168544 | 0.212456 | 0.381 | [0.131 0.619 0. 0.25 ] | 0.144145 | 0.302683 | 0.446828 | [0.131 0.869] | 0.381 |
-| (0.25, 6) | 0.0947743 | 0.273226 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.095146 | 0.34655 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 7) | 0.113473 | 0.251527 | 0.365 | [0.115 0.635 0. 0.25 ] | 0.111097 | 0.329432 | 0.440529 | [0.115 0.885] | 0.365 |
-| (0.25, 8) | 0.155793 | 0.217207 | 0.373 | [0.123 0.627 0. 0.25 ] | 0.136486 | 0.30717 | 0.443656 | [0.123 0.877] | 0.373 |
-| (0.25, 9) | 0.129944 | 0.218056 | 0.348 | [0.098 0.652 0. 0.25 ] | 0.124308 | 0.30972 | 0.434028 | [0.098 0.902] | 0.348 |
-| (0.25, 10) | 0.137385 | 0.225615 | 0.363 | [0.113 0.637 0. 0.25 ] | 0.134428 | 0.305325 | 0.439754 | [0.113 0.887] | 0.363 |
-| (0.25, 11) | 0.129083 | 0.242917 | 0.372 | [0.122 0.628 0. 0.25 ] | 0.136549 | 0.306714 | 0.443262 | [0.122 0.878] | 0.372 |
-| (0.25, 12) | 0.116791 | 0.239209 | 0.356 | [0.106 0.644 0. 0.25 ] | 0.130234 | 0.306828 | 0.437063 | [0.106 0.894] | 0.356 |
-| (0.25, 13) | 0.126751 | 0.222249 | 0.349 | [0.099 0.651 0. 0.25 ] | 0.113015 | 0.32139 | 0.434405 | [0.099 0.901] | 0.349 |
-| (0.25, 14) | 0.128282 | 0.226718 | 0.355 | [0.105 0.645 0. 0.25 ] | 0.120019 | 0.316662 | 0.436681 | [0.105 0.895] | 0.355 |
-| (0.25, 15) | 0.143813 | 0.218187 | 0.362 | [0.113 0.637 0.001 0.249] | 0.126338 | 0.312042 | 0.43838 | [0.114 0.886] | 0.362 |
-| (0.25, 16) | 0.135428 | 0.238572 | 0.374 | [0.124 0.626 0. 0.25 ] | 0.130811 | 0.313239 | 0.44405 | [0.124 0.876] | 0.374 |
-| (0.25, 17) | 0.112018 | 0.241982 | 0.354 | [0.105 0.645 0.001 0.249] | 0.120587 | 0.314728 | 0.435315 | [0.106 0.894] | 0.354 |
-| (0.25, 18) | 0.159659 | 0.202341 | 0.362 | [0.112 0.638 0. 0.25 ] | 0.14518 | 0.294188 | 0.439367 | [0.112 0.888] | 0.362 |
-| (0.25, 19) | 0.125726 | 0.242274 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.116861 | 0.324835 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 20) | 0.156058 | 0.193942 | 0.35 | [0.1 0.65 0. 0.25] | 0.112552 | 0.32223 | 0.434783 | [0.1 0.9] | 0.35 |
-| (0.25, 21) | 0.115433 | 0.259567 | 0.375 | [0.125 0.625 0. 0.25 ] | 0.0991129 | 0.345332 | 0.444444 | [0.125 0.875] | 0.375 |
-| (0.25, 22) | 0.127289 | 0.232711 | 0.36 | [0.11 0.64 0. 0.25] | 0.115265 | 0.323332 | 0.438596 | [0.11 0.89] | 0.36 |
-| (0.25, 23) | 0.124531 | 0.233469 | 0.358 | [0.109 0.641 0.001 0.249] | 0.0982565 | 0.338586 | 0.436842 | [0.11 0.89] | 0.358 |
-| (0.25, 24) | 0.169186 | 0.195814 | 0.365 | [0.115 0.635 0. 0.25 ] | 0.138074 | 0.302455 | 0.440529 | [0.115 0.885] | 0.365 |
-| (0.25, 25) | 0.128267 | 0.227733 | 0.356 | [0.107 0.643 0.001 0.249] | 0.148625 | 0.287452 | 0.436077 | [0.108 0.892] | 0.356 |
-| (0.25, 26) | 0.126575 | 0.236425 | 0.363 | [0.113 0.637 0. 0.25 ] | 0.133828 | 0.305925 | 0.439754 | [0.113 0.887] | 0.363 |
-| (0.25, 27) | 0.129839 | 0.252161 | 0.382 | [0.132 0.618 0. 0.25 ] | 0.115004 | 0.332224 | 0.447227 | [0.132 0.868] | 0.382 |
-| (0.25, 28) | 0.10892 | 0.24408 | 0.353 | [0.103 0.647 0. 0.25 ] | 0.112931 | 0.322988 | 0.43592 | [0.103 0.897] | 0.353 |
-| (0.25, 29) | 0.121689 | 0.228311 | 0.35 | [0.1 0.65 0. 0.25] | 0.124501 | 0.310282 | 0.434783 | [0.1 0.9] | 0.35 |
-| (0.25, 30) | 0.130389 | 0.216611 | 0.347 | [0.098 0.652 0.001 0.249] | 0.137773 | 0.294895 | 0.432667 | [0.099 0.901] | 0.347 |
-| (0.25, 31) | 0.109612 | 0.257388 | 0.367 | [0.117 0.633 0. 0.25 ] | 0.100272 | 0.341035 | 0.441306 | [0.117 0.883] | 0.367 |
-| (0.25, 32) | 0.123587 | 0.245413 | 0.369 | [0.119 0.631 0. 0.25 ] | 0.133389 | 0.308697 | 0.442087 | [0.119 0.881] | 0.369 |
-| (0.25, 33) | 0.162584 | 0.194416 | 0.357 | [0.107 0.643 0. 0.25 ] | 0.134293 | 0.303153 | 0.437445 | [0.107 0.893] | 0.357 |
-| (0.25, 34) | 0.148317 | 0.213683 | 0.362 | [0.112 0.638 0. 0.25 ] | 0.110308 | 0.329059 | 0.439367 | [0.112 0.888] | 0.362 |
-| (0.25, 35) | 0.11158 | 0.25342 | 0.365 | [0.115 0.635 0. 0.25 ] | 0.110128 | 0.330401 | 0.440529 | [0.115 0.885] | 0.365 |
-| (0.25, 36) | 0.154516 | 0.207484 | 0.362 | [0.113 0.637 0.001 0.249] | 0.125018 | 0.313362 | 0.43838 | [0.114 0.886] | 0.362 |
-| (0.25, 37) | 0.120364 | 0.245636 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.116338 | 0.32458 | 0.440917 | [0.116 0.884] | 0.366 |
-| (0.25, 38) | 0.166437 | 0.190563 | 0.357 | [0.108 0.642 0.001 0.249] | 0.140817 | 0.295642 | 0.436459 | [0.109 0.891] | 0.357 |
-| (0.25, 39) | 0.117464 | 0.243536 | 0.361 | [0.111 0.639 0. 0.25 ] | 0.11287 | 0.326111 | 0.438982 | [0.111 0.889] | 0.361 |
-| (0.25, 40) | 0.139079 | 0.196921 | 0.336 | [0.087 0.663 0.001 0.249] | 0.132232 | 0.296339 | 0.428571 | [0.088 0.912] | 0.336 |
-| (0.25, 41) | 0.106429 | 0.239571 | 0.346 | [0.096 0.654 0. 0.25 ] | 0.113467 | 0.319809 | 0.433276 | [0.096 0.904] | 0.346 |
-| (0.25, 42) | 0.130296 | 0.252704 | 0.383 | [0.133 0.617 0. 0.25 ] | 0.0936963 | 0.353931 | 0.447628 | [0.133 0.867] | 0.383 |
-| (0.25, 43) | 0.143415 | 0.201585 | 0.345 | [0.095 0.655 0. 0.25 ] | 0.143536 | 0.289364 | 0.4329 | [0.095 0.905] | 0.345 |
-| (0.25, 44) | 0.114779 | 0.257221 | 0.372 | [0.123 0.627 0.001 0.249] | 0.103723 | 0.338551 | 0.442274 | [0.124 0.876] | 0.372 |
-| (0.25, 45) | 0.16507 | 0.19593 | 0.361 | [0.111 0.639 0. 0.25 ] | 0.149673 | 0.289309 | 0.438982 | [0.111 0.889] | 0.361 |
-| (0.25, 46) | 0.158965 | 0.201035 | 0.36 | [0.11 0.64 0. 0.25] | 0.135501 | 0.303095 | 0.438596 | [0.11 0.89] | 0.36 |
-| (0.25, 47) | 0.12667 | 0.24133 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.120737 | 0.320959 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 48) | 0.142702 | 0.240298 | 0.383 | [0.133 0.617 0. 0.25 ] | 0.126929 | 0.320699 | 0.447628 | [0.133 0.867] | 0.383 |
-| (0.25, 49) | 0.139296 | 0.228704 | 0.368 | [0.12 0.63 0.002 0.248] | 0.116949 | 0.322768 | 0.439716 | [0.122 0.878] | 0.368 |
-| (0.25, 50) | 0.130214 | 0.218786 | 0.349 | [0.099 0.651 0. 0.25 ] | 0.139032 | 0.295373 | 0.434405 | [0.099 0.901] | 0.349 |
-| (0.25, 51) | 0.126645 | 0.221355 | 0.348 | [0.098 0.652 0. 0.25 ] | 0.111247 | 0.322781 | 0.434028 | [0.098 0.902] | 0.348 |
-| (0.25, 52) | 0.162073 | 0.197927 | 0.36 | [0.111 0.639 0.001 0.249] | 0.145148 | 0.292462 | 0.43761 | [0.112 0.888] | 0.36 |
-| (0.25, 53) | 0.125951 | 0.237049 | 0.363 | [0.115 0.635 0.002 0.248] | 0.121835 | 0.315941 | 0.437776 | [0.117 0.883] | 0.363 |
-| (0.25, 54) | 0.137738 | 0.233262 | 0.371 | [0.121 0.629 0. 0.25 ] | 0.149517 | 0.293353 | 0.44287 | [0.121 0.879] | 0.371 |
-| (0.25, 55) | 0.120461 | 0.226539 | 0.347 | [0.098 0.652 0.001 0.249] | 0.126996 | 0.305672 | 0.432667 | [0.099 0.901] | 0.347 |
-| (0.25, 56) | 0.083097 | 0.271903 | 0.355 | [0.106 0.644 0.001 0.249] | 0.0829992 | 0.352696 | 0.435696 | [0.107 0.893] | 0.355 |
-| (0.25, 57) | 0.152516 | 0.206484 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.156152 | 0.28206 | 0.438212 | [0.109 0.891] | 0.359 |
-| (0.25, 58) | 0.15842 | 0.19158 | 0.35 | [0.101 0.649 0.001 0.249] | 0.140964 | 0.292834 | 0.433798 | [0.102 0.898] | 0.35 |
-| (0.25, 59) | 0.120642 | 0.251358 | 0.372 | [0.122 0.628 0. 0.25 ] | 0.121374 | 0.321889 | 0.443262 | [0.122 0.878] | 0.372 |
-| (0.25, 60) | 0.125145 | 0.231855 | 0.357 | [0.107 0.643 0. 0.25 ] | 0.111299 | 0.326146 | 0.437445 | [0.107 0.893] | 0.357 |
-| (0.25, 61) | 0.141589 | 0.228411 | 0.37 | [0.12 0.63 0. 0.25] | 0.146554 | 0.295924 | 0.442478 | [0.12 0.88] | 0.37 |
-| (0.25, 62) | 0.129288 | 0.210712 | 0.34 | [0.09 0.66 0. 0.25] | 0.123316 | 0.307719 | 0.431034 | [0.09 0.91] | 0.34 |
-| (0.25, 63) | 0.167968 | 0.200032 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.14112 | 0.300576 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 64) | 0.126202 | 0.241798 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.107658 | 0.334039 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 65) | 0.139649 | 0.205351 | 0.345 | [0.095 0.655 0. 0.25 ] | 0.132912 | 0.299989 | 0.4329 | [0.095 0.905] | 0.345 |
-| (0.25, 66) | 0.13461 | 0.22139 | 0.356 | [0.107 0.643 0.001 0.249] | 0.120895 | 0.315182 | 0.436077 | [0.108 0.892] | 0.356 |
-| (0.25, 67) | 0.112746 | 0.246254 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.108761 | 0.329451 | 0.438212 | [0.109 0.891] | 0.359 |
-| (0.25, 68) | 0.125963 | 0.240037 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.12457 | 0.316347 | 0.440917 | [0.116 0.884] | 0.366 |
-| (0.25, 69) | 0.117978 | 0.225022 | 0.343 | [0.094 0.656 0.001 0.249] | 0.122437 | 0.308731 | 0.431169 | [0.095 0.905] | 0.343 |
-| (0.25, 70) | 0.0978247 | 0.271175 | 0.369 | [0.119 0.631 0. 0.25 ] | 0.10638 | 0.335707 | 0.442087 | [0.119 0.881] | 0.369 |
-| (0.25, 71) | 0.122178 | 0.228822 | 0.351 | [0.101 0.649 0. 0.25 ] | 0.112982 | 0.322179 | 0.435161 | [0.101 0.899] | 0.351 |
-| (0.25, 72) | 0.116694 | 0.261306 | 0.378 | [0.128 0.622 0. 0.25 ] | 0.129308 | 0.316324 | 0.445633 | [0.128 0.872] | 0.378 |
-| (0.25, 73) | 0.142151 | 0.206849 | 0.349 | [0.099 0.651 0. 0.25 ] | 0.127291 | 0.307114 | 0.434405 | [0.099 0.901] | 0.349 |
-| (0.25, 74) | 0.119932 | 0.223068 | 0.343 | [0.093 0.657 0. 0.25 ] | 0.118733 | 0.313419 | 0.432152 | [0.093 0.907] | 0.343 |
-| (0.25, 75) | 0.161339 | 0.193661 | 0.355 | [0.105 0.645 0. 0.25 ] | 0.13814 | 0.298541 | 0.436681 | [0.105 0.895] | 0.355 |
-| (0.25, 76) | 0.102897 | 0.251103 | 0.354 | [0.105 0.645 0.001 0.249] | 0.113351 | 0.321964 | 0.435315 | [0.106 0.894] | 0.354 |
-| (0.25, 77) | 0.13454 | 0.22646 | 0.361 | [0.111 0.639 0. 0.25 ] | 0.118977 | 0.320005 | 0.438982 | [0.111 0.889] | 0.361 |
-| (0.25, 78) | 0.139003 | 0.228997 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.124439 | 0.317258 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 79) | 0.128929 | 0.230071 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.109666 | 0.328546 | 0.438212 | [0.109 0.891] | 0.359 |
-| (0.25, 80) | 0.153328 | 0.220672 | 0.374 | [0.124 0.626 0. 0.25 ] | 0.148008 | 0.296042 | 0.44405 | [0.124 0.876] | 0.374 |
-| (0.25, 81) | 0.123484 | 0.247516 | 0.371 | [0.121 0.629 0. 0.25 ] | 0.105126 | 0.337743 | 0.44287 | [0.121 0.879] | 0.371 |
-| (0.25, 82) | 0.12095 | 0.23105 | 0.352 | [0.102 0.648 0. 0.25 ] | 0.102409 | 0.333131 | 0.43554 | [0.102 0.898] | 0.352 |
-| (0.25, 83) | 0.123315 | 0.239685 | 0.363 | [0.113 0.637 0. 0.25 ] | 0.113052 | 0.326702 | 0.439754 | [0.113 0.887] | 0.363 |
-| (0.25, 84) | 0.114865 | 0.244135 | 0.359 | [0.11 0.64 0.001 0.249] | 0.0973808 | 0.339845 | 0.437226 | [0.111 0.889] | 0.359 |
-| (0.25, 85) | 0.141829 | 0.225171 | 0.367 | [0.118 0.632 0.001 0.249] | 0.123299 | 0.317019 | 0.440318 | [0.119 0.881] | 0.367 |
-| (0.25, 86) | 0.136209 | 0.229791 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.123135 | 0.317782 | 0.440917 | [0.116 0.884] | 0.366 |
-| (0.25, 87) | 0.170616 | 0.183384 | 0.354 | [0.104 0.646 0. 0.25 ] | 0.145532 | 0.290768 | 0.4363 | [0.104 0.896] | 0.354 |
-| (0.25, 88) | 0.143335 | 0.223665 | 0.367 | [0.117 0.633 0. 0.25 ] | 0.127911 | 0.313396 | 0.441306 | [0.117 0.883] | 0.367 |
-| (0.25, 89) | 0.137073 | 0.216927 | 0.354 | [0.104 0.646 0. 0.25 ] | 0.154553 | 0.281747 | 0.4363 | [0.104 0.896] | 0.354 |
-| (0.25, 90) | 0.140224 | 0.216776 | 0.357 | [0.107 0.643 0. 0.25 ] | 0.152714 | 0.284731 | 0.437445 | [0.107 0.893] | 0.357 |
-| (0.25, 91) | 0.117738 | 0.253262 | 0.371 | [0.121 0.629 0. 0.25 ] | 0.0959792 | 0.346891 | 0.44287 | [0.121 0.879] | 0.371 |
-| (0.25, 92) | 0.123906 | 0.252094 | 0.376 | [0.126 0.624 0. 0.25 ] | 0.126874 | 0.317966 | 0.44484 | [0.126 0.874] | 0.376 |
-| (0.25, 93) | 0.0661894 | 0.301811 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.0814921 | 0.360204 | 0.441696 | [0.118 0.882] | 0.368 |
-| (0.25, 94) | 0.153841 | 0.208159 | 0.362 | [0.112 0.638 0. 0.25 ] | 0.129741 | 0.309626 | 0.439367 | [0.112 0.888] | 0.362 |
-| (0.25, 95) | 0.144879 | 0.200121 | 0.345 | [0.096 0.654 0.001 0.249] | 0.139426 | 0.29249 | 0.431917 | [0.097 0.903] | 0.345 |
-| (0.25, 96) | 0.151496 | 0.214504 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.112522 | 0.328395 | 0.440917 | [0.116 0.884] | 0.366 |
-| (0.25, 97) | 0.135256 | 0.219744 | 0.355 | [0.105 0.645 0. 0.25 ] | 0.126896 | 0.309785 | 0.436681 | [0.105 0.895] | 0.355 |
-| (0.25, 98) | 0.148867 | 0.194133 | 0.343 | [0.093 0.657 0. 0.25 ] | 0.128798 | 0.303354 | 0.432152 | [0.093 0.907] | 0.343 |
-| (0.25, 99) | 0.137454 | 0.221546 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.108894 | 0.329318 | 0.438212 | [0.109 0.891] | 0.359 |
-| (0.3, 0) | 0.115385 | 0.311615 | 0.427 | [0.127 0.573 0. 0.3 ] | 0.103546 | 0.407963 | 0.511509 | [0.127 0.873] | 0.427 |
-| (0.3, 1) | 0.115234 | 0.275766 | 0.391 | [0.092 0.608 0.001 0.299] | 0.105087 | 0.390356 | 0.495443 | [0.093 0.907] | 0.391 |
-| (0.3, 2) | 0.107756 | 0.296244 | 0.404 | [0.105 0.595 0.001 0.299] | 0.105065 | 0.395773 | 0.500838 | [0.106 0.894] | 0.404 |
-| (0.3, 3) | 0.0940979 | 0.301902 | 0.396 | [0.096 0.604 0. 0.3 ] | 0.0939231 | 0.404416 | 0.498339 | [0.096 0.904] | 0.396 |
-| (0.3, 4) | 0.129976 | 0.268024 | 0.398 | [0.098 0.602 0. 0.3 ] | 0.104953 | 0.394215 | 0.499168 | [0.098 0.902] | 0.398 |
-| (0.3, 5) | 0.128381 | 0.250619 | 0.379 | [0.079 0.621 0. 0.3 ] | 0.101842 | 0.389559 | 0.4914 | [0.079 0.921] | 0.379 |
-| (0.3, 6) | 0.131556 | 0.270444 | 0.402 | [0.102 0.598 0. 0.3 ] | 0.117514 | 0.383321 | 0.500835 | [0.102 0.898] | 0.402 |
-| (0.3, 7) | 0.112026 | 0.284974 | 0.397 | [0.099 0.601 0.002 0.298] | 0.124003 | 0.373078 | 0.497081 | [0.101 0.899] | 0.397 |
-| (0.3, 8) | 0.126207 | 0.290793 | 0.417 | [0.117 0.583 0. 0.3 ] | 0.117671 | 0.389514 | 0.507185 | [0.117 0.883] | 0.417 |
-| (0.3, 9) | 0.139192 | 0.253808 | 0.393 | [0.094 0.606 0.001 0.299] | 0.0999559 | 0.39631 | 0.496266 | [0.095 0.905] | 0.393 |
-| (0.3, 10) | 0.120012 | 0.281988 | 0.402 | [0.102 0.598 0. 0.3 ] | 0.119377 | 0.381458 | 0.500835 | [0.102 0.898] | 0.402 |
-| (0.3, 11) | 0.139279 | 0.260721 | 0.4 | [0.1 0.6 0. 0.3] | 0.117324 | 0.382676 | 0.5 | [0.1 0.9] | 0.4 |
-| (0.3, 12) | 0.116443 | 0.276557 | 0.393 | [0.095 0.605 0.002 0.298] | 0.111133 | 0.384295 | 0.495428 | [0.097 0.903] | 0.393 |
-| (0.3, 13) | 0.124193 | 0.273807 | 0.398 | [0.099 0.601 0.001 0.299] | 0.108405 | 0.389929 | 0.498333 | [0.1 0.9] | 0.398 |
-| (0.3, 14) | 0.12208 | 0.26692 | 0.389 | [0.089 0.611 0. 0.3 ] | 0.127327 | 0.368132 | 0.495458 | [0.089 0.911] | 0.389 |
-| (0.3, 15) | 0.103448 | 0.292552 | 0.396 | [0.096 0.604 0. 0.3 ] | 0.100266 | 0.398073 | 0.498339 | [0.096 0.904] | 0.396 |
-| (0.3, 16) | 0.14551 | 0.24649 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.120372 | 0.376316 | 0.496689 | [0.092 0.908] | 0.392 |
-| (0.3, 17) | 0.141222 | 0.269778 | 0.411 | [0.111 0.589 0. 0.3 ] | 0.118556 | 0.38607 | 0.504626 | [0.111 0.889] | 0.411 |
-| (0.3, 18) | 0.142631 | 0.262369 | 0.405 | [0.105 0.595 0. 0.3 ] | 0.0938785 | 0.408214 | 0.502092 | [0.105 0.895] | 0.405 |
-| (0.3, 19) | 0.14518 | 0.26782 | 0.413 | [0.114 0.586 0.001 0.299] | 0.125934 | 0.378707 | 0.504641 | [0.115 0.885] | 0.413 |
-| (0.3, 20) | 0.117111 | 0.292889 | 0.41 | [0.11 0.59 0. 0.3 ] | 0.100578 | 0.403624 | 0.504202 | [0.11 0.89] | 0.41 |
-| (0.3, 21) | 0.147531 | 0.264469 | 0.412 | [0.113 0.587 0.001 0.299] | 0.116326 | 0.387889 | 0.504216 | [0.114 0.886] | 0.412 |
-| (0.3, 22) | 0.106063 | 0.292937 | 0.399 | [0.099 0.601 0. 0.3 ] | 0.106593 | 0.39299 | 0.499584 | [0.099 0.901] | 0.399 |
-| (0.3, 23) | 0.148613 | 0.250387 | 0.399 | [0.099 0.601 0. 0.3 ] | 0.127635 | 0.371949 | 0.499584 | [0.099 0.901] | 0.399 |
-| (0.3, 24) | 0.154573 | 0.248427 | 0.403 | [0.103 0.597 0. 0.3 ] | 0.114545 | 0.386709 | 0.501253 | [0.103 0.897] | 0.403 |
-| (0.3, 25) | 0.126976 | 0.267024 | 0.394 | [0.094 0.606 0. 0.3 ] | 0.107205 | 0.390308 | 0.497512 | [0.094 0.906] | 0.394 |
-| (0.3, 26) | 0.0936366 | 0.315363 | 0.409 | [0.109 0.591 0. 0.3 ] | 0.0963521 | 0.407426 | 0.503778 | [0.109 0.891] | 0.409 |
-| (0.3, 27) | 0.112656 | 0.269344 | 0.382 | [0.083 0.617 0.001 0.299] | 0.104119 | 0.387657 | 0.491776 | [0.084 0.916] | 0.382 |
-| (0.3, 28) | 0.162282 | 0.249718 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.125725 | 0.379325 | 0.505051 | [0.112 0.888] | 0.412 |
-| (0.3, 29) | 0.144141 | 0.254859 | 0.399 | [0.1 0.6 0.001 0.299] | 0.10784 | 0.390909 | 0.498749 | [0.101 0.899] | 0.399 |
-| (0.3, 30) | 0.148497 | 0.254503 | 0.403 | [0.103 0.597 0. 0.3 ] | 0.114328 | 0.386925 | 0.501253 | [0.103 0.897] | 0.403 |
-| (0.3, 31) | 0.132418 | 0.280582 | 0.413 | [0.113 0.587 0. 0.3 ] | 0.110571 | 0.394905 | 0.505476 | [0.113 0.887] | 0.413 |
-| (0.3, 32) | 0.112737 | 0.277263 | 0.39 | [0.091 0.609 0.001 0.299] | 0.105898 | 0.389135 | 0.495033 | [0.092 0.908] | 0.39 |
-| (0.3, 33) | 0.141008 | 0.265992 | 0.407 | [0.107 0.593 0. 0.3 ] | 0.124772 | 0.378162 | 0.502934 | [0.107 0.893] | 0.407 |
-| (0.3, 34) | 0.138324 | 0.254676 | 0.393 | [0.093 0.607 0. 0.3 ] | 0.132808 | 0.364293 | 0.4971 | [0.093 0.907] | 0.393 |
-| (0.3, 35) | 0.142124 | 0.270876 | 0.413 | [0.113 0.587 0. 0.3 ] | 0.114159 | 0.391317 | 0.505476 | [0.113 0.887] | 0.413 |
-| (0.3, 36) | 0.122152 | 0.278848 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.0982835 | 0.402133 | 0.500417 | [0.101 0.899] | 0.401 |
-| (0.3, 37) | 0.131292 | 0.261708 | 0.393 | [0.093 0.607 0. 0.3 ] | 0.123554 | 0.373546 | 0.4971 | [0.093 0.907] | 0.393 |
-| (0.3, 38) | 0.128837 | 0.288163 | 0.417 | [0.118 0.582 0.001 0.299] | 0.108684 | 0.397666 | 0.506351 | [0.119 0.881] | 0.417 |
-| (0.3, 39) | 0.129308 | 0.262692 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.106602 | 0.390086 | 0.496689 | [0.092 0.908] | 0.392 |
-| (0.3, 40) | 0.140918 | 0.253082 | 0.394 | [0.095 0.605 0.001 0.299] | 0.112835 | 0.383843 | 0.496678 | [0.096 0.904] | 0.394 |
-| (0.3, 41) | 0.116026 | 0.291974 | 0.408 | [0.108 0.592 0. 0.3 ] | 0.0894206 | 0.413935 | 0.503356 | [0.108 0.892] | 0.408 |
-| (0.3, 42) | 0.126607 | 0.266393 | 0.393 | [0.095 0.605 0.002 0.298] | 0.112307 | 0.383122 | 0.495428 | [0.097 0.903] | 0.393 |
-| (0.3, 43) | 0.100563 | 0.307437 | 0.408 | [0.109 0.591 0.001 0.299] | 0.099999 | 0.402522 | 0.502521 | [0.11 0.89] | 0.408 |
-| (0.3, 44) | 0.129683 | 0.262317 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.10938 | 0.387309 | 0.496689 | [0.092 0.908] | 0.392 |
-| (0.3, 45) | 0.113322 | 0.281678 | 0.395 | [0.095 0.605 0. 0.3 ] | 0.102612 | 0.395314 | 0.497925 | [0.095 0.905] | 0.395 |
-| (0.3, 46) | 0.121586 | 0.283414 | 0.405 | [0.105 0.595 0. 0.3 ] | 0.111687 | 0.390405 | 0.502092 | [0.105 0.895] | 0.405 |
-| (0.3, 47) | 0.117878 | 0.303122 | 0.421 | [0.121 0.579 0. 0.3 ] | 0.101569 | 0.407336 | 0.508906 | [0.121 0.879] | 0.421 |
-| (0.3, 48) | 0.114245 | 0.286755 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.105145 | 0.395272 | 0.500417 | [0.101 0.899] | 0.401 |
-| (0.3, 49) | 0.138991 | 0.244009 | 0.383 | [0.083 0.617 0. 0.3 ] | 0.126666 | 0.366349 | 0.493016 | [0.083 0.917] | 0.383 |
-| (0.3, 50) | 0.120115 | 0.271885 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.121823 | 0.374866 | 0.496689 | [0.092 0.908] | 0.392 |
-| (0.3, 51) | 0.11579 | 0.26921 | 0.385 | [0.085 0.615 0. 0.3 ] | 0.110148 | 0.383679 | 0.493827 | [0.085 0.915] | 0.385 |
-| (0.3, 52) | 0.134915 | 0.275085 | 0.41 | [0.111 0.589 0.001 0.299] | 0.0925126 | 0.410854 | 0.503367 | [0.112 0.888] | 0.41 |
-| (0.3, 53) | 0.142717 | 0.261283 | 0.404 | [0.106 0.594 0.002 0.298] | 0.118655 | 0.381345 | 0.5 | [0.108 0.892] | 0.404 |
-| (0.3, 54) | 0.154873 | 0.236127 | 0.391 | [0.091 0.609 0. 0.3 ] | 0.115805 | 0.380473 | 0.496278 | [0.091 0.909] | 0.391 |
-| (0.3, 55) | 0.117916 | 0.297084 | 0.415 | [0.115 0.585 0. 0.3 ] | 0.113195 | 0.393134 | 0.506329 | [0.115 0.885] | 0.415 |
-| (0.3, 56) | 0.119119 | 0.291881 | 0.411 | [0.111 0.589 0. 0.3 ] | 0.0887019 | 0.415924 | 0.504626 | [0.111 0.889] | 0.411 |
-| (0.3, 57) | 0.136571 | 0.269429 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.121916 | 0.380597 | 0.502513 | [0.106 0.894] | 0.406 |
-| (0.3, 58) | 0.149654 | 0.235346 | 0.385 | [0.086 0.614 0.001 0.299] | 0.118077 | 0.374916 | 0.492993 | [0.087 0.913] | 0.385 |
-| (0.3, 59) | 0.110281 | 0.305719 | 0.416 | [0.116 0.584 0. 0.3 ] | 0.113127 | 0.39363 | 0.506757 | [0.116 0.884] | 0.416 |
-| (0.3, 60) | 0.105847 | 0.288153 | 0.394 | [0.094 0.606 0. 0.3 ] | 0.108523 | 0.388989 | 0.497512 | [0.094 0.906] | 0.394 |
-| (0.3, 61) | 0.118659 | 0.288341 | 0.407 | [0.107 0.593 0. 0.3 ] | 0.085541 | 0.417393 | 0.502934 | [0.107 0.893] | 0.407 |
-| (0.3, 62) | 0.129623 | 0.283377 | 0.413 | [0.115 0.585 0.002 0.298] | 0.112032 | 0.391772 | 0.503804 | [0.117 0.883] | 0.413 |
-| (0.3, 63) | 0.126394 | 0.269606 | 0.396 | [0.096 0.604 0. 0.3 ] | 0.112563 | 0.385776 | 0.498339 | [0.096 0.904] | 0.396 |
-| (0.3, 64) | 0.139585 | 0.264415 | 0.404 | [0.104 0.596 0. 0.3 ] | 0.111884 | 0.389788 | 0.501672 | [0.104 0.896] | 0.404 |
-| (0.3, 65) | 0.0951434 | 0.310857 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.0848641 | 0.417648 | 0.502513 | [0.106 0.894] | 0.406 |
-| (0.3, 66) | 0.111057 | 0.277943 | 0.389 | [0.089 0.611 0. 0.3 ] | 0.10445 | 0.391009 | 0.495458 | [0.089 0.911] | 0.389 |
-| (0.3, 67) | 0.0656081 | 0.346392 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.0574239 | 0.447627 | 0.505051 | [0.112 0.888] | 0.412 |
-| (0.3, 68) | 0.115383 | 0.293617 | 0.409 | [0.109 0.591 0. 0.3 ] | 0.0971393 | 0.406639 | 0.503778 | [0.109 0.891] | 0.409 |
-| (0.3, 69) | 0.11694 | 0.28806 | 0.405 | [0.105 0.595 0. 0.3 ] | 0.118732 | 0.38336 | 0.502092 | [0.105 0.895] | 0.405 |
-| (0.3, 70) | 0.129901 | 0.276099 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.11687 | 0.385643 | 0.502513 | [0.106 0.894] | 0.406 |
-| (0.3, 71) | 0.12312 | 0.29188 | 0.415 | [0.115 0.585 0. 0.3 ] | 0.0975558 | 0.408773 | 0.506329 | [0.115 0.885] | 0.415 |
-| (0.3, 72) | 0.119927 | 0.294073 | 0.414 | [0.114 0.586 0. 0.3 ] | 0.096911 | 0.408991 | 0.505902 | [0.114 0.886] | 0.414 |
-| (0.3, 73) | 0.133123 | 0.253877 | 0.387 | [0.087 0.613 0. 0.3 ] | 0.110938 | 0.383703 | 0.494641 | [0.087 0.913] | 0.387 |
-| (0.3, 74) | 0.0891778 | 0.333822 | 0.423 | [0.123 0.577 0. 0.3 ] | 0.0806618 | 0.429109 | 0.509771 | [0.123 0.877] | 0.423 |
-| (0.3, 75) | 0.0964315 | 0.321569 | 0.418 | [0.118 0.582 0. 0.3 ] | 0.0962955 | 0.411319 | 0.507614 | [0.118 0.882] | 0.418 |
-| (0.3, 76) | 0.152005 | 0.253995 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.118398 | 0.384115 | 0.502513 | [0.106 0.894] | 0.406 |
-| (0.3, 77) | 0.139943 | 0.259057 | 0.399 | [0.099 0.601 0. 0.3 ] | 0.116276 | 0.383307 | 0.499584 | [0.099 0.901] | 0.399 |
-| (0.3, 78) | 0.13643 | 0.26457 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.112532 | 0.387885 | 0.500417 | [0.101 0.899] | 0.401 |
-| (0.3, 79) | 0.113834 | 0.290166 | 0.404 | [0.104 0.596 0. 0.3 ] | 0.103453 | 0.398219 | 0.501672 | [0.104 0.896] | 0.404 |
-| (0.3, 80) | 0.162074 | 0.225926 | 0.388 | [0.089 0.611 0.001 0.299] | 0.127037 | 0.367178 | 0.494215 | [0.09 0.91] | 0.388 |
-| (0.3, 81) | 0.112507 | 0.294493 | 0.407 | [0.107 0.593 0. 0.3 ] | 0.112868 | 0.390066 | 0.502934 | [0.107 0.893] | 0.407 |
-| (0.3, 82) | 0.137672 | 0.250328 | 0.388 | [0.088 0.612 0. 0.3 ] | 0.107459 | 0.38759 | 0.49505 | [0.088 0.912] | 0.388 |
-| (0.3, 83) | 0.11512 | 0.29688 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.0942575 | 0.410793 | 0.505051 | [0.112 0.888] | 0.412 |
-| (0.3, 84) | 0.103276 | 0.290724 | 0.394 | [0.096 0.604 0.002 0.298] | 0.0984201 | 0.39742 | 0.49584 | [0.098 0.902] | 0.394 |
-| (0.3, 85) | 0.128535 | 0.269465 | 0.398 | [0.099 0.601 0.001 0.299] | 0.102733 | 0.3956 | 0.498333 | [0.1 0.9] | 0.398 |
-| (0.3, 86) | 0.117567 | 0.290433 | 0.408 | [0.108 0.592 0. 0.3 ] | 0.11328 | 0.390076 | 0.503356 | [0.108 0.892] | 0.408 |
-| (0.3, 87) | 0.141018 | 0.252982 | 0.394 | [0.096 0.604 0.002 0.298] | 0.108792 | 0.387049 | 0.49584 | [0.098 0.902] | 0.394 |
-| (0.3, 88) | 0.114183 | 0.286817 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.092482 | 0.407935 | 0.500417 | [0.101 0.899] | 0.401 |
-| (0.3, 89) | 0.110207 | 0.302793 | 0.413 | [0.114 0.586 0.001 0.299] | 0.117155 | 0.387487 | 0.504641 | [0.115 0.885] | 0.413 |
-| (0.3, 90) | 0.129401 | 0.284599 | 0.414 | [0.114 0.586 0. 0.3 ] | 0.10979 | 0.396113 | 0.505902 | [0.114 0.886] | 0.414 |
-| (0.3, 91) | 0.12667 | 0.28733 | 0.414 | [0.115 0.585 0.001 0.299] | 0.109093 | 0.395974 | 0.505068 | [0.116 0.884] | 0.414 |
-| (0.3, 92) | 0.0895823 | 0.309418 | 0.399 | [0.1 0.6 0.001 0.299] | 0.0919172 | 0.406832 | 0.498749 | [0.101 0.899] | 0.399 |
-| (0.3, 93) | 0.13851 | 0.26349 | 0.402 | [0.103 0.597 0.001 0.299] | 0.116828 | 0.383172 | 0.5 | [0.104 0.896] | 0.402 |
-| (0.3, 94) | 0.110087 | 0.308913 | 0.419 | [0.12 0.58 0.001 0.299] | 0.103164 | 0.404046 | 0.507209 | [0.121 0.879] | 0.419 |
-| (0.3, 95) | 0.120184 | 0.297816 | 0.418 | [0.118 0.582 0. 0.3 ] | 0.098135 | 0.409479 | 0.507614 | [0.118 0.882] | 0.418 |
-| (0.3, 96) | 0.133316 | 0.256684 | 0.39 | [0.09 0.61 0. 0.3 ] | 0.116543 | 0.379325 | 0.495868 | [0.09 0.91] | 0.39 |
-| (0.3, 97) | 0.0983323 | 0.313668 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.0720765 | 0.432974 | 0.505051 | [0.112 0.888] | 0.412 |
-| (0.3, 98) | 0.136707 | 0.279293 | 0.416 | [0.116 0.584 0. 0.3 ] | 0.113834 | 0.392923 | 0.506757 | [0.116 0.884] | 0.416 |
-| (0.3, 99) | 0.128764 | 0.277236 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.127621 | 0.374892 | 0.502513 | [0.106 0.894] | 0.406 |
-| (0.35, 0) | 0.127734 | 0.323266 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.106 | 0.454448 | 0.560448 | [0.101 0.899] | 0.451 |
-| (0.35, 1) | 0.126857 | 0.316143 | 0.443 | [0.093 0.557 0. 0.35 ] | 0.113086 | 0.443795 | 0.556881 | [0.093 0.907] | 0.443 |
-| (0.35, 2) | 0.0879283 | 0.358072 | 0.446 | [0.097 0.553 0.001 0.349] | 0.0770572 | 0.480451 | 0.557508 | [0.098 0.902] | 0.446 |
-| (0.35, 3) | 0.111434 | 0.340566 | 0.452 | [0.102 0.548 0. 0.35 ] | 0.107314 | 0.453583 | 0.560897 | [0.102 0.898] | 0.452 |
-| (0.35, 4) | 0.158193 | 0.295807 | 0.454 | [0.104 0.546 0. 0.35 ] | 0.132322 | 0.429476 | 0.561798 | [0.104 0.896] | 0.454 |
-| (0.35, 5) | 0.120109 | 0.325891 | 0.446 | [0.097 0.553 0.001 0.349] | 0.112725 | 0.444783 | 0.557508 | [0.098 0.902] | 0.446 |
-| (0.35, 6) | 0.0941796 | 0.35182 | 0.446 | [0.096 0.554 0. 0.35 ] | 0.0882179 | 0.469996 | 0.558214 | [0.096 0.904] | 0.446 |
-| (0.35, 7) | 0.103097 | 0.345903 | 0.449 | [0.099 0.551 0. 0.35 ] | 0.099472 | 0.46008 | 0.559552 | [0.099 0.901] | 0.449 |
-| (0.35, 8) | 0.138126 | 0.330874 | 0.469 | [0.119 0.531 0. 0.35 ] | 0.100208 | 0.468435 | 0.568643 | [0.119 0.881] | 0.469 |
-| (0.35, 9) | 0.107922 | 0.347078 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.0834859 | 0.478763 | 0.562249 | [0.105 0.895] | 0.455 |
-| (0.35, 10) | 0.0992061 | 0.337794 | 0.437 | [0.087 0.563 0. 0.35 ] | 0.091621 | 0.462615 | 0.554236 | [0.087 0.913] | 0.437 |
-| (0.35, 11) | 0.105041 | 0.344959 | 0.45 | [0.1 0.55 0. 0.35] | 0.0902889 | 0.469711 | 0.56 | [0.1 0.9] | 0.45 |
-| (0.35, 12) | 0.100877 | 0.350123 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.0870643 | 0.473384 | 0.560448 | [0.101 0.899] | 0.451 |
-| (0.35, 13) | 0.0960624 | 0.345938 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0724629 | 0.483976 | 0.556439 | [0.092 0.908] | 0.442 |
-| (0.35, 14) | 0.131091 | 0.299909 | 0.431 | [0.081 0.569 0. 0.35 ] | 0.112462 | 0.439153 | 0.551615 | [0.081 0.919] | 0.431 |
-| (0.35, 15) | 0.120561 | 0.325439 | 0.446 | [0.097 0.553 0.001 0.349] | 0.0972215 | 0.460286 | 0.557508 | [0.098 0.902] | 0.446 |
-| (0.35, 16) | 0.107446 | 0.339554 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.0781809 | 0.480478 | 0.558659 | [0.097 0.903] | 0.447 |
-| (0.35, 17) | 0.12172 | 0.33228 | 0.454 | [0.104 0.546 0. 0.35 ] | 0.0898545 | 0.471943 | 0.561798 | [0.104 0.896] | 0.454 |
-| (0.35, 18) | 0.110049 | 0.365951 | 0.476 | [0.126 0.524 0. 0.35 ] | 0.0858809 | 0.486014 | 0.571895 | [0.126 0.874] | 0.476 |
-| (0.35, 19) | 0.108301 | 0.329699 | 0.438 | [0.089 0.561 0.001 0.349] | 0.0928654 | 0.461103 | 0.553968 | [0.09 0.91] | 0.438 |
-| (0.35, 20) | 0.113459 | 0.319541 | 0.433 | [0.083 0.567 0. 0.35 ] | 0.087382 | 0.465104 | 0.552486 | [0.083 0.917] | 0.433 |
-| (0.35, 21) | 0.123105 | 0.329895 | 0.453 | [0.103 0.547 0. 0.35 ] | 0.105268 | 0.456079 | 0.561347 | [0.103 0.897] | 0.453 |
-| (0.35, 22) | 0.113375 | 0.345625 | 0.459 | [0.109 0.541 0. 0.35 ] | 0.0933376 | 0.470724 | 0.564061 | [0.109 0.891] | 0.459 |
-| (0.35, 23) | 0.118606 | 0.329394 | 0.448 | [0.098 0.552 0. 0.35 ] | 0.0897363 | 0.469369 | 0.559105 | [0.098 0.902] | 0.448 |
-| (0.35, 24) | 0.127113 | 0.306887 | 0.434 | [0.085 0.565 0.001 0.349] | 0.0946077 | 0.457607 | 0.552215 | [0.086 0.914] | 0.434 |
-| (0.35, 25) | 0.119535 | 0.320465 | 0.44 | [0.09 0.56 0. 0.35] | 0.115511 | 0.440044 | 0.555556 | [0.09 0.91] | 0.44 |
-| (0.35, 26) | 0.0883172 | 0.344683 | 0.433 | [0.084 0.566 0.001 0.349] | 0.0744312 | 0.477347 | 0.551779 | [0.085 0.915] | 0.433 |
-| (0.35, 27) | 0.166992 | 0.279008 | 0.446 | [0.096 0.554 0. 0.35 ] | 0.137423 | 0.42079 | 0.558214 | [0.096 0.904] | 0.446 |
-| (0.35, 28) | 0.0954868 | 0.340513 | 0.436 | [0.087 0.563 0.001 0.349] | 0.0830672 | 0.470023 | 0.55309 | [0.088 0.912] | 0.436 |
-| (0.35, 29) | 0.0778668 | 0.367133 | 0.445 | [0.096 0.554 0.001 0.349] | 0.0649534 | 0.49211 | 0.557063 | [0.097 0.903] | 0.445 |
-| (0.35, 30) | 0.107221 | 0.325779 | 0.433 | [0.083 0.567 0. 0.35 ] | 0.0822103 | 0.470276 | 0.552486 | [0.083 0.917] | 0.433 |
-| (0.35, 31) | 0.102419 | 0.339581 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0894659 | 0.466973 | 0.556439 | [0.092 0.908] | 0.442 |
-| (0.35, 32) | 0.119917 | 0.328083 | 0.448 | [0.098 0.552 0. 0.35 ] | 0.0886716 | 0.470434 | 0.559105 | [0.098 0.902] | 0.448 |
-| (0.35, 33) | 0.11129 | 0.34371 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.0841548 | 0.478094 | 0.562249 | [0.105 0.895] | 0.455 |
-| (0.35, 34) | 0.101306 | 0.349694 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.0869425 | 0.473506 | 0.560448 | [0.101 0.899] | 0.451 |
-| (0.35, 35) | 0.109456 | 0.333544 | 0.443 | [0.094 0.556 0.001 0.349] | 0.106623 | 0.449552 | 0.556175 | [0.095 0.905] | 0.443 |
-| (0.35, 36) | 0.0992197 | 0.34478 | 0.444 | [0.094 0.556 0. 0.35 ] | 0.0943453 | 0.46298 | 0.557325 | [0.094 0.906] | 0.444 |
-| (0.35, 37) | 0.150907 | 0.288093 | 0.439 | [0.09 0.56 0.001 0.349] | 0.119051 | 0.435357 | 0.554408 | [0.091 0.909] | 0.439 |
-| (0.35, 38) | 0.109748 | 0.325252 | 0.435 | [0.085 0.565 0. 0.35 ] | 0.0863649 | 0.466995 | 0.55336 | [0.085 0.915] | 0.435 |
-| (0.35, 39) | 0.145428 | 0.291572 | 0.437 | [0.088 0.562 0.001 0.349] | 0.128978 | 0.424551 | 0.553529 | [0.089 0.911] | 0.437 |
-| (0.35, 40) | 0.098426 | 0.360574 | 0.459 | [0.11 0.54 0.001 0.349] | 0.07388 | 0.489478 | 0.563358 | [0.111 0.889] | 0.459 |
-| (0.35, 41) | 0.13594 | 0.31106 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.116727 | 0.441932 | 0.558659 | [0.097 0.903] | 0.447 |
-| (0.35, 42) | 0.123184 | 0.312816 | 0.436 | [0.086 0.564 0. 0.35 ] | 0.114021 | 0.439777 | 0.553797 | [0.086 0.914] | 0.436 |
-| (0.35, 43) | 0.128692 | 0.318308 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.102665 | 0.455994 | 0.558659 | [0.097 0.903] | 0.447 |
-| (0.35, 44) | 0.136286 | 0.292714 | 0.429 | [0.08 0.57 0.001 0.349] | 0.104948 | 0.445091 | 0.550039 | [0.081 0.919] | 0.429 |
-| (0.35, 45) | 0.108885 | 0.336115 | 0.445 | [0.095 0.555 0. 0.35 ] | 0.0977137 | 0.460055 | 0.557769 | [0.095 0.905] | 0.445 |
-| (0.35, 46) | 0.112286 | 0.334714 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.102874 | 0.455785 | 0.558659 | [0.097 0.903] | 0.447 |
-| (0.35, 47) | 0.0906932 | 0.369307 | 0.46 | [0.11 0.54 0. 0.35] | 0.0778993 | 0.486617 | 0.564516 | [0.11 0.89] | 0.46 |
-| (0.35, 48) | 0.137978 | 0.315022 | 0.453 | [0.103 0.547 0. 0.35 ] | 0.102033 | 0.459314 | 0.561347 | [0.103 0.897] | 0.453 |
-| (0.35, 49) | 0.116168 | 0.334832 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.0912107 | 0.469238 | 0.560448 | [0.101 0.899] | 0.451 |
-| (0.35, 50) | 0.104287 | 0.334713 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.0944456 | 0.460669 | 0.555115 | [0.089 0.911] | 0.439 |
-| (0.35, 51) | 0.128891 | 0.313109 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0930384 | 0.4634 | 0.556439 | [0.092 0.908] | 0.442 |
-| (0.35, 52) | 0.113322 | 0.357678 | 0.471 | [0.121 0.529 0. 0.35 ] | 0.100441 | 0.469128 | 0.569569 | [0.121 0.879] | 0.471 |
-| (0.35, 53) | 0.104489 | 0.331511 | 0.436 | [0.086 0.564 0. 0.35 ] | 0.0901448 | 0.463653 | 0.553797 | [0.086 0.914] | 0.436 |
-| (0.35, 54) | 0.0996681 | 0.346332 | 0.446 | [0.096 0.554 0. 0.35 ] | 0.0920318 | 0.466182 | 0.558214 | [0.096 0.904] | 0.446 |
-| (0.35, 55) | 0.119316 | 0.311684 | 0.431 | [0.081 0.569 0. 0.35 ] | 0.108829 | 0.442786 | 0.551615 | [0.081 0.919] | 0.431 |
-| (0.35, 56) | 0.133962 | 0.304038 | 0.438 | [0.089 0.561 0.001 0.349] | 0.106918 | 0.44705 | 0.553968 | [0.09 0.91] | 0.438 |
-| (0.35, 57) | 0.138717 | 0.316283 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.11544 | 0.446809 | 0.562249 | [0.105 0.895] | 0.455 |
-| (0.35, 58) | 0.139865 | 0.314135 | 0.454 | [0.105 0.545 0.001 0.349] | 0.0996406 | 0.461453 | 0.561093 | [0.106 0.894] | 0.454 |
-| (0.35, 59) | 0.117694 | 0.326306 | 0.444 | [0.094 0.556 0. 0.35 ] | 0.0946397 | 0.462685 | 0.557325 | [0.094 0.906] | 0.444 |
-| (0.35, 60) | 0.0823521 | 0.383648 | 0.466 | [0.116 0.534 0. 0.35 ] | 0.0751242 | 0.492137 | 0.567261 | [0.116 0.884] | 0.466 |
-| (0.35, 61) | 0.114932 | 0.324068 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.107789 | 0.447326 | 0.555115 | [0.089 0.911] | 0.439 |
-| (0.35, 62) | 0.0971008 | 0.341899 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.0794721 | 0.475643 | 0.555115 | [0.089 0.911] | 0.439 |
-| (0.35, 63) | 0.114859 | 0.339141 | 0.454 | [0.105 0.545 0.001 0.349] | 0.101821 | 0.459272 | 0.561093 | [0.106 0.894] | 0.454 |
-| (0.35, 64) | 0.105616 | 0.336384 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0953635 | 0.461075 | 0.556439 | [0.092 0.908] | 0.442 |
-| (0.35, 65) | 0.109411 | 0.330589 | 0.44 | [0.09 0.56 0. 0.35] | 0.0857621 | 0.469794 | 0.555556 | [0.09 0.91] | 0.44 |
-| (0.35, 66) | 0.139524 | 0.314476 | 0.454 | [0.104 0.546 0. 0.35 ] | 0.113682 | 0.448115 | 0.561798 | [0.104 0.896] | 0.454 |
-| (0.35, 67) | 0.114339 | 0.340661 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.106207 | 0.456042 | 0.562249 | [0.105 0.895] | 0.455 |
-| (0.35, 68) | 0.115384 | 0.316616 | 0.432 | [0.082 0.568 0. 0.35 ] | 0.104768 | 0.447283 | 0.55205 | [0.082 0.918] | 0.432 |
-| (0.35, 69) | 0.136346 | 0.305654 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.111795 | 0.444644 | 0.556439 | [0.092 0.908] | 0.442 |
-| (0.35, 70) | 0.120153 | 0.319847 | 0.44 | [0.09 0.56 0. 0.35] | 0.109676 | 0.44588 | 0.555556 | [0.09 0.91] | 0.44 |
-| (0.35, 71) | 0.111197 | 0.350803 | 0.462 | [0.112 0.538 0. 0.35 ] | 0.081468 | 0.48396 | 0.565428 | [0.112 0.888] | 0.462 |
-| (0.35, 72) | 0.13692 | 0.30608 | 0.443 | [0.093 0.557 0. 0.35 ] | 0.117318 | 0.439564 | 0.556881 | [0.093 0.907] | 0.443 |
-| (0.35, 73) | 0.124503 | 0.328497 | 0.453 | [0.103 0.547 0. 0.35 ] | 0.0945593 | 0.466788 | 0.561347 | [0.103 0.897] | 0.453 |
-| (0.35, 74) | 0.136985 | 0.301015 | 0.438 | [0.088 0.562 0. 0.35 ] | 0.0994015 | 0.455274 | 0.554675 | [0.088 0.912] | 0.438 |
-| (0.35, 75) | 0.122077 | 0.331923 | 0.454 | [0.106 0.544 0.002 0.348] | 0.0941126 | 0.466274 | 0.560386 | [0.108 0.892] | 0.454 |
-| (0.35, 76) | 0.105174 | 0.352826 | 0.458 | [0.109 0.541 0.001 0.349] | 0.0934764 | 0.469427 | 0.562903 | [0.11 0.89] | 0.458 |
-| (0.35, 77) | 0.109797 | 0.325203 | 0.435 | [0.086 0.564 0.001 0.349] | 0.0970415 | 0.455611 | 0.552652 | [0.087 0.913] | 0.435 |
-| (0.35, 78) | 0.103501 | 0.344499 | 0.448 | [0.098 0.552 0. 0.35 ] | 0.0972722 | 0.461833 | 0.559105 | [0.098 0.902] | 0.448 |
-| (0.35, 79) | 0.0992824 | 0.347718 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.0883709 | 0.470288 | 0.558659 | [0.097 0.903] | 0.447 |
-| (0.35, 80) | 0.0864577 | 0.359542 | 0.446 | [0.097 0.553 0.001 0.349] | 0.0811096 | 0.476398 | 0.557508 | [0.098 0.902] | 0.446 |
-| (0.35, 81) | 0.0944448 | 0.362555 | 0.457 | [0.107 0.543 0. 0.35 ] | 0.0824714 | 0.480682 | 0.563154 | [0.107 0.893] | 0.457 |
-| (0.35, 82) | 0.131583 | 0.318417 | 0.45 | [0.101 0.549 0.001 0.349] | 0.10794 | 0.451355 | 0.559295 | [0.102 0.898] | 0.45 |
-| (0.35, 83) | 0.120998 | 0.331002 | 0.452 | [0.102 0.548 0. 0.35 ] | 0.104399 | 0.456498 | 0.560897 | [0.102 0.898] | 0.452 |
-| (0.35, 84) | 0.106906 | 0.345094 | 0.452 | [0.103 0.547 0.001 0.349] | 0.0750503 | 0.485142 | 0.560193 | [0.104 0.896] | 0.452 |
-| (0.35, 85) | 0.120944 | 0.337056 | 0.458 | [0.108 0.542 0. 0.35 ] | 0.0885901 | 0.475017 | 0.563607 | [0.108 0.892] | 0.458 |
-| (0.35, 86) | 0.105667 | 0.339333 | 0.445 | [0.095 0.555 0. 0.35 ] | 0.0975882 | 0.460181 | 0.557769 | [0.095 0.905] | 0.445 |
-| (0.35, 87) | 0.14568 | 0.29532 | 0.441 | [0.091 0.559 0. 0.35 ] | 0.114812 | 0.441184 | 0.555997 | [0.091 0.909] | 0.441 |
-| (0.35, 88) | 0.113016 | 0.325984 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.106299 | 0.448816 | 0.555115 | [0.089 0.911] | 0.439 |
-| (0.35, 89) | 0.100033 | 0.342967 | 0.443 | [0.093 0.557 0. 0.35 ] | 0.0877762 | 0.469105 | 0.556881 | [0.093 0.907] | 0.443 |
-| (0.35, 90) | 0.130903 | 0.300097 | 0.431 | [0.081 0.569 0. 0.35 ] | 0.128361 | 0.423255 | 0.551615 | [0.081 0.919] | 0.431 |
-| (0.35, 91) | 0.124577 | 0.332423 | 0.457 | [0.107 0.543 0. 0.35 ] | 0.0952436 | 0.46791 | 0.563154 | [0.107 0.893] | 0.457 |
-| (0.35, 92) | 0.105592 | 0.333408 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.098634 | 0.456481 | 0.555115 | [0.089 0.911] | 0.439 |
-| (0.35, 93) | 0.140823 | 0.304177 | 0.445 | [0.096 0.554 0.001 0.349] | 0.125783 | 0.43128 | 0.557063 | [0.097 0.903] | 0.445 |
-| (0.35, 94) | 0.121894 | 0.316106 | 0.438 | [0.089 0.561 0.001 0.349] | 0.0975567 | 0.456412 | 0.553968 | [0.09 0.91] | 0.438 |
-| (0.35, 95) | 0.111933 | 0.332067 | 0.444 | [0.094 0.556 0. 0.35 ] | 0.106763 | 0.450562 | 0.557325 | [0.094 0.906] | 0.444 |
-| (0.35, 96) | 0.116825 | 0.334175 | 0.451 | [0.102 0.548 0.001 0.349] | 0.098681 | 0.461062 | 0.559743 | [0.103 0.897] | 0.451 |
-| (0.35, 97) | 0.0768109 | 0.383189 | 0.46 | [0.11 0.54 0. 0.35] | 0.0613629 | 0.503153 | 0.564516 | [0.11 0.89] | 0.46 |
-| (0.35, 98) | 0.1058 | 0.3342 | 0.44 | [0.09 0.56 0. 0.35] | 0.0989152 | 0.45664 | 0.555556 | [0.09 0.91] | 0.44 |
-| (0.35, 99) | 0.117609 | 0.317391 | 0.435 | [0.085 0.565 0. 0.35 ] | 0.0861184 | 0.467241 | 0.55336 | [0.085 0.915] | 0.435 |
-| (0.4, 0) | 0.092345 | 0.401655 | 0.494 | [0.094 0.506 0. 0.4 ] | 0.0832232 | 0.529334 | 0.612557 | [0.094 0.906] | 0.494 |
-| (0.4, 1) | 0.110067 | 0.369933 | 0.48 | [0.081 0.519 0.001 0.399] | 0.0940139 | 0.511449 | 0.605463 | [0.082 0.918] | 0.48 |
-| (0.4, 2) | 0.10932 | 0.38868 | 0.498 | [0.098 0.502 0. 0.4 ] | 0.0823125 | 0.532127 | 0.614439 | [0.098 0.902] | 0.498 |
-| (0.4, 3) | 0.140325 | 0.344675 | 0.485 | [0.085 0.515 0. 0.4 ] | 0.109529 | 0.498836 | 0.608365 | [0.085 0.915] | 0.485 |
-| (0.4, 4) | 0.113004 | 0.369996 | 0.483 | [0.085 0.515 0.002 0.398] | 0.100758 | 0.505487 | 0.606245 | [0.087 0.913] | 0.483 |
-| (0.4, 5) | 0.102619 | 0.402381 | 0.505 | [0.106 0.494 0.001 0.399] | 0.0800786 | 0.537091 | 0.617169 | [0.107 0.893] | 0.505 |
-| (0.4, 6) | 0.121988 | 0.385012 | 0.507 | [0.107 0.493 0. 0.4 ] | 0.0934156 | 0.525301 | 0.618716 | [0.107 0.893] | 0.507 |
-| (0.4, 7) | 0.111719 | 0.373281 | 0.485 | [0.085 0.515 0. 0.4 ] | 0.0860944 | 0.522271 | 0.608365 | [0.085 0.915] | 0.485 |
-| (0.4, 8) | 0.103077 | 0.391923 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0934454 | 0.519581 | 0.613027 | [0.095 0.905] | 0.495 |
-| (0.4, 9) | 0.09463 | 0.39437 | 0.489 | [0.089 0.511 0. 0.4 ] | 0.0841998 | 0.526021 | 0.610221 | [0.089 0.911] | 0.489 |
-| (0.4, 10) | 0.114552 | 0.377448 | 0.492 | [0.092 0.508 0. 0.4 ] | 0.0829579 | 0.528663 | 0.611621 | [0.092 0.908] | 0.492 |
-| (0.4, 11) | 0.0881744 | 0.402826 | 0.491 | [0.091 0.509 0. 0.4 ] | 0.080588 | 0.530566 | 0.611154 | [0.091 0.909] | 0.491 |
-| (0.4, 12) | 0.116386 | 0.369614 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0788718 | 0.529956 | 0.608828 | [0.086 0.914] | 0.486 |
-| (0.4, 13) | 0.082174 | 0.422826 | 0.505 | [0.106 0.494 0.001 0.399] | 0.0696855 | 0.547484 | 0.617169 | [0.107 0.893] | 0.505 |
-| (0.4, 14) | 0.10176 | 0.38824 | 0.49 | [0.09 0.51 0. 0.4 ] | 0.0850318 | 0.525655 | 0.610687 | [0.09 0.91] | 0.49 |
-| (0.4, 15) | 0.0911766 | 0.404823 | 0.496 | [0.097 0.503 0.001 0.399] | 0.0791771 | 0.533726 | 0.612903 | [0.098 0.902] | 0.496 |
-| (0.4, 16) | 0.148433 | 0.335567 | 0.484 | [0.084 0.516 0. 0.4 ] | 0.105864 | 0.502038 | 0.607903 | [0.084 0.916] | 0.484 |
-| (0.4, 17) | 0.0972479 | 0.395752 | 0.493 | [0.093 0.507 0. 0.4 ] | 0.0776354 | 0.534453 | 0.612089 | [0.093 0.907] | 0.493 |
-| (0.4, 18) | 0.0899533 | 0.390047 | 0.48 | [0.08 0.52 0. 0.4 ] | 0.0751172 | 0.530943 | 0.606061 | [0.08 0.92] | 0.48 |
-| (0.4, 19) | 0.0985107 | 0.395489 | 0.494 | [0.094 0.506 0. 0.4 ] | 0.0900225 | 0.522535 | 0.612557 | [0.094 0.906] | 0.494 |
-| (0.4, 20) | 0.133984 | 0.358016 | 0.492 | [0.093 0.507 0.001 0.399] | 0.100027 | 0.510999 | 0.611026 | [0.094 0.906] | 0.492 |
-| (0.4, 21) | 0.107137 | 0.388863 | 0.496 | [0.096 0.504 0. 0.4 ] | 0.0792101 | 0.534287 | 0.613497 | [0.096 0.904] | 0.496 |
-| (0.4, 22) | 0.0939334 | 0.401067 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0811591 | 0.531868 | 0.613027 | [0.095 0.905] | 0.495 |
-| (0.4, 23) | 0.119607 | 0.363393 | 0.483 | [0.085 0.515 0.002 0.398] | 0.0741715 | 0.532074 | 0.606245 | [0.087 0.913] | 0.483 |
-| (0.4, 24) | 0.0886681 | 0.402332 | 0.491 | [0.092 0.508 0.001 0.399] | 0.0779011 | 0.532657 | 0.610559 | [0.093 0.907] | 0.491 |
-| (0.4, 25) | 0.120708 | 0.361292 | 0.482 | [0.083 0.517 0.001 0.399] | 0.0967001 | 0.509683 | 0.606383 | [0.084 0.916] | 0.482 |
-| (0.4, 26) | 0.115847 | 0.372153 | 0.488 | [0.088 0.512 0. 0.4 ] | 0.090602 | 0.519154 | 0.609756 | [0.088 0.912] | 0.488 |
-| (0.4, 27) | 0.0823224 | 0.418678 | 0.501 | [0.101 0.499 0. 0.4 ] | 0.0663761 | 0.549482 | 0.615858 | [0.101 0.899] | 0.501 |
-| (0.4, 28) | 0.126811 | 0.354189 | 0.481 | [0.081 0.519 0. 0.4 ] | 0.0952304 | 0.51129 | 0.60652 | [0.081 0.919] | 0.481 |
-| (0.4, 29) | 0.120102 | 0.370898 | 0.491 | [0.091 0.509 0. 0.4 ] | 0.0952146 | 0.515939 | 0.611154 | [0.091 0.909] | 0.491 |
-| (0.4, 30) | 0.1235 | 0.3405 | 0.464 | [0.064 0.536 0. 0.4 ] | 0.0918379 | 0.506964 | 0.598802 | [0.064 0.936] | 0.464 |
-| (0.4, 31) | 0.116506 | 0.369494 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0997973 | 0.509031 | 0.608828 | [0.086 0.914] | 0.486 |
-| (0.4, 32) | 0.129958 | 0.359042 | 0.489 | [0.089 0.511 0. 0.4 ] | 0.0956325 | 0.514589 | 0.610221 | [0.089 0.911] | 0.489 |
-| (0.4, 33) | 0.101764 | 0.388236 | 0.49 | [0.09 0.51 0. 0.4 ] | 0.0904647 | 0.520222 | 0.610687 | [0.09 0.91] | 0.49 |
-| (0.4, 34) | 0.111378 | 0.382622 | 0.494 | [0.094 0.506 0. 0.4 ] | 0.0774008 | 0.535157 | 0.612557 | [0.094 0.906] | 0.494 |
-| (0.4, 35) | 0.118964 | 0.369036 | 0.488 | [0.089 0.511 0.001 0.399] | 0.0925809 | 0.516579 | 0.60916 | [0.09 0.91] | 0.488 |
-| (0.4, 36) | 0.107617 | 0.379383 | 0.487 | [0.087 0.513 0. 0.4 ] | 0.0748225 | 0.534469 | 0.609292 | [0.087 0.913] | 0.487 |
-| (0.4, 37) | 0.104499 | 0.377501 | 0.482 | [0.083 0.517 0.001 0.399] | 0.0941583 | 0.512225 | 0.606383 | [0.084 0.916] | 0.482 |
-| (0.4, 38) | 0.0908303 | 0.38517 | 0.476 | [0.077 0.523 0.001 0.399] | 0.0805585 | 0.523072 | 0.603631 | [0.078 0.922] | 0.476 |
-| (0.4, 39) | 0.141925 | 0.327075 | 0.469 | [0.069 0.531 0. 0.4 ] | 0.109778 | 0.491274 | 0.601052 | [0.069 0.931] | 0.469 |
-| (0.4, 40) | 0.113013 | 0.380987 | 0.494 | [0.095 0.505 0.001 0.399] | 0.0873407 | 0.524622 | 0.611963 | [0.096 0.904] | 0.494 |
-| (0.4, 41) | 0.103835 | 0.397165 | 0.501 | [0.101 0.499 0. 0.4 ] | 0.0760962 | 0.539762 | 0.615858 | [0.101 0.899] | 0.501 |
-| (0.4, 42) | 0.117133 | 0.378867 | 0.496 | [0.097 0.503 0.001 0.399] | 0.0906409 | 0.522262 | 0.612903 | [0.098 0.902] | 0.496 |
-| (0.4, 43) | 0.0771431 | 0.416857 | 0.494 | [0.096 0.504 0.002 0.398] | 0.065077 | 0.54629 | 0.611367 | [0.098 0.902] | 0.494 |
-| (0.4, 44) | 0.0940821 | 0.384918 | 0.479 | [0.079 0.521 0. 0.4 ] | 0.083618 | 0.521984 | 0.605602 | [0.079 0.921] | 0.479 |
-| (0.4, 45) | 0.100887 | 0.379113 | 0.48 | [0.081 0.519 0.001 0.399] | 0.098478 | 0.506985 | 0.605463 | [0.082 0.918] | 0.48 |
-| (0.4, 46) | 0.0877998 | 0.4042 | 0.492 | [0.093 0.507 0.001 0.399] | 0.0742074 | 0.536819 | 0.611026 | [0.094 0.906] | 0.492 |
-| (0.4, 47) | 0.133793 | 0.343207 | 0.477 | [0.077 0.523 0. 0.4 ] | 0.111633 | 0.493053 | 0.604686 | [0.077 0.923] | 0.477 |
-| (0.4, 48) | 0.104751 | 0.391249 | 0.496 | [0.096 0.504 0. 0.4 ] | 0.0948151 | 0.518682 | 0.613497 | [0.096 0.904] | 0.496 |
-| (0.4, 49) | 0.111086 | 0.372914 | 0.484 | [0.085 0.515 0.001 0.399] | 0.0854655 | 0.52184 | 0.607306 | [0.086 0.914] | 0.484 |
-| (0.4, 50) | 0.115748 | 0.367252 | 0.483 | [0.084 0.516 0.001 0.399] | 0.0794044 | 0.52744 | 0.606844 | [0.085 0.915] | 0.483 |
-| (0.4, 51) | 0.111478 | 0.389522 | 0.501 | [0.101 0.499 0. 0.4 ] | 0.094504 | 0.521354 | 0.615858 | [0.101 0.899] | 0.501 |
-| (0.4, 52) | 0.116461 | 0.378539 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0778475 | 0.535179 | 0.613027 | [0.095 0.905] | 0.495 |
-| (0.4, 53) | 0.129073 | 0.340927 | 0.47 | [0.071 0.529 0.001 0.399] | 0.10103 | 0.499874 | 0.600904 | [0.072 0.928] | 0.47 |
-| (0.4, 54) | 0.070972 | 0.413028 | 0.484 | [0.085 0.515 0.001 0.399] | 0.0619927 | 0.545313 | 0.607306 | [0.086 0.914] | 0.484 |
-| (0.4, 55) | 0.117027 | 0.363973 | 0.481 | [0.081 0.519 0. 0.4 ] | 0.100197 | 0.506323 | 0.60652 | [0.081 0.919] | 0.481 |
-| (0.4, 56) | 0.116247 | 0.360753 | 0.477 | [0.077 0.523 0. 0.4 ] | 0.0981762 | 0.50651 | 0.604686 | [0.077 0.923] | 0.477 |
-| (0.4, 57) | 0.0605851 | 0.419415 | 0.48 | [0.08 0.52 0. 0.4 ] | 0.0531007 | 0.55296 | 0.606061 | [0.08 0.92] | 0.48 |
-| (0.4, 58) | 0.123128 | 0.349872 | 0.473 | [0.073 0.527 0. 0.4 ] | 0.0887936 | 0.51407 | 0.602864 | [0.073 0.927] | 0.473 |
-| (0.4, 59) | 0.118622 | 0.362378 | 0.481 | [0.081 0.519 0. 0.4 ] | 0.0999178 | 0.506602 | 0.60652 | [0.081 0.919] | 0.481 |
-| (0.4, 60) | 0.127352 | 0.347648 | 0.475 | [0.075 0.525 0. 0.4 ] | 0.0978482 | 0.505925 | 0.603774 | [0.075 0.925] | 0.475 |
-| (0.4, 61) | 0.106386 | 0.353614 | 0.46 | [0.061 0.539 0.001 0.399] | 0.0804344 | 0.515978 | 0.596413 | [0.062 0.938] | 0.46 |
-| (0.4, 62) | 0.0924329 | 0.395567 | 0.488 | [0.089 0.511 0.001 0.399] | 0.0820076 | 0.527153 | 0.60916 | [0.09 0.91] | 0.488 |
-| (0.4, 63) | 0.105464 | 0.381536 | 0.487 | [0.087 0.513 0. 0.4 ] | 0.0768776 | 0.532414 | 0.609292 | [0.087 0.913] | 0.487 |
-| (0.4, 64) | 0.103833 | 0.377167 | 0.481 | [0.082 0.518 0.001 0.399] | 0.0846173 | 0.521305 | 0.605923 | [0.083 0.917] | 0.481 |
-| (0.4, 65) | 0.099706 | 0.378294 | 0.478 | [0.079 0.521 0.001 0.399] | 0.0838127 | 0.520733 | 0.604545 | [0.08 0.92] | 0.478 |
-| (0.4, 66) | 0.138331 | 0.336669 | 0.475 | [0.076 0.524 0.001 0.399] | 0.103986 | 0.499188 | 0.603175 | [0.077 0.923] | 0.475 |
-| (0.4, 67) | 0.0768523 | 0.407148 | 0.484 | [0.084 0.516 0. 0.4 ] | 0.0699597 | 0.537943 | 0.607903 | [0.084 0.916] | 0.484 |
-| (0.4, 68) | 0.12711 | 0.35589 | 0.483 | [0.083 0.517 0. 0.4 ] | 0.106317 | 0.501125 | 0.607441 | [0.083 0.917] | 0.483 |
-| (0.4, 69) | 0.0883312 | 0.388669 | 0.477 | [0.077 0.523 0. 0.4 ] | 0.0754731 | 0.529213 | 0.604686 | [0.077 0.923] | 0.477 |
-| (0.4, 70) | 0.0730699 | 0.41593 | 0.489 | [0.089 0.511 0. 0.4 ] | 0.0616618 | 0.548559 | 0.610221 | [0.089 0.911] | 0.489 |
-| (0.4, 71) | 0.124959 | 0.375041 | 0.5 | [0.1 0.5 0. 0.4] | 0.0857221 | 0.529663 | 0.615385 | [0.1 0.9] | 0.5 |
-| (0.4, 72) | 0.113747 | 0.376253 | 0.49 | [0.091 0.509 0.001 0.399] | 0.0965721 | 0.51352 | 0.610092 | [0.092 0.908] | 0.49 |
-| (0.4, 73) | 0.133 | 0.358 | 0.491 | [0.092 0.508 0.001 0.399] | 0.0919066 | 0.518652 | 0.610559 | [0.093 0.907] | 0.491 |
-| (0.4, 74) | 0.105271 | 0.386729 | 0.492 | [0.092 0.508 0. 0.4 ] | 0.0828093 | 0.528812 | 0.611621 | [0.092 0.908] | 0.492 |
-| (0.4, 75) | 0.134828 | 0.358172 | 0.493 | [0.093 0.507 0. 0.4 ] | 0.110178 | 0.50191 | 0.612089 | [0.093 0.907] | 0.493 |
-| (0.4, 76) | 0.12011 | 0.37189 | 0.492 | [0.092 0.508 0. 0.4 ] | 0.091034 | 0.520587 | 0.611621 | [0.092 0.908] | 0.492 |
-| (0.4, 77) | 0.118663 | 0.359337 | 0.478 | [0.078 0.522 0. 0.4 ] | 0.0957442 | 0.5094 | 0.605144 | [0.078 0.922] | 0.478 |
-| (0.4, 78) | 0.0944783 | 0.405522 | 0.5 | [0.1 0.5 0. 0.4] | 0.0700838 | 0.545301 | 0.615385 | [0.1 0.9] | 0.5 |
-| (0.4, 79) | 0.116782 | 0.380218 | 0.497 | [0.097 0.503 0. 0.4 ] | 0.0970365 | 0.516931 | 0.613968 | [0.097 0.903] | 0.497 |
-| (0.4, 80) | 0.107796 | 0.369204 | 0.477 | [0.079 0.521 0.002 0.398] | 0.0821726 | 0.521315 | 0.603487 | [0.081 0.919] | 0.477 |
-| (0.4, 81) | 0.105714 | 0.380286 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0767872 | 0.532041 | 0.608828 | [0.086 0.914] | 0.486 |
-| (0.4, 82) | 0.114563 | 0.391437 | 0.506 | [0.106 0.494 0. 0.4 ] | 0.0992908 | 0.518947 | 0.618238 | [0.106 0.894] | 0.506 |
-| (0.4, 83) | 0.112762 | 0.366238 | 0.479 | [0.079 0.521 0. 0.4 ] | 0.0831437 | 0.522458 | 0.605602 | [0.079 0.921] | 0.479 |
-| (0.4, 84) | 0.118112 | 0.361888 | 0.48 | [0.081 0.519 0.001 0.399] | 0.0910492 | 0.514414 | 0.605463 | [0.082 0.918] | 0.48 |
-| (0.4, 85) | 0.109261 | 0.369739 | 0.479 | [0.079 0.521 0. 0.4 ] | 0.0871998 | 0.518402 | 0.605602 | [0.079 0.921] | 0.479 |
-| (0.4, 86) | 0.0915574 | 0.404443 | 0.496 | [0.096 0.504 0. 0.4 ] | 0.0691098 | 0.544387 | 0.613497 | [0.096 0.904] | 0.496 |
-| (0.4, 87) | 0.102728 | 0.399272 | 0.502 | [0.102 0.498 0. 0.4 ] | 0.0756223 | 0.540711 | 0.616333 | [0.102 0.898] | 0.502 |
-| (0.4, 88) | 0.073757 | 0.414243 | 0.488 | [0.088 0.512 0. 0.4 ] | 0.0647122 | 0.545044 | 0.609756 | [0.088 0.912] | 0.488 |
-| (0.4, 89) | 0.0796764 | 0.404324 | 0.484 | [0.084 0.516 0. 0.4 ] | 0.0650499 | 0.542853 | 0.607903 | [0.084 0.916] | 0.484 |
-| (0.4, 90) | 0.109032 | 0.383968 | 0.493 | [0.093 0.507 0. 0.4 ] | 0.0869838 | 0.525105 | 0.612089 | [0.093 0.907] | 0.493 |
-| (0.4, 91) | 0.0873812 | 0.403619 | 0.491 | [0.093 0.507 0.002 0.398] | 0.0752138 | 0.534748 | 0.609962 | [0.095 0.905] | 0.491 |
-| (0.4, 92) | 0.133381 | 0.342619 | 0.476 | [0.077 0.523 0.001 0.399] | 0.116146 | 0.487485 | 0.603631 | [0.078 0.922] | 0.476 |
-| (0.4, 93) | 0.0782402 | 0.39776 | 0.476 | [0.077 0.523 0.001 0.399] | 0.0717926 | 0.531838 | 0.603631 | [0.078 0.922] | 0.476 |
-| (0.4, 94) | 0.0698796 | 0.43712 | 0.507 | [0.107 0.493 0. 0.4 ] | 0.056667 | 0.562049 | 0.618716 | [0.107 0.893] | 0.507 |
-| (0.4, 95) | 0.0862284 | 0.399772 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0655856 | 0.543242 | 0.608828 | [0.086 0.914] | 0.486 |
-| (0.4, 96) | 0.082924 | 0.402076 | 0.485 | [0.086 0.514 0.001 0.399] | 0.0622894 | 0.545479 | 0.607768 | [0.087 0.913] | 0.485 |
-| (0.4, 97) | 0.106119 | 0.388881 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0793528 | 0.533674 | 0.613027 | [0.095 0.905] | 0.495 |
-| (0.4, 98) | 0.0803093 | 0.415691 | 0.496 | [0.097 0.503 0.001 0.399] | 0.0649711 | 0.547932 | 0.612903 | [0.098 0.902] | 0.496 |
-| (0.4, 99) | 0.130854 | 0.357146 | 0.488 | [0.088 0.512 0. 0.4 ] | 0.0929463 | 0.51681 | 0.609756 | [0.088 0.912] | 0.488 |
-| (0.45, 0) | 0.144135 | 0.390865 | 0.535 | [0.085 0.465 0. 0.45 ] | 0.0978465 | 0.561494 | 0.659341 | [0.085 0.915] | 0.535 |
-| (0.45, 1) | 0.0803529 | 0.446647 | 0.527 | [0.078 0.472 0.001 0.449] | 0.0665225 | 0.588474 | 0.654996 | [0.079 0.921] | 0.527 |
-| (0.45, 2) | 0.102685 | 0.434315 | 0.537 | [0.087 0.463 0. 0.45 ] | 0.0754333 | 0.584875 | 0.660308 | [0.087 0.913] | 0.537 |
-| (0.45, 3) | 0.0687572 | 0.470243 | 0.539 | [0.089 0.461 0. 0.45 ] | 0.0624005 | 0.598878 | 0.661278 | [0.089 0.911] | 0.539 |
-| (0.45, 4) | 0.125853 | 0.388147 | 0.514 | [0.064 0.486 0. 0.45 ] | 0.0917095 | 0.557641 | 0.649351 | [0.064 0.936] | 0.514 |
-| (0.45, 5) | 0.0746958 | 0.451304 | 0.526 | [0.076 0.474 0. 0.45 ] | 0.0637687 | 0.591253 | 0.655022 | [0.076 0.924] | 0.526 |
-| (0.45, 6) | 0.110722 | 0.424278 | 0.535 | [0.085 0.465 0. 0.45 ] | 0.0802848 | 0.579056 | 0.659341 | [0.085 0.915] | 0.535 |
-| (0.45, 7) | 0.0962457 | 0.436754 | 0.533 | [0.084 0.466 0.001 0.449] | 0.0746481 | 0.583227 | 0.657875 | [0.085 0.915] | 0.533 |
-| (0.45, 8) | 0.0899108 | 0.463089 | 0.553 | [0.103 0.447 0. 0.45 ] | 0.0678808 | 0.600271 | 0.668151 | [0.103 0.897] | 0.553 |
-| (0.45, 9) | 0.0804035 | 0.443597 | 0.524 | [0.074 0.476 0. 0.45 ] | 0.0667882 | 0.587282 | 0.65407 | [0.074 0.926] | 0.524 |
-| (0.45, 10) | 0.0723278 | 0.458672 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.056579 | 0.600835 | 0.657414 | [0.081 0.919] | 0.531 |
-| (0.45, 11) | 0.130674 | 0.398326 | 0.529 | [0.079 0.471 0. 0.45 ] | 0.0896737 | 0.566781 | 0.656455 | [0.079 0.921] | 0.529 |
-| (0.45, 12) | 0.0678408 | 0.468159 | 0.536 | [0.088 0.462 0.002 0.448] | 0.0504177 | 0.608406 | 0.658824 | [0.09 0.91] | 0.536 |
-| (0.45, 13) | 0.102707 | 0.424293 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0840882 | 0.571411 | 0.655499 | [0.077 0.923] | 0.527 |
-| (0.45, 14) | 0.123353 | 0.414647 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0904657 | 0.570327 | 0.660793 | [0.088 0.912] | 0.538 |
-| (0.45, 15) | 0.117961 | 0.416039 | 0.534 | [0.084 0.466 0. 0.45 ] | 0.0893819 | 0.569476 | 0.658858 | [0.084 0.916] | 0.534 |
-| (0.45, 16) | 0.0889066 | 0.440093 | 0.529 | [0.079 0.471 0. 0.45 ] | 0.06649 | 0.589965 | 0.656455 | [0.079 0.921] | 0.529 |
-| (0.45, 17) | 0.093381 | 0.428619 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0608659 | 0.592255 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 18) | 0.0845936 | 0.448406 | 0.533 | [0.083 0.467 0. 0.45 ] | 0.0663776 | 0.591998 | 0.658376 | [0.083 0.917] | 0.533 |
-| (0.45, 19) | 0.0937979 | 0.442202 | 0.536 | [0.086 0.464 0. 0.45 ] | 0.0702677 | 0.589556 | 0.659824 | [0.086 0.914] | 0.536 |
-| (0.45, 20) | 0.0977833 | 0.443217 | 0.541 | [0.091 0.459 0. 0.45 ] | 0.0747889 | 0.587463 | 0.662252 | [0.091 0.909] | 0.541 |
-| (0.45, 21) | 0.109247 | 0.412753 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0880567 | 0.565064 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 22) | 0.0977246 | 0.433275 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0722733 | 0.585141 | 0.657414 | [0.081 0.919] | 0.531 |
-| (0.45, 23) | 0.0845927 | 0.444407 | 0.529 | [0.08 0.47 0.001 0.449] | 0.063226 | 0.592727 | 0.655953 | [0.081 0.919] | 0.529 |
-| (0.45, 24) | 0.0863168 | 0.444683 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0612519 | 0.596162 | 0.657414 | [0.081 0.919] | 0.531 |
-| (0.45, 25) | 0.0951726 | 0.430827 | 0.526 | [0.076 0.474 0. 0.45 ] | 0.0676557 | 0.587366 | 0.655022 | [0.076 0.924] | 0.526 |
-| (0.45, 26) | 0.11682 | 0.41518 | 0.532 | [0.083 0.467 0.001 0.449] | 0.0886786 | 0.568715 | 0.657394 | [0.084 0.916] | 0.532 |
-| (0.45, 27) | 0.0810696 | 0.46393 | 0.545 | [0.095 0.455 0. 0.45 ] | 0.0680873 | 0.596119 | 0.664207 | [0.095 0.905] | 0.545 |
-| (0.45, 28) | 0.0983129 | 0.434687 | 0.533 | [0.084 0.466 0.001 0.449] | 0.0680319 | 0.589844 | 0.657875 | [0.085 0.915] | 0.533 |
-| (0.45, 29) | 0.113898 | 0.434102 | 0.548 | [0.098 0.452 0. 0.45 ] | 0.099043 | 0.566637 | 0.66568 | [0.098 0.902] | 0.548 |
-| (0.45, 30) | 0.107967 | 0.436033 | 0.544 | [0.094 0.456 0. 0.45 ] | 0.0797048 | 0.584012 | 0.663717 | [0.094 0.906] | 0.544 |
-| (0.45, 31) | 0.0910724 | 0.435928 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0792247 | 0.576274 | 0.655499 | [0.077 0.923] | 0.527 |
-| (0.45, 32) | 0.0998013 | 0.437199 | 0.537 | [0.088 0.462 0.001 0.449] | 0.0709575 | 0.588851 | 0.659809 | [0.089 0.911] | 0.537 |
-| (0.45, 33) | 0.128649 | 0.395351 | 0.524 | [0.075 0.475 0.001 0.449] | 0.0880365 | 0.56553 | 0.653566 | [0.076 0.924] | 0.524 |
-| (0.45, 34) | 0.11969 | 0.42331 | 0.543 | [0.093 0.457 0. 0.45 ] | 0.0735173 | 0.58971 | 0.663228 | [0.093 0.907] | 0.543 |
-| (0.45, 35) | 0.10032 | 0.43168 | 0.532 | [0.084 0.466 0.002 0.448] | 0.0863961 | 0.570495 | 0.656891 | [0.086 0.914] | 0.532 |
-| (0.45, 36) | 0.0874866 | 0.436513 | 0.524 | [0.074 0.476 0. 0.45 ] | 0.0645323 | 0.589537 | 0.65407 | [0.074 0.926] | 0.524 |
-| (0.45, 37) | 0.0794778 | 0.447522 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0575178 | 0.597981 | 0.655499 | [0.077 0.923] | 0.527 |
-| (0.45, 38) | 0.0371157 | 0.498884 | 0.536 | [0.086 0.464 0. 0.45 ] | 0.0320388 | 0.627785 | 0.659824 | [0.086 0.914] | 0.536 |
-| (0.45, 39) | 0.0757443 | 0.446256 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0608502 | 0.59227 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 40) | 0.125924 | 0.399076 | 0.525 | [0.077 0.473 0.002 0.448] | 0.0963192 | 0.557218 | 0.653538 | [0.079 0.921] | 0.525 |
-| (0.45, 41) | 0.0878115 | 0.450189 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0617661 | 0.599027 | 0.660793 | [0.088 0.912] | 0.538 |
-| (0.45, 42) | 0.0975696 | 0.44243 | 0.54 | [0.091 0.459 0.001 0.449] | 0.0706756 | 0.590591 | 0.661267 | [0.092 0.908] | 0.54 |
-| (0.45, 43) | 0.0907168 | 0.447283 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0714498 | 0.589343 | 0.660793 | [0.088 0.912] | 0.538 |
-| (0.45, 44) | 0.069606 | 0.452394 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0567298 | 0.596391 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 45) | 0.0775188 | 0.460481 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0631226 | 0.59767 | 0.660793 | [0.088 0.912] | 0.538 |
-| (0.45, 46) | 0.107153 | 0.428847 | 0.536 | [0.087 0.463 0.001 0.449] | 0.0851788 | 0.574146 | 0.659325 | [0.088 0.912] | 0.536 |
-| (0.45, 47) | 0.110526 | 0.409474 | 0.52 | [0.07 0.48 0. 0.45] | 0.0791248 | 0.573049 | 0.652174 | [0.07 0.93] | 0.52 |
-| (0.45, 48) | 0.105262 | 0.422738 | 0.528 | [0.078 0.472 0. 0.45 ] | 0.0851603 | 0.570816 | 0.655977 | [0.078 0.922] | 0.528 |
-| (0.45, 49) | 0.0977202 | 0.44528 | 0.543 | [0.093 0.457 0. 0.45 ] | 0.0667705 | 0.596457 | 0.663228 | [0.093 0.907] | 0.543 |
-| (0.45, 50) | 0.110384 | 0.406616 | 0.517 | [0.067 0.483 0. 0.45 ] | 0.0739936 | 0.576766 | 0.650759 | [0.067 0.933] | 0.517 |
-| (0.45, 51) | 0.10361 | 0.42639 | 0.53 | [0.08 0.47 0. 0.45] | 0.0716481 | 0.585286 | 0.656934 | [0.08 0.92] | 0.53 |
-| (0.45, 52) | 0.0978246 | 0.433175 | 0.531 | [0.082 0.468 0.001 0.449] | 0.0701777 | 0.586735 | 0.656913 | [0.083 0.917] | 0.531 |
-| (0.45, 53) | 0.0900391 | 0.431961 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0735003 | 0.57962 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 54) | 0.0896197 | 0.44938 | 0.539 | [0.09 0.46 0.001 0.449] | 0.0574227 | 0.603357 | 0.66078 | [0.091 0.909] | 0.539 |
-| (0.45, 55) | 0.0844244 | 0.429576 | 0.514 | [0.064 0.486 0. 0.45 ] | 0.0684914 | 0.580859 | 0.649351 | [0.064 0.936] | 0.514 |
-| (0.45, 56) | 0.0762635 | 0.447736 | 0.524 | [0.074 0.476 0. 0.45 ] | 0.0546346 | 0.599435 | 0.65407 | [0.074 0.926] | 0.524 |
-| (0.45, 57) | 0.0873352 | 0.442665 | 0.53 | [0.08 0.47 0. 0.45] | 0.0714978 | 0.585436 | 0.656934 | [0.08 0.92] | 0.53 |
-| (0.45, 58) | 0.0981975 | 0.432803 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0694249 | 0.587989 | 0.657414 | [0.081 0.919] | 0.531 |
-| (0.45, 59) | 0.0862462 | 0.438754 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0721937 | 0.582352 | 0.654545 | [0.075 0.925] | 0.525 |
-| (0.45, 60) | 0.0910102 | 0.42499 | 0.516 | [0.066 0.484 0. 0.45 ] | 0.0711453 | 0.579144 | 0.650289 | [0.066 0.934] | 0.516 |
-| (0.45, 61) | 0.108033 | 0.420967 | 0.529 | [0.079 0.471 0. 0.45 ] | 0.0712548 | 0.5852 | 0.656455 | [0.079 0.921] | 0.529 |
-| (0.45, 62) | 0.0915517 | 0.437448 | 0.529 | [0.08 0.47 0.001 0.449] | 0.0657728 | 0.59018 | 0.655953 | [0.081 0.919] | 0.529 |
-| (0.45, 63) | 0.10221 | 0.42779 | 0.53 | [0.08 0.47 0. 0.45] | 0.071132 | 0.585802 | 0.656934 | [0.08 0.92] | 0.53 |
-| (0.45, 64) | 0.0737738 | 0.451226 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0595941 | 0.594951 | 0.654545 | [0.075 0.925] | 0.525 |
-| (0.45, 65) | 0.108378 | 0.413622 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0710203 | 0.5821 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 66) | 0.0985459 | 0.432454 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0684595 | 0.588955 | 0.657414 | [0.081 0.919] | 0.531 |
-| (0.45, 67) | 0.0782579 | 0.460742 | 0.539 | [0.09 0.46 0.001 0.449] | 0.0622707 | 0.598509 | 0.66078 | [0.091 0.909] | 0.539 |
-| (0.45, 68) | 0.0895337 | 0.436466 | 0.526 | [0.077 0.473 0.001 0.449] | 0.0572073 | 0.597312 | 0.654519 | [0.078 0.922] | 0.526 |
-| (0.45, 69) | 0.116034 | 0.410966 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0800237 | 0.575475 | 0.655499 | [0.077 0.923] | 0.527 |
-| (0.45, 70) | 0.0733139 | 0.451686 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0563668 | 0.598179 | 0.654545 | [0.075 0.925] | 0.525 |
-| (0.45, 71) | 0.0764108 | 0.454589 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0568153 | 0.600599 | 0.657414 | [0.081 0.919] | 0.531 |
-| (0.45, 72) | 0.101457 | 0.421543 | 0.523 | [0.074 0.476 0.001 0.449] | 0.0660446 | 0.587046 | 0.653091 | [0.075 0.925] | 0.523 |
-| (0.45, 73) | 0.074457 | 0.445543 | 0.52 | [0.07 0.48 0. 0.45] | 0.0427993 | 0.609375 | 0.652174 | [0.07 0.93] | 0.52 |
-| (0.45, 74) | 0.114778 | 0.416222 | 0.531 | [0.082 0.468 0.001 0.449] | 0.0877855 | 0.569127 | 0.656913 | [0.083 0.917] | 0.531 |
-| (0.45, 75) | 0.0871245 | 0.453876 | 0.541 | [0.091 0.459 0. 0.45 ] | 0.0578167 | 0.604435 | 0.662252 | [0.091 0.909] | 0.541 |
-| (0.45, 76) | 0.0804687 | 0.448531 | 0.529 | [0.08 0.47 0.001 0.449] | 0.0565621 | 0.599391 | 0.655953 | [0.081 0.919] | 0.529 |
-| (0.45, 77) | 0.0759259 | 0.472074 | 0.548 | [0.098 0.452 0. 0.45 ] | 0.0714512 | 0.594229 | 0.66568 | [0.098 0.902] | 0.548 |
-| (0.45, 78) | 0.0901168 | 0.436883 | 0.527 | [0.078 0.472 0.001 0.449] | 0.0652689 | 0.589727 | 0.654996 | [0.079 0.921] | 0.527 |
-| (0.45, 79) | 0.117665 | 0.398335 | 0.516 | [0.066 0.484 0. 0.45 ] | 0.0850179 | 0.565271 | 0.650289 | [0.066 0.934] | 0.516 |
-| (0.45, 80) | 0.0838263 | 0.450174 | 0.534 | [0.086 0.464 0.002 0.448] | 0.0586789 | 0.599177 | 0.657856 | [0.088 0.912] | 0.534 |
-| (0.45, 81) | 0.117966 | 0.407034 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0916233 | 0.562922 | 0.654545 | [0.075 0.925] | 0.525 |
-| (0.45, 82) | 0.0783591 | 0.465641 | 0.544 | [0.094 0.456 0. 0.45 ] | 0.0563563 | 0.607361 | 0.663717 | [0.094 0.906] | 0.544 |
-| (0.45, 83) | 0.107869 | 0.426131 | 0.534 | [0.084 0.466 0. 0.45 ] | 0.079874 | 0.578984 | 0.658858 | [0.084 0.916] | 0.534 |
-| (0.45, 84) | 0.0742541 | 0.457746 | 0.532 | [0.083 0.467 0.001 0.449] | 0.0582135 | 0.59918 | 0.657394 | [0.084 0.916] | 0.532 |
-| (0.45, 85) | 0.0889582 | 0.436042 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0641647 | 0.590381 | 0.654545 | [0.075 0.925] | 0.525 |
-| (0.45, 86) | 0.105018 | 0.429982 | 0.535 | [0.086 0.464 0.001 0.449] | 0.075934 | 0.582907 | 0.658841 | [0.087 0.913] | 0.535 |
-| (0.45, 87) | 0.0880208 | 0.437979 | 0.526 | [0.077 0.473 0.001 0.449] | 0.0573692 | 0.59715 | 0.654519 | [0.078 0.922] | 0.526 |
-| (0.45, 88) | 0.0817681 | 0.456232 | 0.538 | [0.09 0.46 0.002 0.448] | 0.056134 | 0.60366 | 0.659794 | [0.092 0.908] | 0.538 |
-| (0.45, 89) | 0.113433 | 0.420567 | 0.534 | [0.085 0.465 0.001 0.449] | 0.085868 | 0.57249 | 0.658358 | [0.086 0.914] | 0.534 |
-| (0.45, 90) | 0.0828514 | 0.446149 | 0.529 | [0.081 0.469 0.002 0.448] | 0.0623557 | 0.593094 | 0.65545 | [0.083 0.917] | 0.529 |
-| (0.45, 91) | 0.0816244 | 0.451376 | 0.533 | [0.083 0.467 0. 0.45 ] | 0.0671052 | 0.591271 | 0.658376 | [0.083 0.917] | 0.533 |
-| (0.45, 92) | 0.0661671 | 0.459833 | 0.526 | [0.076 0.474 0. 0.45 ] | 0.0487002 | 0.606322 | 0.655022 | [0.076 0.924] | 0.526 |
-| (0.45, 93) | 0.111753 | 0.412247 | 0.524 | [0.075 0.475 0.001 0.449] | 0.0867837 | 0.566783 | 0.653566 | [0.076 0.924] | 0.524 |
-| (0.45, 94) | 0.120017 | 0.414983 | 0.535 | [0.085 0.465 0. 0.45 ] | 0.0876596 | 0.571681 | 0.659341 | [0.085 0.915] | 0.535 |
-| (0.45, 95) | 0.121518 | 0.412482 | 0.534 | [0.084 0.466 0. 0.45 ] | 0.0959745 | 0.562883 | 0.658858 | [0.084 0.916] | 0.534 |
-| (0.45, 96) | 0.0951344 | 0.426866 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0639835 | 0.589137 | 0.65312 | [0.072 0.928] | 0.522 |
-| (0.45, 97) | 0.0712756 | 0.461724 | 0.533 | [0.083 0.467 0. 0.45 ] | 0.0543197 | 0.604056 | 0.658376 | [0.083 0.917] | 0.533 |
-| (0.45, 98) | 0.0954362 | 0.448564 | 0.544 | [0.094 0.456 0. 0.45 ] | 0.0673074 | 0.596409 | 0.663717 | [0.094 0.906] | 0.544 |
-| (0.45, 99) | 0.103458 | 0.428542 | 0.532 | [0.082 0.468 0. 0.45 ] | 0.0707815 | 0.587113 | 0.657895 | [0.082 0.918] | 0.532 |
-| (0.5, 0) | 0.0823199 | 0.48668 | 0.569 | [0.071 0.429 0.002 0.498] | 0.0658081 | 0.63216 | 0.697968 | [0.073 0.927] | 0.569 |
-| (0.5, 1) | 0.0714074 | 0.492593 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0533071 | 0.643072 | 0.696379 | [0.064 0.936] | 0.564 |
-| (0.5, 2) | 0.0913782 | 0.477622 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0608316 | 0.63798 | 0.698812 | [0.069 0.931] | 0.569 |
-| (0.5, 3) | 0.0980838 | 0.467916 | 0.566 | [0.066 0.434 0. 0.5 ] | 0.0728228 | 0.624527 | 0.69735 | [0.066 0.934] | 0.566 |
-| (0.5, 4) | 0.0713764 | 0.485624 | 0.557 | [0.06 0.44 0.003 0.497] | 0.0545128 | 0.637206 | 0.691719 | [0.063 0.937] | 0.557 |
-| (0.5, 5) | 0.109045 | 0.462955 | 0.572 | [0.073 0.427 0.001 0.499] | 0.069359 | 0.630501 | 0.69986 | [0.074 0.926] | 0.572 |
-| (0.5, 6) | 0.0859611 | 0.500039 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0553646 | 0.651849 | 0.707214 | [0.086 0.914] | 0.586 |
-| (0.5, 7) | 0.0853441 | 0.483656 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0633528 | 0.635459 | 0.698812 | [0.069 0.931] | 0.569 |
-| (0.5, 8) | 0.132703 | 0.442297 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.0890792 | 0.612675 | 0.701754 | [0.075 0.925] | 0.575 |
-| (0.5, 9) | 0.0901357 | 0.484864 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.061493 | 0.640261 | 0.701754 | [0.075 0.925] | 0.575 |
-| (0.5, 10) | 0.0896721 | 0.492328 | 0.582 | [0.083 0.417 0.001 0.499] | 0.05777 | 0.647032 | 0.704802 | [0.084 0.916] | 0.582 |
-| (0.5, 11) | 0.104675 | 0.472325 | 0.577 | [0.078 0.422 0.001 0.499] | 0.0722944 | 0.630028 | 0.702322 | [0.079 0.921] | 0.577 |
-| (0.5, 12) | 0.106432 | 0.467568 | 0.574 | [0.074 0.426 0. 0.5 ] | 0.0760253 | 0.625237 | 0.701262 | [0.074 0.926] | 0.574 |
-| (0.5, 13) | 0.0447724 | 0.536228 | 0.581 | [0.082 0.418 0.001 0.499] | 0.0338064 | 0.670499 | 0.704305 | [0.083 0.917] | 0.581 |
-| (0.5, 14) | 0.08127 | 0.49473 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0546865 | 0.647561 | 0.702247 | [0.076 0.924] | 0.576 |
-| (0.5, 15) | 0.0927274 | 0.466273 | 0.559 | [0.059 0.441 0. 0.5 ] | 0.0689874 | 0.624975 | 0.693963 | [0.059 0.941] | 0.559 |
-| (0.5, 16) | 0.0895199 | 0.49148 | 0.581 | [0.082 0.418 0.001 0.499] | 0.0676034 | 0.636701 | 0.704305 | [0.083 0.917] | 0.581 |
-| (0.5, 17) | 0.101514 | 0.471486 | 0.573 | [0.073 0.427 0. 0.5 ] | 0.0786432 | 0.622128 | 0.700771 | [0.073 0.927] | 0.573 |
-| (0.5, 18) | 0.0802439 | 0.488756 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0639173 | 0.634895 | 0.698812 | [0.069 0.931] | 0.569 |
-| (0.5, 19) | 0.094629 | 0.466371 | 0.561 | [0.061 0.439 0. 0.5 ] | 0.0745545 | 0.620373 | 0.694927 | [0.061 0.939] | 0.561 |
-| (0.5, 20) | 0.0639745 | 0.506026 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.0458685 | 0.653432 | 0.699301 | [0.07 0.93] | 0.57 |
-| (0.5, 21) | 0.0647483 | 0.507252 | 0.572 | [0.073 0.427 0.001 0.499] | 0.0419894 | 0.65787 | 0.69986 | [0.074 0.926] | 0.572 |
-| (0.5, 22) | 0.0906012 | 0.469399 | 0.56 | [0.06 0.44 0. 0.5 ] | 0.0719325 | 0.622512 | 0.694444 | [0.06 0.94] | 0.56 |
-| (0.5, 23) | 0.0792254 | 0.484775 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0515546 | 0.644824 | 0.696379 | [0.064 0.936] | 0.564 |
-| (0.5, 24) | 0.089042 | 0.475958 | 0.565 | [0.065 0.435 0. 0.5 ] | 0.0625937 | 0.63427 | 0.696864 | [0.065 0.935] | 0.565 |
-| (0.5, 25) | 0.0693021 | 0.508698 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0390147 | 0.66422 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 26) | 0.0826301 | 0.47537 | 0.558 | [0.058 0.442 0. 0.5 ] | 0.0662074 | 0.627274 | 0.693481 | [0.058 0.942] | 0.558 |
-| (0.5, 27) | 0.0865851 | 0.486415 | 0.573 | [0.074 0.426 0.001 0.499] | 0.0592513 | 0.6411 | 0.700351 | [0.075 0.925] | 0.573 |
-| (0.5, 28) | 0.098346 | 0.477654 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0675682 | 0.634679 | 0.702247 | [0.076 0.924] | 0.576 |
-| (0.5, 29) | 0.106672 | 0.465328 | 0.572 | [0.072 0.428 0. 0.5 ] | 0.0687628 | 0.631517 | 0.70028 | [0.072 0.928] | 0.572 |
-| (0.5, 30) | 0.0814945 | 0.491505 | 0.573 | [0.074 0.426 0.001 0.499] | 0.0639574 | 0.636394 | 0.700351 | [0.075 0.925] | 0.573 |
-| (0.5, 31) | 0.089467 | 0.491533 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0609881 | 0.643734 | 0.704722 | [0.081 0.919] | 0.581 |
-| (0.5, 32) | 0.118053 | 0.457947 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0806901 | 0.621557 | 0.702247 | [0.076 0.924] | 0.576 |
-| (0.5, 33) | 0.0825452 | 0.499455 | 0.582 | [0.082 0.418 0. 0.5 ] | 0.0582277 | 0.646991 | 0.705219 | [0.082 0.918] | 0.582 |
-| (0.5, 34) | 0.0417537 | 0.522246 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0305612 | 0.665818 | 0.696379 | [0.064 0.936] | 0.564 |
-| (0.5, 35) | 0.0785123 | 0.502488 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0475305 | 0.657191 | 0.704722 | [0.081 0.919] | 0.581 |
-| (0.5, 36) | 0.0744245 | 0.511576 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0489571 | 0.658257 | 0.707214 | [0.086 0.914] | 0.586 |
-| (0.5, 37) | 0.0843737 | 0.491626 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0653751 | 0.636872 | 0.702247 | [0.076 0.924] | 0.576 |
-| (0.5, 38) | 0.09586 | 0.47114 | 0.567 | [0.069 0.431 0.002 0.498] | 0.0624039 | 0.634587 | 0.696991 | [0.071 0.929] | 0.567 |
-| (0.5, 39) | 0.0986446 | 0.471355 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.0662648 | 0.633036 | 0.699301 | [0.07 0.93] | 0.57 |
-| (0.5, 40) | 0.108438 | 0.460562 | 0.569 | [0.07 0.43 0.001 0.499] | 0.0689099 | 0.629481 | 0.69839 | [0.071 0.929] | 0.569 |
-| (0.5, 41) | 0.0767079 | 0.524292 | 0.601 | [0.101 0.399 0. 0.5 ] | 0.0610743 | 0.653722 | 0.714796 | [0.101 0.899] | 0.601 |
-| (0.5, 42) | 0.0732868 | 0.501713 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.0550139 | 0.64674 | 0.701754 | [0.075 0.925] | 0.575 |
-| (0.5, 43) | 0.0867752 | 0.495225 | 0.582 | [0.082 0.418 0. 0.5 ] | 0.0691998 | 0.636019 | 0.705219 | [0.082 0.918] | 0.582 |
-| (0.5, 44) | 0.0828599 | 0.50414 | 0.587 | [0.089 0.411 0.002 0.498] | 0.0641183 | 0.642766 | 0.706884 | [0.091 0.909] | 0.587 |
-| (0.5, 45) | 0.0958384 | 0.493162 | 0.589 | [0.089 0.411 0. 0.5 ] | 0.067415 | 0.641302 | 0.708717 | [0.089 0.911] | 0.589 |
-| (0.5, 46) | 0.094656 | 0.483344 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0723339 | 0.630901 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 47) | 0.0912958 | 0.476704 | 0.568 | [0.068 0.432 0. 0.5 ] | 0.0622567 | 0.636067 | 0.698324 | [0.068 0.932] | 0.568 |
-| (0.5, 48) | 0.0869253 | 0.491075 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0550731 | 0.648162 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 49) | 0.0468182 | 0.517182 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0355723 | 0.660806 | 0.696379 | [0.064 0.936] | 0.564 |
-| (0.5, 50) | 0.0751574 | 0.489843 | 0.565 | [0.066 0.434 0.001 0.499] | 0.0543628 | 0.642078 | 0.696441 | [0.067 0.933] | 0.565 |
-| (0.5, 51) | 0.0801626 | 0.511837 | 0.592 | [0.092 0.408 0. 0.5 ] | 0.0670399 | 0.643187 | 0.710227 | [0.092 0.908] | 0.592 |
-| (0.5, 52) | 0.0800749 | 0.499925 | 0.58 | [0.08 0.42 0. 0.5 ] | 0.0537815 | 0.650444 | 0.704225 | [0.08 0.92] | 0.58 |
-| (0.5, 53) | 0.0895674 | 0.487433 | 0.577 | [0.077 0.423 0. 0.5 ] | 0.0634805 | 0.63926 | 0.702741 | [0.077 0.923] | 0.577 |
-| (0.5, 54) | 0.083454 | 0.484546 | 0.568 | [0.068 0.432 0. 0.5 ] | 0.061941 | 0.636383 | 0.698324 | [0.068 0.932] | 0.568 |
-| (0.5, 55) | 0.0657226 | 0.511277 | 0.577 | [0.078 0.422 0.001 0.499] | 0.053739 | 0.648583 | 0.702322 | [0.079 0.921] | 0.577 |
-| (0.5, 56) | 0.0652427 | 0.517757 | 0.583 | [0.083 0.417 0. 0.5 ] | 0.0528151 | 0.652901 | 0.705716 | [0.083 0.917] | 0.583 |
-| (0.5, 57) | 0.08749 | 0.49551 | 0.583 | [0.084 0.416 0.001 0.499] | 0.0566554 | 0.648645 | 0.7053 | [0.085 0.915] | 0.583 |
-| (0.5, 58) | 0.0876101 | 0.47539 | 0.563 | [0.063 0.437 0. 0.5 ] | 0.0661026 | 0.629792 | 0.695894 | [0.063 0.937] | 0.563 |
-| (0.5, 59) | 0.081788 | 0.504212 | 0.586 | [0.087 0.413 0.001 0.499] | 0.063427 | 0.643372 | 0.706799 | [0.088 0.912] | 0.586 |
-| (0.5, 60) | 0.08172 | 0.48428 | 0.566 | [0.066 0.434 0. 0.5 ] | 0.0662614 | 0.631089 | 0.69735 | [0.066 0.934] | 0.566 |
-| (0.5, 61) | 0.108461 | 0.451539 | 0.56 | [0.061 0.439 0.001 0.499] | 0.0744602 | 0.619559 | 0.694019 | [0.062 0.938] | 0.56 |
-| (0.5, 62) | 0.0928987 | 0.476101 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0653223 | 0.63349 | 0.698812 | [0.069 0.931] | 0.569 |
-| (0.5, 63) | 0.0916214 | 0.487379 | 0.579 | [0.079 0.421 0. 0.5 ] | 0.0658141 | 0.637916 | 0.70373 | [0.079 0.921] | 0.579 |
-| (0.5, 64) | 0.0774471 | 0.500553 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0503743 | 0.652861 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 65) | 0.0649944 | 0.505006 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.0464662 | 0.652835 | 0.699301 | [0.07 0.93] | 0.57 |
-| (0.5, 66) | 0.112129 | 0.459871 | 0.572 | [0.072 0.428 0. 0.5 ] | 0.0782461 | 0.622034 | 0.70028 | [0.072 0.928] | 0.572 |
-| (0.5, 67) | 0.0465229 | 0.539477 | 0.586 | [0.087 0.413 0.001 0.499] | 0.0326439 | 0.674155 | 0.706799 | [0.088 0.912] | 0.586 |
-| (0.5, 68) | 0.0947336 | 0.477266 | 0.572 | [0.072 0.428 0. 0.5 ] | 0.0738824 | 0.626398 | 0.70028 | [0.072 0.928] | 0.572 |
-| (0.5, 69) | 0.0904762 | 0.471524 | 0.562 | [0.062 0.438 0. 0.5 ] | 0.0632376 | 0.632173 | 0.69541 | [0.062 0.938] | 0.562 |
-| (0.5, 70) | 0.0690796 | 0.51192 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0519332 | 0.652788 | 0.704722 | [0.081 0.919] | 0.581 |
-| (0.5, 71) | 0.0983992 | 0.465601 | 0.564 | [0.065 0.435 0.001 0.499] | 0.0771774 | 0.618778 | 0.695955 | [0.066 0.934] | 0.564 |
-| (0.5, 72) | 0.0972073 | 0.477793 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.0747774 | 0.626977 | 0.701754 | [0.075 0.925] | 0.575 |
-| (0.5, 73) | 0.0639479 | 0.518052 | 0.582 | [0.083 0.417 0.001 0.499] | 0.0473908 | 0.657411 | 0.704802 | [0.084 0.916] | 0.582 |
-| (0.5, 74) | 0.0487624 | 0.529238 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0355232 | 0.667712 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 75) | 0.0990139 | 0.468986 | 0.568 | [0.069 0.431 0.001 0.499] | 0.0652727 | 0.632629 | 0.697902 | [0.07 0.93] | 0.568 |
-| (0.5, 76) | 0.0674569 | 0.510543 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0482796 | 0.654955 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 77) | 0.104605 | 0.473395 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0767052 | 0.62653 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 78) | 0.101666 | 0.483334 | 0.585 | [0.085 0.415 0. 0.5 ] | 0.0646452 | 0.642069 | 0.706714 | [0.085 0.915] | 0.585 |
-| (0.5, 79) | 0.0801886 | 0.480811 | 0.561 | [0.061 0.439 0. 0.5 ] | 0.0615175 | 0.63341 | 0.694927 | [0.061 0.939] | 0.561 |
-| (0.5, 80) | 0.0946084 | 0.482392 | 0.577 | [0.077 0.423 0. 0.5 ] | 0.0679813 | 0.634759 | 0.702741 | [0.077 0.923] | 0.577 |
-| (0.5, 81) | 0.106413 | 0.474587 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0724391 | 0.632283 | 0.704722 | [0.081 0.919] | 0.581 |
-| (0.5, 82) | 0.0781018 | 0.487898 | 0.566 | [0.067 0.433 0.001 0.499] | 0.0478596 | 0.649068 | 0.696927 | [0.068 0.932] | 0.566 |
-| (0.5, 83) | 0.0936024 | 0.473398 | 0.567 | [0.067 0.433 0. 0.5 ] | 0.0720418 | 0.625795 | 0.697837 | [0.067 0.933] | 0.567 |
-| (0.5, 84) | 0.111706 | 0.459294 | 0.571 | [0.071 0.429 0. 0.5 ] | 0.0712875 | 0.628503 | 0.69979 | [0.071 0.929] | 0.571 |
-| (0.5, 85) | 0.0536686 | 0.513331 | 0.567 | [0.067 0.433 0. 0.5 ] | 0.039865 | 0.657972 | 0.697837 | [0.067 0.933] | 0.567 |
-| (0.5, 86) | 0.0633176 | 0.509682 | 0.573 | [0.073 0.427 0. 0.5 ] | 0.0460594 | 0.654711 | 0.700771 | [0.073 0.927] | 0.573 |
-| (0.5, 87) | 0.0521377 | 0.525862 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0411703 | 0.662065 | 0.703235 | [0.078 0.922] | 0.578 |
-| (0.5, 88) | 0.0845024 | 0.501498 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0657795 | 0.641434 | 0.707214 | [0.086 0.914] | 0.586 |
-| (0.5, 89) | 0.0716476 | 0.514352 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0514473 | 0.655766 | 0.707214 | [0.086 0.914] | 0.586 |
-| (0.5, 90) | 0.0727238 | 0.512276 | 0.585 | [0.085 0.415 0. 0.5 ] | 0.0502498 | 0.656464 | 0.706714 | [0.085 0.915] | 0.585 |
-| (0.5, 91) | 0.0693259 | 0.507674 | 0.577 | [0.077 0.423 0. 0.5 ] | 0.0515734 | 0.651167 | 0.702741 | [0.077 0.923] | 0.577 |
-| (0.5, 92) | 0.0893712 | 0.486629 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0645728 | 0.637674 | 0.702247 | [0.076 0.924] | 0.576 |
-| (0.5, 93) | 0.0645983 | 0.509402 | 0.574 | [0.075 0.425 0.001 0.499] | 0.0470981 | 0.653745 | 0.700843 | [0.076 0.924] | 0.574 |
-| (0.5, 94) | 0.0577857 | 0.528214 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0477799 | 0.659434 | 0.707214 | [0.086 0.914] | 0.586 |
-| (0.5, 95) | 0.0683137 | 0.511686 | 0.58 | [0.08 0.42 0. 0.5 ] | 0.0438813 | 0.660344 | 0.704225 | [0.08 0.92] | 0.58 |
-| (0.5, 96) | 0.0836411 | 0.485359 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0653466 | 0.633465 | 0.698812 | [0.069 0.931] | 0.569 |
-| (0.5, 97) | 0.0842354 | 0.485765 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.048951 | 0.65035 | 0.699301 | [0.07 0.93] | 0.57 |
-| (0.5, 98) | 0.100673 | 0.472327 | 0.573 | [0.073 0.427 0. 0.5 ] | 0.0649737 | 0.635797 | 0.700771 | [0.073 0.927] | 0.573 |
-| (0.5, 99) | 0.0852149 | 0.486785 | 0.572 | [0.073 0.427 0.001 0.499] | 0.0583452 | 0.641515 | 0.69986 | [0.074 0.926] | 0.572 |
-| (0.55, 0) | 0.0730904 | 0.53891 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0428355 | 0.696412 | 0.739247 | [0.062 0.938] | 0.612 |
-| (0.55, 1) | 0.0661012 | 0.542899 | 0.609 | [0.059 0.391 0. 0.55 ] | 0.0467022 | 0.691058 | 0.73776 | [0.059 0.941] | 0.609 |
-| (0.55, 2) | 0.0644516 | 0.542548 | 0.607 | [0.057 0.393 0. 0.55 ] | 0.046827 | 0.689945 | 0.736772 | [0.057 0.943] | 0.607 |
-| (0.55, 3) | 0.0620741 | 0.547926 | 0.61 | [0.06 0.39 0. 0.55] | 0.0387163 | 0.699539 | 0.738255 | [0.06 0.94] | 0.61 |
-| (0.55, 4) | 0.0833749 | 0.528625 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.05636 | 0.682887 | 0.739247 | [0.062 0.938] | 0.612 |
-| (0.55, 5) | 0.1047 | 0.5133 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0670869 | 0.675153 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 6) | 0.0682258 | 0.538774 | 0.607 | [0.057 0.393 0. 0.55 ] | 0.0365568 | 0.700215 | 0.736772 | [0.057 0.943] | 0.607 |
-| (0.55, 7) | 0.0636036 | 0.566396 | 0.63 | [0.081 0.369 0.001 0.549] | 0.0466895 | 0.701267 | 0.747956 | [0.082 0.918] | 0.63 |
-| (0.55, 8) | 0.0886129 | 0.523387 | 0.612 | [0.063 0.387 0.001 0.549] | 0.058874 | 0.680022 | 0.738896 | [0.064 0.936] | 0.612 |
-| (0.55, 9) | 0.0695911 | 0.535409 | 0.605 | [0.056 0.394 0.001 0.549] | 0.0521205 | 0.683312 | 0.735432 | [0.057 0.943] | 0.605 |
-| (0.55, 10) | 0.0832089 | 0.543791 | 0.627 | [0.077 0.373 0. 0.55 ] | 0.0564085 | 0.690367 | 0.746775 | [0.077 0.923] | 0.627 |
-| (0.55, 11) | 0.0741853 | 0.553815 | 0.628 | [0.079 0.371 0.001 0.549] | 0.0503493 | 0.696589 | 0.746939 | [0.08 0.92] | 0.628 |
-| (0.55, 12) | 0.0767586 | 0.530241 | 0.607 | [0.058 0.392 0.001 0.549] | 0.054906 | 0.681513 | 0.736419 | [0.059 0.941] | 0.607 |
-| (0.55, 13) | 0.108092 | 0.515908 | 0.624 | [0.074 0.376 0. 0.55 ] | 0.0698793 | 0.675378 | 0.745257 | [0.074 0.926] | 0.624 |
-| (0.55, 14) | 0.0878994 | 0.532101 | 0.62 | [0.071 0.379 0.001 0.549] | 0.0573614 | 0.685534 | 0.742896 | [0.072 0.928] | 0.62 |
-| (0.55, 15) | 0.0678694 | 0.559131 | 0.627 | [0.077 0.373 0. 0.55 ] | 0.042195 | 0.70458 | 0.746775 | [0.077 0.923] | 0.627 |
-| (0.55, 16) | 0.0683432 | 0.539657 | 0.608 | [0.058 0.392 0. 0.55 ] | 0.0498925 | 0.687373 | 0.737265 | [0.058 0.942] | 0.608 |
-| (0.55, 17) | 0.0753853 | 0.536615 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0528654 | 0.686382 | 0.739247 | [0.062 0.938] | 0.612 |
-| (0.55, 18) | 0.086495 | 0.527505 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0563929 | 0.683499 | 0.739892 | [0.066 0.934] | 0.614 |
-| (0.55, 19) | 0.0657372 | 0.545263 | 0.611 | [0.061 0.389 0. 0.55 ] | 0.0404072 | 0.698344 | 0.738751 | [0.061 0.939] | 0.611 |
-| (0.55, 20) | 0.108858 | 0.504142 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0840232 | 0.655721 | 0.739744 | [0.063 0.937] | 0.613 |
-| (0.55, 21) | 0.0967053 | 0.505295 | 0.602 | [0.053 0.397 0.001 0.549] | 0.066302 | 0.667655 | 0.733957 | [0.054 0.946] | 0.602 |
-| (0.55, 22) | 0.0630256 | 0.553974 | 0.617 | [0.068 0.382 0.001 0.549] | 0.045882 | 0.695509 | 0.741391 | [0.069 0.931] | 0.617 |
-| (0.55, 23) | 0.0913141 | 0.522686 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0593481 | 0.680894 | 0.740242 | [0.064 0.936] | 0.614 |
-| (0.55, 24) | 0.0817313 | 0.530269 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0508022 | 0.688445 | 0.739247 | [0.062 0.938] | 0.612 |
-| (0.55, 25) | 0.077761 | 0.540239 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0587776 | 0.683463 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 26) | 0.117069 | 0.500931 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0827969 | 0.659443 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 27) | 0.0470736 | 0.581926 | 0.629 | [0.08 0.37 0.001 0.549] | 0.0371326 | 0.710315 | 0.747447 | [0.081 0.919] | 0.629 |
-| (0.55, 28) | 0.0650752 | 0.559925 | 0.625 | [0.076 0.374 0.001 0.549] | 0.0448129 | 0.700605 | 0.745418 | [0.077 0.923] | 0.625 |
-| (0.55, 29) | 0.0881858 | 0.528814 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0568185 | 0.684921 | 0.74174 | [0.067 0.933] | 0.617 |
-| (0.55, 30) | 0.0977565 | 0.528244 | 0.626 | [0.076 0.374 0. 0.55 ] | 0.0690057 | 0.677263 | 0.746269 | [0.076 0.924] | 0.626 |
-| (0.55, 31) | 0.0871869 | 0.523813 | 0.611 | [0.061 0.389 0. 0.55 ] | 0.0582915 | 0.680459 | 0.738751 | [0.061 0.939] | 0.611 |
-| (0.55, 32) | 0.0728003 | 0.5452 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0543715 | 0.687869 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 33) | 0.0809225 | 0.523078 | 0.604 | [0.054 0.396 0. 0.55 ] | 0.0520946 | 0.6832 | 0.735294 | [0.054 0.946] | 0.604 |
-| (0.55, 34) | 0.100559 | 0.526441 | 0.627 | [0.077 0.373 0. 0.55 ] | 0.0630208 | 0.683754 | 0.746775 | [0.077 0.923] | 0.627 |
-| (0.55, 35) | 0.103207 | 0.513793 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0645554 | 0.677184 | 0.74174 | [0.067 0.933] | 0.617 |
-| (0.55, 36) | 0.0817379 | 0.536262 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0547587 | 0.687481 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 37) | 0.075124 | 0.537876 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0481441 | 0.6916 | 0.739744 | [0.063 0.937] | 0.613 |
-| (0.55, 38) | 0.0678917 | 0.557108 | 0.625 | [0.075 0.375 0. 0.55 ] | 0.0452231 | 0.70054 | 0.745763 | [0.075 0.925] | 0.625 |
-| (0.55, 39) | 0.0702522 | 0.550748 | 0.621 | [0.072 0.378 0.001 0.549] | 0.0474194 | 0.695979 | 0.743399 | [0.073 0.927] | 0.621 |
-| (0.55, 40) | 0.0989642 | 0.522036 | 0.621 | [0.071 0.379 0. 0.55 ] | 0.061899 | 0.681847 | 0.743746 | [0.071 0.929] | 0.621 |
-| (0.55, 41) | 0.0844022 | 0.539598 | 0.624 | [0.074 0.376 0. 0.55 ] | 0.0556893 | 0.689568 | 0.745257 | [0.074 0.926] | 0.624 |
-| (0.55, 42) | 0.0793985 | 0.555601 | 0.635 | [0.086 0.364 0.001 0.549] | 0.0532486 | 0.697264 | 0.750513 | [0.087 0.913] | 0.635 |
-| (0.55, 43) | 0.0422454 | 0.564755 | 0.607 | [0.058 0.392 0.001 0.549] | 0.0257601 | 0.710658 | 0.736419 | [0.059 0.941] | 0.607 |
-| (0.55, 44) | 0.0642159 | 0.551784 | 0.616 | [0.066 0.384 0. 0.55 ] | 0.0499338 | 0.691306 | 0.74124 | [0.066 0.934] | 0.616 |
-| (0.55, 45) | 0.0775302 | 0.54147 | 0.619 | [0.069 0.381 0. 0.55 ] | 0.0494472 | 0.693294 | 0.742741 | [0.069 0.931] | 0.619 |
-| (0.55, 46) | 0.0855431 | 0.530457 | 0.616 | [0.066 0.384 0. 0.55 ] | 0.0539876 | 0.687252 | 0.74124 | [0.066 0.934] | 0.616 |
-| (0.55, 47) | 0.0621009 | 0.567899 | 0.63 | [0.081 0.369 0.001 0.549] | 0.0462904 | 0.701666 | 0.747956 | [0.082 0.918] | 0.63 |
-| (0.55, 48) | 0.0883259 | 0.526674 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0598105 | 0.680581 | 0.740391 | [0.067 0.933] | 0.615 |
-| (0.55, 49) | 0.0951236 | 0.512876 | 0.608 | [0.059 0.391 0.001 0.549] | 0.0690868 | 0.667826 | 0.736913 | [0.06 0.94] | 0.608 |
-| (0.55, 50) | 0.0554219 | 0.551578 | 0.607 | [0.057 0.393 0. 0.55 ] | 0.0409083 | 0.695863 | 0.736772 | [0.057 0.943] | 0.607 |
-| (0.55, 51) | 0.0839772 | 0.516023 | 0.6 | [0.053 0.397 0.003 0.547] | 0.0600569 | 0.672206 | 0.732262 | [0.056 0.944] | 0.6 |
-| (0.55, 52) | 0.12439 | 0.48961 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0840354 | 0.656207 | 0.740242 | [0.064 0.936] | 0.614 |
-| (0.55, 53) | 0.0616151 | 0.552385 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0439556 | 0.695937 | 0.739892 | [0.066 0.934] | 0.614 |
-| (0.55, 54) | 0.0917346 | 0.531265 | 0.623 | [0.073 0.377 0. 0.55 ] | 0.0659632 | 0.67879 | 0.744753 | [0.073 0.927] | 0.623 |
-| (0.55, 55) | 0.0825903 | 0.53441 | 0.617 | [0.068 0.382 0.001 0.549] | 0.0581616 | 0.683229 | 0.741391 | [0.069 0.931] | 0.617 |
-| (0.55, 56) | 0.0439757 | 0.564024 | 0.608 | [0.058 0.392 0. 0.55 ] | 0.0307259 | 0.706539 | 0.737265 | [0.058 0.942] | 0.608 |
-| (0.55, 57) | 0.0791233 | 0.533877 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0549126 | 0.684832 | 0.739744 | [0.063 0.937] | 0.613 |
-| (0.55, 58) | 0.0466274 | 0.568373 | 0.615 | [0.065 0.385 0. 0.55 ] | 0.0319929 | 0.708748 | 0.740741 | [0.065 0.935] | 0.615 |
-| (0.55, 59) | 0.0716604 | 0.54134 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0421397 | 0.697605 | 0.739744 | [0.063 0.937] | 0.613 |
-| (0.55, 60) | 0.0891312 | 0.525869 | 0.615 | [0.066 0.384 0.001 0.549] | 0.055412 | 0.684979 | 0.740391 | [0.067 0.933] | 0.615 |
-| (0.55, 61) | 0.050594 | 0.567406 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0318906 | 0.71035 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 62) | 0.0764588 | 0.536541 | 0.613 | [0.064 0.386 0.001 0.549] | 0.0534303 | 0.685964 | 0.739394 | [0.065 0.935] | 0.613 |
-| (0.55, 63) | 0.0825997 | 0.5264 | 0.609 | [0.059 0.391 0. 0.55 ] | 0.0549614 | 0.682798 | 0.73776 | [0.059 0.941] | 0.609 |
-| (0.55, 64) | 0.0790597 | 0.53894 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0599859 | 0.682254 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 65) | 0.102482 | 0.509518 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0717024 | 0.667545 | 0.739247 | [0.062 0.938] | 0.612 |
-| (0.55, 66) | 0.0946111 | 0.521389 | 0.616 | [0.067 0.383 0.001 0.549] | 0.0639841 | 0.676907 | 0.740891 | [0.068 0.932] | 0.616 |
-| (0.55, 67) | 0.0656431 | 0.551357 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0496327 | 0.692107 | 0.74174 | [0.067 0.933] | 0.617 |
-| (0.55, 68) | 0.069672 | 0.551328 | 0.621 | [0.071 0.379 0. 0.55 ] | 0.0451221 | 0.698624 | 0.743746 | [0.071 0.929] | 0.621 |
-| (0.55, 69) | 0.0642955 | 0.555705 | 0.62 | [0.07 0.38 0. 0.55] | 0.0396424 | 0.703601 | 0.743243 | [0.07 0.93] | 0.62 |
-| (0.55, 70) | 0.0843746 | 0.530625 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0508608 | 0.68953 | 0.740391 | [0.067 0.933] | 0.615 |
-| (0.55, 71) | 0.0788593 | 0.531141 | 0.61 | [0.06 0.39 0. 0.55] | 0.0476278 | 0.690627 | 0.738255 | [0.06 0.94] | 0.61 |
-| (0.55, 72) | 0.0766319 | 0.540368 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0548507 | 0.686889 | 0.74174 | [0.067 0.933] | 0.617 |
-| (0.55, 73) | 0.0480531 | 0.566947 | 0.615 | [0.065 0.385 0. 0.55 ] | 0.0363437 | 0.704397 | 0.740741 | [0.065 0.935] | 0.615 |
-| (0.55, 74) | 0.101802 | 0.516198 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0708638 | 0.671376 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 75) | 0.0852682 | 0.540732 | 0.626 | [0.076 0.374 0. 0.55 ] | 0.0630882 | 0.68318 | 0.746269 | [0.076 0.924] | 0.626 |
-| (0.55, 76) | 0.0654355 | 0.555565 | 0.621 | [0.073 0.377 0.002 0.548] | 0.048294 | 0.694757 | 0.743051 | [0.075 0.925] | 0.621 |
-| (0.55, 77) | 0.0788674 | 0.540133 | 0.619 | [0.07 0.38 0.001 0.549] | 0.0505293 | 0.691864 | 0.742394 | [0.071 0.929] | 0.619 |
-| (0.55, 78) | 0.0809986 | 0.521001 | 0.602 | [0.052 0.398 0. 0.55 ] | 0.0579031 | 0.676409 | 0.734312 | [0.052 0.948] | 0.602 |
-| (0.55, 79) | 0.0710941 | 0.543906 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0542047 | 0.686186 | 0.740391 | [0.067 0.933] | 0.615 |
-| (0.55, 80) | 0.104299 | 0.515701 | 0.62 | [0.071 0.379 0.001 0.549] | 0.065018 | 0.677878 | 0.742896 | [0.072 0.928] | 0.62 |
-| (0.55, 81) | 0.053892 | 0.565108 | 0.619 | [0.069 0.381 0. 0.55 ] | 0.0370133 | 0.705728 | 0.742741 | [0.069 0.931] | 0.619 |
-| (0.55, 82) | 0.0392997 | 0.5717 | 0.611 | [0.061 0.389 0. 0.55 ] | 0.0282315 | 0.710519 | 0.738751 | [0.061 0.939] | 0.611 |
-| (0.55, 83) | 0.0996358 | 0.514364 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0624861 | 0.677406 | 0.739892 | [0.066 0.934] | 0.614 |
-| (0.55, 84) | 0.0668299 | 0.56717 | 0.634 | [0.084 0.366 0. 0.55 ] | 0.049494 | 0.700847 | 0.750341 | [0.084 0.916] | 0.634 |
-| (0.55, 85) | 0.0628239 | 0.555176 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0445864 | 0.697654 | 0.74224 | [0.068 0.932] | 0.618 |
-| (0.55, 86) | 0.080314 | 0.529686 | 0.61 | [0.06 0.39 0. 0.55] | 0.0544223 | 0.683833 | 0.738255 | [0.06 0.94] | 0.61 |
-| (0.55, 87) | 0.0760951 | 0.544905 | 0.621 | [0.071 0.379 0. 0.55 ] | 0.0544041 | 0.689342 | 0.743746 | [0.071 0.929] | 0.621 |
-| (0.55, 88) | 0.0713211 | 0.557679 | 0.629 | [0.079 0.371 0. 0.55 ] | 0.0527228 | 0.695068 | 0.747791 | [0.079 0.921] | 0.629 |
-| (0.55, 89) | 0.0759801 | 0.53702 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0498224 | 0.689922 | 0.739744 | [0.063 0.937] | 0.613 |
-| (0.55, 90) | 0.0725677 | 0.541432 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0533703 | 0.686872 | 0.740242 | [0.064 0.936] | 0.614 |
-| (0.55, 91) | 0.0842715 | 0.530729 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0616303 | 0.678761 | 0.740391 | [0.067 0.933] | 0.615 |
-| (0.55, 92) | 0.0881018 | 0.525898 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0610744 | 0.678818 | 0.739892 | [0.066 0.934] | 0.614 |
-| (0.55, 93) | 0.0972321 | 0.513768 | 0.611 | [0.062 0.388 0.001 0.549] | 0.0641005 | 0.674299 | 0.738399 | [0.063 0.937] | 0.611 |
-| (0.55, 94) | 0.0627574 | 0.562243 | 0.625 | [0.075 0.375 0. 0.55 ] | 0.0409383 | 0.704824 | 0.745763 | [0.075 0.925] | 0.625 |
-| (0.55, 95) | 0.07313 | 0.53787 | 0.611 | [0.062 0.388 0.001 0.549] | 0.0538739 | 0.684526 | 0.738399 | [0.063 0.937] | 0.611 |
-| (0.55, 96) | 0.0938753 | 0.508125 | 0.602 | [0.053 0.397 0.001 0.549] | 0.0607252 | 0.673232 | 0.733957 | [0.054 0.946] | 0.602 |
-| (0.55, 97) | 0.0986028 | 0.515397 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0621644 | 0.678078 | 0.740242 | [0.064 0.936] | 0.614 |
-| (0.55, 98) | 0.0961309 | 0.527869 | 0.624 | [0.074 0.376 0. 0.55 ] | 0.05855 | 0.686707 | 0.745257 | [0.074 0.926] | 0.624 |
-| (0.55, 99) | 0.0959075 | 0.505093 | 0.601 | [0.052 0.398 0.001 0.549] | 0.0639415 | 0.669525 | 0.733467 | [0.053 0.947] | 0.601 |
-| (0.6, 0) | 0.0881511 | 0.577849 | 0.666 | [0.067 0.333 0.001 0.599] | 0.055237 | 0.726747 | 0.781984 | [0.068 0.932] | 0.666 |
-| (0.6, 1) | 0.0676567 | 0.594343 | 0.662 | [0.063 0.337 0.001 0.599] | 0.0477349 | 0.732213 | 0.779948 | [0.064 0.936] | 0.662 |
-| (0.6, 2) | 0.0491176 | 0.612882 | 0.662 | [0.062 0.338 0. 0.6 ] | 0.027934 | 0.7523 | 0.780234 | [0.062 0.938] | 0.662 |
-| (0.6, 3) | 0.0568165 | 0.596183 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.035421 | 0.740274 | 0.775695 | [0.053 0.947] | 0.653 |
-| (0.6, 4) | 0.0615035 | 0.605496 | 0.667 | [0.068 0.332 0.001 0.599] | 0.040621 | 0.741874 | 0.782495 | [0.069 0.931] | 0.667 |
-| (0.6, 5) | 0.0730526 | 0.589947 | 0.663 | [0.063 0.337 0. 0.6 ] | 0.0445382 | 0.736204 | 0.780742 | [0.063 0.937] | 0.663 |
-| (0.6, 6) | 0.0522423 | 0.607758 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0293391 | 0.749882 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 7) | 0.0615754 | 0.594425 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0386705 | 0.738532 | 0.777202 | [0.056 0.944] | 0.656 |
-| (0.6, 8) | 0.0665795 | 0.582421 | 0.649 | [0.049 0.351 0. 0.6 ] | 0.0407432 | 0.732951 | 0.773694 | [0.049 0.951] | 0.649 |
-| (0.6, 9) | 0.0737038 | 0.576296 | 0.65 | [0.051 0.349 0.001 0.599] | 0.0521496 | 0.721752 | 0.773902 | [0.052 0.948] | 0.65 |
-| (0.6, 10) | 0.085578 | 0.578422 | 0.664 | [0.064 0.336 0. 0.6 ] | 0.0560622 | 0.725188 | 0.78125 | [0.064 0.936] | 0.664 |
-| (0.6, 11) | 0.064456 | 0.598544 | 0.663 | [0.064 0.336 0.001 0.599] | 0.0459933 | 0.734463 | 0.780456 | [0.065 0.935] | 0.663 |
-| (0.6, 12) | 0.0562835 | 0.604716 | 0.661 | [0.061 0.339 0. 0.6 ] | 0.0319463 | 0.747781 | 0.779727 | [0.061 0.939] | 0.661 |
-| (0.6, 13) | 0.0716397 | 0.59336 | 0.665 | [0.065 0.335 0. 0.6 ] | 0.0419245 | 0.739834 | 0.781759 | [0.065 0.935] | 0.665 |
-| (0.6, 14) | 0.0583248 | 0.601675 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0437987 | 0.735422 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 15) | 0.0434325 | 0.614568 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.0282215 | 0.749989 | 0.77821 | [0.058 0.942] | 0.658 |
-| (0.6, 16) | 0.047439 | 0.621561 | 0.669 | [0.07 0.33 0.001 0.599] | 0.0270545 | 0.756464 | 0.783519 | [0.071 0.929] | 0.669 |
-| (0.6, 17) | 0.0933332 | 0.582667 | 0.676 | [0.077 0.323 0.001 0.599] | 0.058648 | 0.728474 | 0.787122 | [0.078 0.922] | 0.676 |
-| (0.6, 18) | 0.0390986 | 0.632901 | 0.672 | [0.072 0.328 0. 0.6 ] | 0.0259942 | 0.759346 | 0.78534 | [0.072 0.928] | 0.672 |
-| (0.6, 19) | 0.0678786 | 0.600121 | 0.668 | [0.068 0.332 0. 0.6 ] | 0.0480079 | 0.735282 | 0.78329 | [0.068 0.932] | 0.668 |
-| (0.6, 20) | 0.0539102 | 0.60209 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0370685 | 0.740134 | 0.777202 | [0.056 0.944] | 0.656 |
-| (0.6, 21) | 0.0820918 | 0.574908 | 0.657 | [0.058 0.342 0.001 0.599] | 0.0477883 | 0.729629 | 0.777417 | [0.059 0.941] | 0.657 |
-| (0.6, 22) | 0.0825172 | 0.577483 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0515437 | 0.727677 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 23) | 0.0568959 | 0.596104 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0359543 | 0.739741 | 0.775695 | [0.053 0.947] | 0.653 |
-| (0.6, 24) | 0.0690674 | 0.599933 | 0.669 | [0.069 0.331 0. 0.6 ] | 0.0425673 | 0.741234 | 0.783801 | [0.069 0.931] | 0.669 |
-| (0.6, 25) | 0.076607 | 0.581393 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.048413 | 0.729797 | 0.77821 | [0.058 0.942] | 0.658 |
-| (0.6, 26) | 0.0757756 | 0.580224 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0556539 | 0.721548 | 0.777202 | [0.056 0.944] | 0.656 |
-| (0.6, 27) | 0.0648862 | 0.578114 | 0.643 | [0.044 0.356 0.001 0.599] | 0.0435439 | 0.726874 | 0.770418 | [0.045 0.955] | 0.643 |
-| (0.6, 28) | 0.0528143 | 0.600186 | 0.653 | [0.054 0.346 0.001 0.599] | 0.0340945 | 0.74131 | 0.775405 | [0.055 0.945] | 0.653 |
-| (0.6, 29) | 0.0667359 | 0.601264 | 0.668 | [0.068 0.332 0. 0.6 ] | 0.0335976 | 0.749692 | 0.78329 | [0.068 0.932] | 0.668 |
-| (0.6, 30) | 0.0675497 | 0.58545 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0414239 | 0.734271 | 0.775695 | [0.053 0.947] | 0.653 |
-| (0.6, 31) | 0.0660047 | 0.598995 | 0.665 | [0.066 0.334 0.001 0.599] | 0.0426951 | 0.738779 | 0.781474 | [0.067 0.933] | 0.665 |
-| (0.6, 32) | 0.0442055 | 0.618795 | 0.663 | [0.063 0.337 0. 0.6 ] | 0.030497 | 0.750245 | 0.780742 | [0.063 0.937] | 0.663 |
-| (0.6, 33) | 0.0443751 | 0.609625 | 0.654 | [0.057 0.343 0.003 0.597] | 0.021217 | 0.754108 | 0.775325 | [0.06 0.94] | 0.654 |
-| (0.6, 34) | 0.0943248 | 0.576675 | 0.671 | [0.072 0.328 0.001 0.599] | 0.0621463 | 0.722399 | 0.784545 | [0.073 0.927] | 0.671 |
-| (0.6, 35) | 0.0535663 | 0.600434 | 0.654 | [0.054 0.346 0. 0.6 ] | 0.0296445 | 0.746552 | 0.776197 | [0.054 0.946] | 0.654 |
-| (0.6, 36) | 0.0605562 | 0.604444 | 0.665 | [0.065 0.335 0. 0.6 ] | 0.0392217 | 0.742537 | 0.781759 | [0.065 0.935] | 0.665 |
-| (0.6, 37) | 0.0866943 | 0.573306 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0538976 | 0.725323 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 38) | 0.0545823 | 0.593418 | 0.648 | [0.048 0.352 0. 0.6 ] | 0.0352752 | 0.737921 | 0.773196 | [0.048 0.952] | 0.648 |
-| (0.6, 39) | 0.0336199 | 0.63738 | 0.671 | [0.071 0.329 0. 0.6 ] | 0.0231063 | 0.76172 | 0.784827 | [0.071 0.929] | 0.671 |
-| (0.6, 40) | 0.087924 | 0.585076 | 0.673 | [0.074 0.326 0.001 0.599] | 0.0570552 | 0.728519 | 0.785574 | [0.075 0.925] | 0.673 |
-| (0.6, 41) | 0.0627829 | 0.594217 | 0.657 | [0.057 0.343 0. 0.6 ] | 0.0367148 | 0.740991 | 0.777706 | [0.057 0.943] | 0.657 |
-| (0.6, 42) | 0.0661217 | 0.588878 | 0.655 | [0.055 0.345 0. 0.6 ] | 0.0462947 | 0.730404 | 0.776699 | [0.055 0.945] | 0.655 |
-| (0.6, 43) | 0.0472093 | 0.608791 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0315161 | 0.745686 | 0.777202 | [0.056 0.944] | 0.656 |
-| (0.6, 44) | 0.062447 | 0.595553 | 0.658 | [0.059 0.341 0.001 0.599] | 0.0393384 | 0.738584 | 0.777922 | [0.06 0.94] | 0.658 |
-| (0.6, 45) | 0.0553339 | 0.597666 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0316878 | 0.744007 | 0.775695 | [0.053 0.947] | 0.653 |
-| (0.6, 46) | 0.0603068 | 0.612693 | 0.673 | [0.073 0.327 0. 0.6 ] | 0.0403993 | 0.745455 | 0.785855 | [0.073 0.927] | 0.673 |
-| (0.6, 47) | 0.05245 | 0.59255 | 0.645 | [0.045 0.355 0. 0.6 ] | 0.0331539 | 0.73855 | 0.771704 | [0.045 0.955] | 0.645 |
-| (0.6, 48) | 0.0380303 | 0.61797 | 0.656 | [0.057 0.343 0.001 0.599] | 0.0253723 | 0.751541 | 0.776913 | [0.058 0.942] | 0.656 |
-| (0.6, 49) | 0.0738868 | 0.593113 | 0.667 | [0.067 0.333 0. 0.6 ] | 0.0450897 | 0.737689 | 0.782779 | [0.067 0.933] | 0.667 |
-| (0.6, 50) | 0.0354761 | 0.619524 | 0.655 | [0.055 0.345 0. 0.6 ] | 0.0207475 | 0.755952 | 0.776699 | [0.055 0.945] | 0.655 |
-| (0.6, 51) | 0.0437408 | 0.600259 | 0.644 | [0.046 0.354 0.002 0.598] | 0.0251752 | 0.745443 | 0.770619 | [0.048 0.952] | 0.644 |
-| (0.6, 52) | 0.0453087 | 0.612691 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.0260618 | 0.752148 | 0.77821 | [0.058 0.942] | 0.658 |
-| (0.6, 53) | 0.0722881 | 0.592712 | 0.665 | [0.065 0.335 0. 0.6 ] | 0.047134 | 0.734625 | 0.781759 | [0.065 0.935] | 0.665 |
-| (0.6, 54) | 0.0421048 | 0.615895 | 0.658 | [0.059 0.341 0.001 0.599] | 0.0287259 | 0.749196 | 0.777922 | [0.06 0.94] | 0.658 |
-| (0.6, 55) | 0.066419 | 0.595581 | 0.662 | [0.062 0.338 0. 0.6 ] | 0.048597 | 0.731637 | 0.780234 | [0.062 0.938] | 0.662 |
-| (0.6, 56) | 0.0490829 | 0.605917 | 0.655 | [0.056 0.344 0.001 0.599] | 0.0286827 | 0.747727 | 0.77641 | [0.057 0.943] | 0.655 |
-| (0.6, 57) | 0.066909 | 0.583091 | 0.65 | [0.05 0.35 0. 0.6 ] | 0.0391516 | 0.735042 | 0.774194 | [0.05 0.95] | 0.65 |
-| (0.6, 58) | 0.0463631 | 0.608637 | 0.655 | [0.057 0.343 0.002 0.598] | 0.0324057 | 0.743714 | 0.776119 | [0.059 0.941] | 0.655 |
-| (0.6, 59) | 0.0634421 | 0.586558 | 0.65 | [0.05 0.35 0. 0.6 ] | 0.0366035 | 0.73759 | 0.774194 | [0.05 0.95] | 0.65 |
-| (0.6, 60) | 0.0772581 | 0.582742 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0456753 | 0.733546 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 61) | 0.0671458 | 0.591854 | 0.659 | [0.06 0.34 0.001 0.599] | 0.0450789 | 0.733349 | 0.778428 | [0.061 0.939] | 0.659 |
-| (0.6, 62) | 0.0522664 | 0.599734 | 0.652 | [0.054 0.346 0.002 0.598] | 0.0359455 | 0.738666 | 0.774611 | [0.056 0.944] | 0.652 |
-| (0.6, 63) | 0.063116 | 0.588884 | 0.652 | [0.052 0.348 0. 0.6 ] | 0.0464068 | 0.728787 | 0.775194 | [0.052 0.948] | 0.652 |
-| (0.6, 64) | 0.0512798 | 0.61072 | 0.662 | [0.062 0.338 0. 0.6 ] | 0.0361072 | 0.744127 | 0.780234 | [0.062 0.938] | 0.662 |
-| (0.6, 65) | 0.0398496 | 0.62515 | 0.665 | [0.066 0.334 0.001 0.599] | 0.0283116 | 0.753163 | 0.781474 | [0.067 0.933] | 0.665 |
-| (0.6, 66) | 0.05223 | 0.60377 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0330846 | 0.744118 | 0.777202 | [0.056 0.944] | 0.656 |
-| (0.6, 67) | 0.0785234 | 0.581477 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0465799 | 0.732641 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 68) | 0.0458468 | 0.604153 | 0.65 | [0.051 0.349 0.001 0.599] | 0.0325445 | 0.741357 | 0.773902 | [0.052 0.948] | 0.65 |
-| (0.6, 69) | 0.0860971 | 0.577903 | 0.664 | [0.065 0.335 0.001 0.599] | 0.0522512 | 0.728714 | 0.780965 | [0.066 0.934] | 0.664 |
-| (0.6, 70) | 0.0806746 | 0.589325 | 0.67 | [0.071 0.329 0.001 0.599] | 0.0519335 | 0.732098 | 0.784031 | [0.072 0.928] | 0.67 |
-| (0.6, 71) | 0.0784531 | 0.577547 | 0.656 | [0.057 0.343 0.001 0.599] | 0.0508206 | 0.726092 | 0.776913 | [0.058 0.942] | 0.656 |
-| (0.6, 72) | 0.0399431 | 0.613057 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0248862 | 0.750809 | 0.775695 | [0.053 0.947] | 0.653 |
-| (0.6, 73) | 0.0907004 | 0.5673 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.0579146 | 0.720295 | 0.77821 | [0.058 0.942] | 0.658 |
-| (0.6, 74) | 0.0589133 | 0.596087 | 0.655 | [0.057 0.343 0.002 0.598] | 0.035358 | 0.740761 | 0.776119 | [0.059 0.941] | 0.655 |
-| (0.6, 75) | 0.0447162 | 0.624284 | 0.669 | [0.07 0.33 0.001 0.599] | 0.0297811 | 0.753738 | 0.783519 | [0.071 0.929] | 0.669 |
-| (0.6, 76) | 0.0764676 | 0.583532 | 0.66 | [0.061 0.339 0.001 0.599] | 0.0455743 | 0.733359 | 0.778934 | [0.062 0.938] | 0.66 |
-| (0.6, 77) | 0.0816418 | 0.584358 | 0.666 | [0.066 0.334 0. 0.6 ] | 0.0474277 | 0.734841 | 0.782269 | [0.066 0.934] | 0.666 |
-| (0.6, 78) | 0.0735751 | 0.572425 | 0.646 | [0.047 0.353 0.001 0.599] | 0.0540717 | 0.717836 | 0.771907 | [0.048 0.952] | 0.646 |
-| (0.6, 79) | 0.0570677 | 0.596932 | 0.654 | [0.055 0.345 0.001 0.599] | 0.0358959 | 0.740011 | 0.775907 | [0.056 0.944] | 0.654 |
-| (0.6, 80) | 0.0479097 | 0.60509 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.032508 | 0.743187 | 0.775695 | [0.053 0.947] | 0.653 |
-| (0.6, 81) | 0.0575586 | 0.594441 | 0.652 | [0.052 0.348 0. 0.6 ] | 0.038032 | 0.737162 | 0.775194 | [0.052 0.948] | 0.652 |
-| (0.6, 82) | 0.0761639 | 0.587836 | 0.664 | [0.064 0.336 0. 0.6 ] | 0.0527736 | 0.728476 | 0.78125 | [0.064 0.936] | 0.664 |
-| (0.6, 83) | 0.0529422 | 0.607058 | 0.66 | [0.062 0.338 0.002 0.598] | 0.0371465 | 0.741499 | 0.778646 | [0.064 0.936] | 0.66 |
-| (0.6, 84) | 0.0580051 | 0.595995 | 0.654 | [0.055 0.345 0.001 0.599] | 0.0419757 | 0.733931 | 0.775907 | [0.056 0.944] | 0.654 |
-| (0.6, 85) | 0.0759486 | 0.587051 | 0.663 | [0.064 0.336 0.001 0.599] | 0.0539609 | 0.726495 | 0.780456 | [0.065 0.935] | 0.663 |
-| (0.6, 86) | 0.055749 | 0.619251 | 0.675 | [0.076 0.324 0.001 0.599] | 0.0404567 | 0.746149 | 0.786605 | [0.077 0.923] | 0.675 |
-| (0.6, 87) | 0.0509463 | 0.610054 | 0.661 | [0.061 0.339 0. 0.6 ] | 0.0335963 | 0.746131 | 0.779727 | [0.061 0.939] | 0.661 |
-| (0.6, 88) | 0.0355192 | 0.647481 | 0.683 | [0.083 0.317 0. 0.6 ] | 0.0262492 | 0.764786 | 0.791035 | [0.083 0.917] | 0.683 |
-| (0.6, 89) | 0.0640233 | 0.596977 | 0.661 | [0.061 0.339 0. 0.6 ] | 0.0340662 | 0.745661 | 0.779727 | [0.061 0.939] | 0.661 |
-| (0.6, 90) | 0.0701055 | 0.599894 | 0.67 | [0.07 0.33 0. 0.6 ] | 0.0407704 | 0.743543 | 0.784314 | [0.07 0.93] | 0.67 |
-| (0.6, 91) | 0.0341839 | 0.616816 | 0.651 | [0.052 0.348 0.001 0.599] | 0.0247255 | 0.749677 | 0.774402 | [0.053 0.947] | 0.651 |
-| (0.6, 92) | 0.0685819 | 0.611418 | 0.68 | [0.08 0.32 0. 0.6 ] | 0.0442119 | 0.745262 | 0.789474 | [0.08 0.92] | 0.68 |
-| (0.6, 93) | 0.0894146 | 0.567585 | 0.657 | [0.058 0.342 0.001 0.599] | 0.0539746 | 0.723443 | 0.777417 | [0.059 0.941] | 0.657 |
-| (0.6, 94) | 0.0650644 | 0.598936 | 0.664 | [0.064 0.336 0. 0.6 ] | 0.037461 | 0.743789 | 0.78125 | [0.064 0.936] | 0.664 |
-| (0.6, 95) | 0.0508844 | 0.599116 | 0.65 | [0.05 0.35 0. 0.6 ] | 0.0363045 | 0.737889 | 0.774194 | [0.05 0.95] | 0.65 |
-| (0.6, 96) | 0.0661985 | 0.603802 | 0.67 | [0.07 0.33 0. 0.6 ] | 0.039231 | 0.745083 | 0.784314 | [0.07 0.93] | 0.67 |
-| (0.6, 97) | 0.0892339 | 0.565766 | 0.655 | [0.057 0.343 0.002 0.598] | 0.0551233 | 0.720996 | 0.776119 | [0.059 0.941] | 0.655 |
-| (0.6, 98) | 0.0976272 | 0.562373 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0597714 | 0.719449 | 0.779221 | [0.06 0.94] | 0.66 |
-| (0.6, 99) | 0.0636941 | 0.593306 | 0.657 | [0.058 0.342 0.001 0.599] | 0.0418411 | 0.735576 | 0.777417 | [0.059 0.941] | 0.657 |
-| (0.65, 0) | 0.0739099 | 0.61709 | 0.691 | [0.041 0.309 0. 0.65 ] | 0.0526754 | 0.75528 | 0.807955 | [0.041 0.959] | 0.691 |
-| (0.65, 1) | 0.0477952 | 0.658205 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0325986 | 0.78296 | 0.815558 | [0.056 0.944] | 0.706 |
-| (0.65, 2) | 0.0229299 | 0.67707 | 0.7 | [0.05 0.3 0. 0.65] | 0.0159672 | 0.796533 | 0.8125 | [0.05 0.95] | 0.7 |
-| (0.65, 3) | 0.0538452 | 0.645155 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0312362 | 0.780756 | 0.811993 | [0.049 0.951] | 0.699 |
-| (0.65, 4) | 0.0925105 | 0.61149 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0581155 | 0.756421 | 0.814536 | [0.054 0.946] | 0.704 |
-| (0.65, 5) | 0.0578091 | 0.647191 | 0.705 | [0.056 0.294 0.001 0.649] | 0.0351116 | 0.779703 | 0.814815 | [0.057 0.943] | 0.705 |
-| (0.65, 6) | 0.062668 | 0.629332 | 0.692 | [0.042 0.308 0. 0.65 ] | 0.0378076 | 0.77065 | 0.808458 | [0.042 0.958] | 0.692 |
-| (0.65, 7) | 0.0638892 | 0.645111 | 0.709 | [0.06 0.29 0.001 0.649] | 0.0344787 | 0.782387 | 0.816866 | [0.061 0.939] | 0.709 |
-| (0.65, 8) | 0.0890857 | 0.608914 | 0.698 | [0.049 0.301 0.001 0.649] | 0.0547982 | 0.756452 | 0.81125 | [0.05 0.95] | 0.698 |
-| (0.65, 9) | 0.0611097 | 0.63789 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0413559 | 0.770637 | 0.811993 | [0.049 0.951] | 0.699 |
-| (0.65, 10) | 0.0562112 | 0.632789 | 0.689 | [0.039 0.311 0. 0.65 ] | 0.0323477 | 0.774605 | 0.806952 | [0.039 0.961] | 0.689 |
-| (0.65, 11) | 0.0589517 | 0.638048 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0366973 | 0.774282 | 0.810979 | [0.047 0.953] | 0.697 |
-| (0.65, 12) | 0.0482449 | 0.654755 | 0.703 | [0.053 0.297 0. 0.65 ] | 0.0320813 | 0.781945 | 0.814026 | [0.053 0.947] | 0.703 |
-| (0.65, 13) | 0.0736681 | 0.636332 | 0.71 | [0.061 0.289 0.001 0.649] | 0.0420889 | 0.775291 | 0.81738 | [0.062 0.938] | 0.71 |
-| (0.65, 14) | 0.0430404 | 0.66396 | 0.707 | [0.057 0.293 0. 0.65 ] | 0.0287048 | 0.787366 | 0.81607 | [0.057 0.943] | 0.707 |
-| (0.65, 15) | 0.0560687 | 0.637931 | 0.694 | [0.045 0.305 0.001 0.649] | 0.0310618 | 0.778165 | 0.809227 | [0.046 0.954] | 0.694 |
-| (0.65, 16) | 0.0456324 | 0.653368 | 0.699 | [0.05 0.3 0.001 0.649] | 0.0263883 | 0.785369 | 0.811757 | [0.051 0.949] | 0.699 |
-| (0.65, 17) | 0.064613 | 0.632387 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0387813 | 0.772198 | 0.810979 | [0.047 0.953] | 0.697 |
-| (0.65, 18) | 0.0734902 | 0.62551 | 0.699 | [0.052 0.298 0.003 0.647] | 0.0453684 | 0.765917 | 0.811285 | [0.055 0.945] | 0.699 |
-| (0.65, 19) | 0.0628344 | 0.639166 | 0.702 | [0.054 0.296 0.002 0.648] | 0.0345718 | 0.778477 | 0.813049 | [0.056 0.944] | 0.702 |
-| (0.65, 20) | 0.0673456 | 0.640654 | 0.708 | [0.059 0.291 0.001 0.649] | 0.0388652 | 0.777487 | 0.816352 | [0.06 0.94] | 0.708 |
-| (0.65, 21) | 0.0752692 | 0.617731 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0459319 | 0.763029 | 0.808961 | [0.043 0.957] | 0.693 |
-| (0.65, 22) | 0.0450542 | 0.652946 | 0.698 | [0.049 0.301 0.001 0.649] | 0.0298831 | 0.781367 | 0.81125 | [0.05 0.95] | 0.698 |
-| (0.65, 23) | 0.0337217 | 0.675278 | 0.709 | [0.06 0.29 0.001 0.649] | 0.0242411 | 0.792625 | 0.816866 | [0.061 0.939] | 0.709 |
-| (0.65, 24) | 0.052651 | 0.649349 | 0.702 | [0.054 0.296 0.002 0.648] | 0.0312041 | 0.781845 | 0.813049 | [0.056 0.944] | 0.702 |
-| (0.65, 25) | 0.0663186 | 0.632681 | 0.699 | [0.05 0.3 0.001 0.649] | 0.0405875 | 0.77117 | 0.811757 | [0.051 0.949] | 0.699 |
-| (0.65, 26) | 0.0504554 | 0.668545 | 0.719 | [0.069 0.281 0. 0.65 ] | 0.0367366 | 0.785528 | 0.822264 | [0.069 0.931] | 0.719 |
-| (0.65, 27) | 0.0624661 | 0.646534 | 0.709 | [0.06 0.29 0.001 0.649] | 0.0340857 | 0.78278 | 0.816866 | [0.061 0.939] | 0.709 |
-| (0.65, 28) | 0.0504084 | 0.651592 | 0.702 | [0.054 0.296 0.002 0.648] | 0.0300143 | 0.783035 | 0.813049 | [0.056 0.944] | 0.702 |
-| (0.65, 29) | 0.0659238 | 0.629076 | 0.695 | [0.046 0.304 0.001 0.649] | 0.0444182 | 0.765314 | 0.809732 | [0.047 0.953] | 0.695 |
-| (0.65, 30) | 0.0823759 | 0.623624 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0473784 | 0.76818 | 0.815558 | [0.056 0.944] | 0.706 |
-| (0.65, 31) | 0.06098 | 0.63702 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.0393581 | 0.772128 | 0.811486 | [0.048 0.952] | 0.698 |
-| (0.65, 32) | 0.0843391 | 0.613661 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.0515263 | 0.759959 | 0.811486 | [0.048 0.952] | 0.698 |
-| (0.65, 33) | 0.0906488 | 0.620351 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.0539358 | 0.764189 | 0.818125 | [0.061 0.939] | 0.711 |
-| (0.65, 34) | 0.051511 | 0.654489 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0330441 | 0.782514 | 0.815558 | [0.056 0.944] | 0.706 |
-| (0.65, 35) | 0.068127 | 0.623873 | 0.692 | [0.044 0.306 0.002 0.648] | 0.0475416 | 0.760438 | 0.80798 | [0.046 0.954] | 0.692 |
-| (0.65, 36) | 0.05139 | 0.65561 | 0.707 | [0.058 0.292 0.001 0.649] | 0.0342364 | 0.781603 | 0.815839 | [0.059 0.941] | 0.707 |
-| (0.65, 37) | 0.0553304 | 0.64467 | 0.7 | [0.05 0.3 0. 0.65] | 0.0339875 | 0.778513 | 0.8125 | [0.05 0.95] | 0.7 |
-| (0.65, 38) | 0.0220005 | 0.683 | 0.705 | [0.058 0.292 0.003 0.647] | 0.0105615 | 0.803787 | 0.814349 | [0.061 0.939] | 0.705 |
-| (0.65, 39) | 0.0344814 | 0.684519 | 0.719 | [0.069 0.281 0. 0.65 ] | 0.0200217 | 0.802243 | 0.822264 | [0.069 0.931] | 0.719 |
-| (0.65, 40) | 0.0192848 | 0.687715 | 0.707 | [0.058 0.292 0.001 0.649] | 0.0118281 | 0.804011 | 0.815839 | [0.059 0.941] | 0.707 |
-| (0.65, 41) | 0.0629462 | 0.641054 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0417315 | 0.772805 | 0.814536 | [0.054 0.946] | 0.704 |
-| (0.65, 42) | 0.0509591 | 0.648041 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0323075 | 0.779685 | 0.811993 | [0.049 0.951] | 0.699 |
-| (0.65, 43) | 0.0284053 | 0.684595 | 0.713 | [0.063 0.287 0. 0.65 ] | 0.0186126 | 0.800543 | 0.819156 | [0.063 0.937] | 0.713 |
-| (0.65, 44) | 0.0542485 | 0.646751 | 0.701 | [0.051 0.299 0. 0.65 ] | 0.0377042 | 0.775304 | 0.813008 | [0.051 0.949] | 0.701 |
-| (0.65, 45) | 0.0473474 | 0.648653 | 0.696 | [0.046 0.304 0. 0.65 ] | 0.0312429 | 0.779231 | 0.810474 | [0.046 0.954] | 0.696 |
-| (0.65, 46) | 0.0573545 | 0.647646 | 0.705 | [0.055 0.295 0. 0.65 ] | 0.0328666 | 0.78218 | 0.815047 | [0.055 0.945] | 0.705 |
-| (0.65, 47) | 0.0778962 | 0.630104 | 0.708 | [0.058 0.292 0. 0.65 ] | 0.0481544 | 0.768428 | 0.816583 | [0.058 0.942] | 0.708 |
-| (0.65, 48) | 0.0636552 | 0.634345 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.042687 | 0.768799 | 0.811486 | [0.048 0.952] | 0.698 |
-| (0.65, 49) | 0.0684301 | 0.62757 | 0.696 | [0.046 0.304 0. 0.65 ] | 0.0417784 | 0.768695 | 0.810474 | [0.046 0.954] | 0.696 |
-| (0.65, 50) | 0.0600838 | 0.648916 | 0.709 | [0.059 0.291 0. 0.65 ] | 0.0338159 | 0.78328 | 0.817096 | [0.059 0.941] | 0.709 |
-| (0.65, 51) | 0.0315922 | 0.670408 | 0.702 | [0.052 0.298 0. 0.65 ] | 0.0197787 | 0.793738 | 0.813517 | [0.052 0.948] | 0.702 |
-| (0.65, 52) | 0.0805029 | 0.622497 | 0.703 | [0.053 0.297 0. 0.65 ] | 0.0511013 | 0.762925 | 0.814026 | [0.053 0.947] | 0.703 |
-| (0.65, 53) | 0.0684217 | 0.642578 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.0392399 | 0.778885 | 0.818125 | [0.061 0.939] | 0.711 |
-| (0.65, 54) | 0.0478134 | 0.656187 | 0.704 | [0.055 0.295 0.001 0.649] | 0.0278887 | 0.786415 | 0.814304 | [0.056 0.944] | 0.704 |
-| (0.65, 55) | 0.042591 | 0.654409 | 0.697 | [0.048 0.302 0.001 0.649] | 0.0266163 | 0.784127 | 0.810743 | [0.049 0.951] | 0.697 |
-| (0.65, 56) | 0.029453 | 0.676547 | 0.706 | [0.057 0.293 0.001 0.649] | 0.0176713 | 0.797655 | 0.815327 | [0.058 0.942] | 0.706 |
-| (0.65, 57) | 0.0740491 | 0.622951 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0467645 | 0.764215 | 0.810979 | [0.047 0.953] | 0.697 |
-| (0.65, 58) | 0.0721752 | 0.626825 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0467288 | 0.765264 | 0.811993 | [0.049 0.951] | 0.699 |
-| (0.65, 59) | 0.0720319 | 0.631968 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0479897 | 0.766547 | 0.814536 | [0.054 0.946] | 0.704 |
-| (0.65, 60) | 0.0632844 | 0.629716 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0401505 | 0.76881 | 0.808961 | [0.043 0.957] | 0.693 |
-| (0.65, 61) | 0.0312424 | 0.673758 | 0.705 | [0.056 0.294 0.001 0.649] | 0.0161445 | 0.79867 | 0.814815 | [0.057 0.943] | 0.705 |
-| (0.65, 62) | 0.0886932 | 0.611307 | 0.7 | [0.05 0.3 0. 0.65] | 0.0558643 | 0.756636 | 0.8125 | [0.05 0.95] | 0.7 |
-| (0.65, 63) | 0.0666069 | 0.627393 | 0.694 | [0.044 0.306 0. 0.65 ] | 0.0392557 | 0.770209 | 0.809465 | [0.044 0.956] | 0.694 |
-| (0.65, 64) | 0.0493815 | 0.650619 | 0.7 | [0.05 0.3 0. 0.65] | 0.033134 | 0.779366 | 0.8125 | [0.05 0.95] | 0.7 |
-| (0.65, 65) | 0.0743474 | 0.627653 | 0.702 | [0.053 0.297 0.001 0.649] | 0.0455442 | 0.767739 | 0.813283 | [0.054 0.946] | 0.702 |
-| (0.65, 66) | 0.0590576 | 0.642942 | 0.702 | [0.052 0.298 0. 0.65 ] | 0.0378606 | 0.775656 | 0.813517 | [0.052 0.948] | 0.702 |
-| (0.65, 67) | 0.0504622 | 0.640538 | 0.691 | [0.042 0.308 0.001 0.649] | 0.0288882 | 0.778828 | 0.807716 | [0.043 0.957] | 0.691 |
-| (0.65, 68) | 0.0491287 | 0.651871 | 0.701 | [0.051 0.299 0. 0.65 ] | 0.0298382 | 0.78317 | 0.813008 | [0.051 0.949] | 0.701 |
-| (0.65, 69) | 0.0671233 | 0.625877 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0465888 | 0.762372 | 0.808961 | [0.043 0.957] | 0.693 |
-| (0.65, 70) | 0.0581822 | 0.649818 | 0.708 | [0.059 0.291 0.001 0.649] | 0.039018 | 0.777334 | 0.816352 | [0.06 0.94] | 0.708 |
-| (0.65, 71) | 0.0656468 | 0.639353 | 0.705 | [0.055 0.295 0. 0.65 ] | 0.0450479 | 0.769999 | 0.815047 | [0.055 0.945] | 0.705 |
-| (0.65, 72) | 0.042696 | 0.659304 | 0.702 | [0.052 0.298 0. 0.65 ] | 0.029769 | 0.783748 | 0.813517 | [0.052 0.948] | 0.702 |
-| (0.65, 73) | 0.0621281 | 0.642872 | 0.705 | [0.055 0.295 0. 0.65 ] | 0.0356486 | 0.779398 | 0.815047 | [0.055 0.945] | 0.705 |
-| (0.65, 74) | 0.0614174 | 0.638583 | 0.7 | [0.05 0.3 0. 0.65] | 0.0417064 | 0.770794 | 0.8125 | [0.05 0.95] | 0.7 |
-| (0.65, 75) | 0.0690815 | 0.636919 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0382886 | 0.77727 | 0.815558 | [0.056 0.944] | 0.706 |
-| (0.65, 76) | 0.0663326 | 0.632667 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0417255 | 0.770267 | 0.811993 | [0.049 0.951] | 0.699 |
-| (0.65, 77) | 0.0329796 | 0.66402 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0208125 | 0.790167 | 0.810979 | [0.047 0.953] | 0.697 |
-| (0.65, 78) | 0.0305704 | 0.66243 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0199287 | 0.789032 | 0.808961 | [0.043 0.957] | 0.693 |
-| (0.65, 79) | 0.0591355 | 0.651865 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.033893 | 0.784232 | 0.818125 | [0.061 0.939] | 0.711 |
-| (0.65, 80) | 0.0828419 | 0.621158 | 0.704 | [0.055 0.295 0.001 0.649] | 0.0513442 | 0.762959 | 0.814304 | [0.056 0.944] | 0.704 |
-| (0.65, 81) | 0.0405789 | 0.653421 | 0.694 | [0.044 0.306 0. 0.65 ] | 0.0252821 | 0.784182 | 0.809465 | [0.044 0.956] | 0.694 |
-| (0.65, 82) | 0.0552317 | 0.631768 | 0.687 | [0.037 0.313 0. 0.65 ] | 0.0343555 | 0.771596 | 0.805952 | [0.037 0.963] | 0.687 |
-| (0.65, 83) | 0.0558149 | 0.656185 | 0.712 | [0.062 0.288 0. 0.65 ] | 0.032602 | 0.786038 | 0.81864 | [0.062 0.938] | 0.712 |
-| (0.65, 84) | 0.0477823 | 0.663218 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.025912 | 0.792213 | 0.818125 | [0.061 0.939] | 0.711 |
-| (0.65, 85) | 0.0763267 | 0.624673 | 0.701 | [0.052 0.298 0.001 0.649] | 0.0468193 | 0.765955 | 0.812774 | [0.053 0.947] | 0.701 |
-| (0.65, 86) | 0.0360446 | 0.657955 | 0.694 | [0.044 0.306 0. 0.65 ] | 0.0189634 | 0.790501 | 0.809465 | [0.044 0.956] | 0.694 |
-| (0.65, 87) | 0.0756674 | 0.622333 | 0.698 | [0.05 0.3 0.002 0.648] | 0.0459044 | 0.765109 | 0.811014 | [0.052 0.948] | 0.698 |
-| (0.65, 88) | 0.071613 | 0.627387 | 0.699 | [0.051 0.299 0.002 0.648] | 0.0411009 | 0.770421 | 0.811522 | [0.053 0.947] | 0.699 |
-| (0.65, 89) | 0.0559207 | 0.652079 | 0.708 | [0.059 0.291 0.001 0.649] | 0.0337589 | 0.782593 | 0.816352 | [0.06 0.94] | 0.708 |
-| (0.65, 90) | 0.0897853 | 0.600215 | 0.69 | [0.043 0.307 0.003 0.647] | 0.0598717 | 0.746861 | 0.806733 | [0.046 0.954] | 0.69 |
-| (0.65, 91) | 0.0652016 | 0.625798 | 0.691 | [0.041 0.309 0. 0.65 ] | 0.0389561 | 0.768999 | 0.807955 | [0.041 0.959] | 0.691 |
-| (0.65, 92) | 0.0780821 | 0.632918 | 0.711 | [0.062 0.288 0.001 0.649] | 0.0459551 | 0.77194 | 0.817895 | [0.063 0.937] | 0.711 |
-| (0.65, 93) | 0.0369541 | 0.667046 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0196589 | 0.794877 | 0.814536 | [0.054 0.946] | 0.704 |
-| (0.65, 94) | 0.0868486 | 0.613151 | 0.7 | [0.05 0.3 0. 0.65] | 0.052447 | 0.760053 | 0.8125 | [0.05 0.95] | 0.7 |
-| (0.65, 95) | 0.0358453 | 0.659155 | 0.695 | [0.046 0.304 0.001 0.649] | 0.0240181 | 0.785714 | 0.809732 | [0.047 0.953] | 0.695 |
-| (0.65, 96) | 0.0577789 | 0.650221 | 0.708 | [0.058 0.292 0. 0.65 ] | 0.0355455 | 0.781037 | 0.816583 | [0.058 0.942] | 0.708 |
-| (0.65, 97) | 0.0486151 | 0.645385 | 0.694 | [0.045 0.305 0.001 0.649] | 0.0316332 | 0.777594 | 0.809227 | [0.046 0.954] | 0.694 |
-| (0.65, 98) | 0.04014 | 0.65786 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.0231171 | 0.788369 | 0.811486 | [0.048 0.952] | 0.698 |
-| (0.65, 99) | 0.0660544 | 0.650946 | 0.717 | [0.069 0.281 0.002 0.648] | 0.0386239 | 0.782149 | 0.820773 | [0.071 0.929] | 0.717 |
-| (0.7, 0) | 0.0257237 | 0.713276 | 0.739 | [0.039 0.261 0. 0.7 ] | 0.0158348 | 0.827031 | 0.842866 | [0.039 0.961] | 0.739 |
-| (0.7, 1) | 0.0460058 | 0.694994 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.0269198 | 0.816962 | 0.843882 | [0.041 0.959] | 0.741 |
-| (0.7, 2) | 0.042295 | 0.707705 | 0.75 | [0.051 0.249 0.001 0.699] | 0.0283674 | 0.819934 | 0.848301 | [0.052 0.948] | 0.75 |
-| (0.7, 3) | 0.0288274 | 0.716173 | 0.745 | [0.048 0.252 0.003 0.697] | 0.0176749 | 0.827686 | 0.845361 | [0.051 0.949] | 0.745 |
-| (0.7, 4) | 0.018103 | 0.731897 | 0.75 | [0.051 0.249 0.001 0.699] | 0.0117766 | 0.836524 | 0.848301 | [0.052 0.948] | 0.75 |
-| (0.7, 5) | 0.0264212 | 0.724579 | 0.751 | [0.051 0.249 0. 0.7 ] | 0.0160402 | 0.832959 | 0.848999 | [0.051 0.949] | 0.751 |
-| (0.7, 6) | 0.0509385 | 0.697061 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0314891 | 0.815784 | 0.847273 | [0.05 0.95] | 0.748 |
-| (0.7, 7) | 0.0454696 | 0.71053 | 0.756 | [0.056 0.244 0. 0.7 ] | 0.0292168 | 0.822365 | 0.851582 | [0.056 0.944] | 0.756 |
-| (0.7, 8) | 0.0431997 | 0.7028 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0222566 | 0.824176 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 9) | 0.0663396 | 0.67366 | 0.74 | [0.04 0.26 0. 0.7 ] | 0.0383664 | 0.805007 | 0.843373 | [0.04 0.96] | 0.74 |
-| (0.7, 10) | 0.0436339 | 0.702366 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.021438 | 0.824995 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 11) | 0.0669556 | 0.677044 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0409375 | 0.804286 | 0.845224 | [0.046 0.954] | 0.744 |
-| (0.7, 12) | 0.0236731 | 0.732327 | 0.756 | [0.056 0.244 0. 0.7 ] | 0.0114491 | 0.840132 | 0.851582 | [0.056 0.944] | 0.756 |
-| (0.7, 13) | 0.0543776 | 0.695622 | 0.75 | [0.051 0.249 0.001 0.699] | 0.0311781 | 0.817123 | 0.848301 | [0.052 0.948] | 0.75 |
-| (0.7, 14) | 0.0219647 | 0.722035 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0127436 | 0.83248 | 0.845224 | [0.046 0.954] | 0.744 |
-| (0.7, 15) | 0.04204 | 0.70096 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0265375 | 0.818363 | 0.8449 | [0.043 0.957] | 0.743 |
-| (0.7, 16) | 0.0428157 | 0.693184 | 0.736 | [0.037 0.263 0.001 0.699] | 0.0243824 | 0.816773 | 0.841155 | [0.038 0.962] | 0.736 |
-| (0.7, 17) | 0.0241334 | 0.712867 | 0.737 | [0.038 0.262 0.001 0.699] | 0.0143424 | 0.827319 | 0.841662 | [0.039 0.961] | 0.737 |
-| (0.7, 18) | 0.0369606 | 0.702039 | 0.739 | [0.039 0.261 0. 0.7 ] | 0.0251595 | 0.817706 | 0.842866 | [0.039 0.961] | 0.739 |
-| (0.7, 19) | 0.0357608 | 0.708239 | 0.744 | [0.046 0.254 0.002 0.698] | 0.0229315 | 0.822105 | 0.845036 | [0.048 0.952] | 0.744 |
-| (0.7, 20) | 0.0544485 | 0.688552 | 0.743 | [0.044 0.256 0.001 0.699] | 0.0318225 | 0.81289 | 0.844713 | [0.045 0.955] | 0.743 |
-| (0.7, 21) | 0.0619287 | 0.696071 | 0.758 | [0.058 0.242 0. 0.7 ] | 0.0351504 | 0.817468 | 0.852619 | [0.058 0.942] | 0.758 |
-| (0.7, 22) | 0.04091 | 0.69509 | 0.736 | [0.037 0.263 0.001 0.699] | 0.0261895 | 0.814966 | 0.841155 | [0.038 0.962] | 0.736 |
-| (0.7, 23) | 0.0581635 | 0.696836 | 0.755 | [0.055 0.245 0. 0.7 ] | 0.0322321 | 0.818832 | 0.851064 | [0.055 0.945] | 0.755 |
-| (0.7, 24) | 0.031157 | 0.713843 | 0.745 | [0.046 0.254 0.001 0.699] | 0.020101 | 0.825634 | 0.845735 | [0.047 0.953] | 0.745 |
-| (0.7, 25) | 0.0699032 | 0.679097 | 0.749 | [0.049 0.251 0. 0.7 ] | 0.0441162 | 0.803855 | 0.847971 | [0.049 0.951] | 0.749 |
-| (0.7, 26) | 0.0365515 | 0.704449 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.02384 | 0.820042 | 0.843882 | [0.041 0.959] | 0.741 |
-| (0.7, 27) | 0.051094 | 0.686906 | 0.738 | [0.04 0.26 0.002 0.698] | 0.0296508 | 0.812327 | 0.841978 | [0.042 0.958] | 0.738 |
-| (0.7, 28) | 0.0580445 | 0.695955 | 0.754 | [0.054 0.246 0. 0.7 ] | 0.0329645 | 0.817582 | 0.850547 | [0.054 0.946] | 0.754 |
-| (0.7, 29) | 0.0581874 | 0.687813 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0329015 | 0.813531 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 30) | 0.0596123 | 0.683388 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0371841 | 0.807716 | 0.8449 | [0.043 0.957] | 0.743 |
-| (0.7, 31) | 0.0457276 | 0.695272 | 0.741 | [0.043 0.257 0.002 0.698] | 0.0284045 | 0.8151 | 0.843505 | [0.045 0.955] | 0.741 |
-| (0.7, 32) | 0.0302288 | 0.712771 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0195378 | 0.825363 | 0.8449 | [0.043 0.957] | 0.743 |
-| (0.7, 33) | 0.0102201 | 0.73978 | 0.75 | [0.05 0.25 0. 0.7 ] | 0.00445961 | 0.844025 | 0.848485 | [0.05 0.95] | 0.75 |
-| (0.7, 34) | 0.0382468 | 0.706753 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0235733 | 0.822348 | 0.845921 | [0.045 0.955] | 0.745 |
-| (0.7, 35) | 0.0399682 | 0.706032 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0243874 | 0.822045 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 36) | 0.0552478 | 0.685752 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.0321503 | 0.811732 | 0.843882 | [0.041 0.959] | 0.741 |
-| (0.7, 37) | 0.0626886 | 0.683311 | 0.746 | [0.047 0.253 0.001 0.699] | 0.0357774 | 0.81047 | 0.846247 | [0.048 0.952] | 0.746 |
-| (0.7, 38) | 0.0941167 | 0.653883 | 0.748 | [0.048 0.252 0. 0.7 ] | 0.0630955 | 0.784362 | 0.847458 | [0.048 0.952] | 0.748 |
-| (0.7, 39) | 0.0540688 | 0.684931 | 0.739 | [0.039 0.261 0. 0.7 ] | 0.0299878 | 0.812878 | 0.842866 | [0.039 0.961] | 0.739 |
-| (0.7, 40) | 0.0768883 | 0.673112 | 0.75 | [0.05 0.25 0. 0.7 ] | 0.0440604 | 0.804424 | 0.848485 | [0.05 0.95] | 0.75 |
-| (0.7, 41) | 0.0345316 | 0.705468 | 0.74 | [0.042 0.258 0.002 0.698] | 0.0216253 | 0.82137 | 0.842995 | [0.044 0.956] | 0.74 |
-| (0.7, 42) | 0.0386848 | 0.702315 | 0.741 | [0.042 0.258 0.001 0.699] | 0.0241046 | 0.819589 | 0.843693 | [0.043 0.957] | 0.741 |
-| (0.7, 43) | 0.0599738 | 0.673026 | 0.733 | [0.034 0.266 0.001 0.699] | 0.0351087 | 0.804531 | 0.83964 | [0.035 0.965] | 0.733 |
-| (0.7, 44) | 0.0584178 | 0.686582 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0322826 | 0.813639 | 0.845921 | [0.045 0.955] | 0.745 |
-| (0.7, 45) | 0.0447354 | 0.700265 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0272621 | 0.818659 | 0.845921 | [0.045 0.955] | 0.745 |
-| (0.7, 46) | 0.0340733 | 0.718927 | 0.753 | [0.053 0.247 0. 0.7 ] | 0.0217421 | 0.828288 | 0.85003 | [0.053 0.947] | 0.753 |
-| (0.7, 47) | 0.0335992 | 0.719401 | 0.753 | [0.053 0.247 0. 0.7 ] | 0.020345 | 0.829685 | 0.85003 | [0.053 0.947] | 0.753 |
-| (0.7, 48) | 0.0205774 | 0.714423 | 0.735 | [0.036 0.264 0.001 0.699] | 0.0129594 | 0.82769 | 0.840649 | [0.037 0.963] | 0.735 |
-| (0.7, 49) | 0.0587974 | 0.686203 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0339661 | 0.811955 | 0.845921 | [0.045 0.955] | 0.745 |
-| (0.7, 50) | 0.0351737 | 0.719826 | 0.755 | [0.056 0.244 0.001 0.699] | 0.0199776 | 0.830905 | 0.850883 | [0.057 0.943] | 0.755 |
-| (0.7, 51) | 0.0267817 | 0.728218 | 0.755 | [0.055 0.245 0. 0.7 ] | 0.0161224 | 0.834941 | 0.851064 | [0.055 0.945] | 0.755 |
-| (0.7, 52) | 0.0472808 | 0.698719 | 0.746 | [0.047 0.253 0.001 0.699] | 0.0257035 | 0.820544 | 0.846247 | [0.048 0.952] | 0.746 |
-| (0.7, 53) | 0.0651052 | 0.670895 | 0.736 | [0.036 0.264 0. 0.7 ] | 0.0414622 | 0.799884 | 0.841346 | [0.036 0.964] | 0.736 |
-| (0.7, 54) | 0.0266103 | 0.71839 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0163738 | 0.829548 | 0.845921 | [0.045 0.955] | 0.745 |
-| (0.7, 55) | 0.0556272 | 0.685373 | 0.741 | [0.042 0.258 0.001 0.699] | 0.0349463 | 0.808747 | 0.843693 | [0.043 0.957] | 0.741 |
-| (0.7, 56) | 0.0522764 | 0.689724 | 0.742 | [0.044 0.256 0.002 0.698] | 0.0302049 | 0.81381 | 0.844015 | [0.046 0.954] | 0.742 |
-| (0.7, 57) | 0.0489347 | 0.701065 | 0.75 | [0.05 0.25 0. 0.7 ] | 0.0319756 | 0.816509 | 0.848485 | [0.05 0.95] | 0.75 |
-| (0.7, 58) | 0.0572132 | 0.690787 | 0.748 | [0.048 0.252 0. 0.7 ] | 0.0348496 | 0.812608 | 0.847458 | [0.048 0.952] | 0.748 |
-| (0.7, 59) | 0.0616845 | 0.687316 | 0.749 | [0.052 0.248 0.003 0.697] | 0.0364798 | 0.810937 | 0.847416 | [0.055 0.945] | 0.749 |
-| (0.7, 60) | 0.0266481 | 0.719352 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0112287 | 0.835204 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 61) | 0.0431471 | 0.703853 | 0.747 | [0.047 0.253 0. 0.7 ] | 0.0277927 | 0.819152 | 0.846945 | [0.047 0.953] | 0.747 |
-| (0.7, 62) | 0.058813 | 0.695187 | 0.754 | [0.055 0.245 0.001 0.699] | 0.0385337 | 0.811831 | 0.850365 | [0.056 0.944] | 0.754 |
-| (0.7, 63) | 0.044278 | 0.703722 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0263027 | 0.82097 | 0.847273 | [0.05 0.95] | 0.748 |
-| (0.7, 64) | 0.0824936 | 0.657506 | 0.74 | [0.041 0.259 0.001 0.699] | 0.0498315 | 0.793353 | 0.843185 | [0.042 0.958] | 0.74 |
-| (0.7, 65) | 0.0487397 | 0.69226 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.0273824 | 0.8165 | 0.843882 | [0.041 0.959] | 0.741 |
-| (0.7, 66) | 0.0456017 | 0.700398 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0291693 | 0.817264 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 67) | 0.0599507 | 0.682049 | 0.742 | [0.042 0.258 0. 0.7 ] | 0.0336685 | 0.810722 | 0.844391 | [0.042 0.958] | 0.742 |
-| (0.7, 68) | 0.0606527 | 0.686347 | 0.747 | [0.049 0.251 0.002 0.698] | 0.0362096 | 0.810364 | 0.846574 | [0.051 0.949] | 0.747 |
-| (0.7, 69) | 0.0634868 | 0.670513 | 0.734 | [0.034 0.266 0. 0.7 ] | 0.0382688 | 0.802067 | 0.840336 | [0.034 0.966] | 0.734 |
-| (0.7, 70) | 0.0314017 | 0.715598 | 0.747 | [0.049 0.251 0.002 0.698] | 0.0198875 | 0.826686 | 0.846574 | [0.051 0.949] | 0.747 |
-| (0.7, 71) | 0.0570147 | 0.693985 | 0.751 | [0.051 0.249 0. 0.7 ] | 0.0312233 | 0.817776 | 0.848999 | [0.051 0.949] | 0.751 |
-| (0.7, 72) | 0.0439817 | 0.690018 | 0.734 | [0.035 0.265 0.001 0.699] | 0.0238598 | 0.816284 | 0.840144 | [0.036 0.964] | 0.734 |
-| (0.7, 73) | 0.0455512 | 0.698449 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0244858 | 0.820738 | 0.845224 | [0.046 0.954] | 0.744 |
-| (0.7, 74) | 0.0488415 | 0.697158 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0275018 | 0.818931 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 75) | 0.040398 | 0.701602 | 0.742 | [0.042 0.258 0. 0.7 ] | 0.025014 | 0.819377 | 0.844391 | [0.042 0.958] | 0.742 |
-| (0.7, 76) | 0.0338518 | 0.711148 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0211698 | 0.824752 | 0.845921 | [0.045 0.955] | 0.745 |
-| (0.7, 77) | 0.0635197 | 0.67848 | 0.742 | [0.042 0.258 0. 0.7 ] | 0.0368786 | 0.807512 | 0.844391 | [0.042 0.958] | 0.742 |
-| (0.7, 78) | 0.0168386 | 0.730161 | 0.747 | [0.048 0.252 0.001 0.699] | 0.00937337 | 0.837386 | 0.84676 | [0.049 0.951] | 0.747 |
-| (0.7, 79) | 0.0418986 | 0.714101 | 0.756 | [0.056 0.244 0. 0.7 ] | 0.025139 | 0.826443 | 0.851582 | [0.056 0.944] | 0.756 |
-| (0.7, 80) | 0.037095 | 0.711905 | 0.749 | [0.049 0.251 0. 0.7 ] | 0.0236265 | 0.824344 | 0.847971 | [0.049 0.951] | 0.749 |
-| (0.7, 81) | 0.0355185 | 0.710481 | 0.746 | [0.047 0.253 0.001 0.699] | 0.023162 | 0.823085 | 0.846247 | [0.048 0.952] | 0.746 |
-| (0.7, 82) | 0.051202 | 0.689798 | 0.741 | [0.043 0.257 0.002 0.698] | 0.0302617 | 0.813243 | 0.843505 | [0.045 0.955] | 0.741 |
-| (0.7, 83) | 0.0127804 | 0.72822 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.00508636 | 0.838795 | 0.843882 | [0.041 0.959] | 0.741 |
-| (0.7, 84) | 0.0571513 | 0.682849 | 0.74 | [0.042 0.258 0.002 0.698] | 0.0317753 | 0.81122 | 0.842995 | [0.044 0.956] | 0.74 |
-| (0.7, 85) | 0.03966 | 0.70434 | 0.744 | [0.044 0.256 0. 0.7 ] | 0.0248263 | 0.820584 | 0.845411 | [0.044 0.956] | 0.744 |
-| (0.7, 86) | 0.0395805 | 0.70942 | 0.749 | [0.05 0.25 0.001 0.699] | 0.0253555 | 0.822431 | 0.847787 | [0.051 0.949] | 0.749 |
-| (0.7, 87) | 0.0439101 | 0.70109 | 0.745 | [0.046 0.254 0.001 0.699] | 0.0245246 | 0.82121 | 0.845735 | [0.047 0.953] | 0.745 |
-| (0.7, 88) | 0.0251373 | 0.720863 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0166981 | 0.829735 | 0.846433 | [0.046 0.954] | 0.746 |
-| (0.7, 89) | 0.0427015 | 0.700298 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0273584 | 0.817542 | 0.8449 | [0.043 0.957] | 0.743 |
-| (0.7, 90) | 0.0521871 | 0.687813 | 0.74 | [0.04 0.26 0. 0.7 ] | 0.0297551 | 0.813618 | 0.843373 | [0.04 0.96] | 0.74 |
-| (0.7, 91) | 0.0432122 | 0.695788 | 0.739 | [0.04 0.26 0.001 0.699] | 0.0262949 | 0.816381 | 0.842676 | [0.041 0.959] | 0.739 |
-| (0.7, 92) | 0.0378549 | 0.706145 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0179952 | 0.827228 | 0.845224 | [0.046 0.954] | 0.744 |
-| (0.7, 93) | 0.0545061 | 0.693494 | 0.748 | [0.048 0.252 0. 0.7 ] | 0.0338916 | 0.813566 | 0.847458 | [0.048 0.952] | 0.748 |
-| (0.7, 94) | 0.0669098 | 0.67309 | 0.74 | [0.04 0.26 0. 0.7 ] | 0.0398733 | 0.8035 | 0.843373 | [0.04 0.96] | 0.74 |
-| (0.7, 95) | 0.0615466 | 0.686453 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0419311 | 0.805342 | 0.847273 | [0.05 0.95] | 0.748 |
-| (0.7, 96) | 0.0643432 | 0.684657 | 0.749 | [0.049 0.251 0. 0.7 ] | 0.0391777 | 0.808793 | 0.847971 | [0.049 0.951] | 0.749 |
-| (0.7, 97) | 0.0318799 | 0.69612 | 0.728 | [0.03 0.27 0.002 0.698] | 0.0182705 | 0.81866 | 0.83693 | [0.032 0.968] | 0.728 |
-| (0.7, 98) | 0.0286473 | 0.719353 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0153222 | 0.831951 | 0.847273 | [0.05 0.95] | 0.748 |
-| (0.7, 99) | 0.048621 | 0.683379 | 0.732 | [0.032 0.268 0. 0.7 ] | 0.0314276 | 0.807901 | 0.839329 | [0.032 0.968] | 0.732 |
-| (0.75, 0) | 0.0290489 | 0.763951 | 0.793 | [0.043 0.207 0. 0.75 ] | 0.0188064 | 0.859928 | 0.878735 | [0.043 0.957] | 0.793 |
-| (0.75, 1) | 0.0213086 | 0.783691 | 0.805 | [0.055 0.195 0. 0.75 ] | 0.0131107 | 0.871845 | 0.884956 | [0.055 0.945] | 0.805 |
-| (0.75, 2) | 0.0258045 | 0.769195 | 0.795 | [0.046 0.204 0.001 0.749] | 0.0152213 | 0.864403 | 0.879624 | [0.047 0.953] | 0.795 |
-| (0.75, 3) | 0.0499394 | 0.737061 | 0.787 | [0.037 0.213 0. 0.75 ] | 0.0290134 | 0.846643 | 0.875657 | [0.037 0.963] | 0.787 |
-| (0.75, 4) | 0.0376303 | 0.74437 | 0.782 | [0.032 0.218 0. 0.75 ] | 0.0197061 | 0.853402 | 0.873108 | [0.032 0.968] | 0.782 |
-| (0.75, 5) | 0.0469517 | 0.733048 | 0.78 | [0.03 0.22 0. 0.75] | 0.0263483 | 0.845745 | 0.872093 | [0.03 0.97] | 0.78 |
-| (0.75, 6) | 0.0370853 | 0.757915 | 0.795 | [0.046 0.204 0.001 0.749] | 0.0226526 | 0.856972 | 0.879624 | [0.047 0.953] | 0.795 |
-| (0.75, 7) | 0.0310667 | 0.756933 | 0.788 | [0.038 0.212 0. 0.75 ] | 0.0161298 | 0.860038 | 0.876168 | [0.038 0.962] | 0.788 |
-| (0.75, 8) | 0.0332692 | 0.761731 | 0.795 | [0.047 0.203 0.002 0.748] | 0.0202977 | 0.859185 | 0.879483 | [0.049 0.951] | 0.795 |
-| (0.75, 9) | 0.0136944 | 0.777306 | 0.791 | [0.041 0.209 0. 0.75 ] | 0.00761378 | 0.870092 | 0.877706 | [0.041 0.959] | 0.791 |
-| (0.75, 10) | 0.0441472 | 0.740853 | 0.785 | [0.036 0.214 0.001 0.749] | 0.0265147 | 0.847975 | 0.874489 | [0.037 0.963] | 0.785 |
-| (0.75, 11) | 0.00733119 | 0.775669 | 0.783 | [0.034 0.216 0.001 0.749] | 0.00279004 | 0.870679 | 0.873469 | [0.035 0.965] | 0.783 |
-| (0.75, 12) | 0.0121353 | 0.770865 | 0.783 | [0.035 0.215 0.002 0.748] | 0.00702411 | 0.866298 | 0.873322 | [0.037 0.963] | 0.783 |
-| (0.75, 13) | 0.0565286 | 0.731471 | 0.788 | [0.039 0.211 0.001 0.749] | 0.0321032 | 0.84392 | 0.876023 | [0.04 0.96] | 0.788 |
-| (0.75, 14) | 0.0152813 | 0.769719 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.00888373 | 0.865752 | 0.874636 | [0.035 0.965] | 0.785 |
-| (0.75, 15) | 0.0153936 | 0.772606 | 0.788 | [0.039 0.211 0.001 0.749] | 0.00762887 | 0.868395 | 0.876023 | [0.04 0.96] | 0.788 |
-| (0.75, 16) | 0.0119624 | 0.778038 | 0.79 | [0.042 0.208 0.002 0.748] | 0.00732564 | 0.869579 | 0.876905 | [0.044 0.956] | 0.79 |
-| (0.75, 17) | 0.0485998 | 0.7364 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.0266139 | 0.848022 | 0.874636 | [0.035 0.965] | 0.785 |
-| (0.75, 18) | 0.026567 | 0.751433 | 0.778 | [0.03 0.22 0.002 0.748] | 0.0149359 | 0.855844 | 0.87078 | [0.032 0.968] | 0.778 |
-| (0.75, 19) | 0.0434839 | 0.746516 | 0.79 | [0.04 0.21 0. 0.75] | 0.0227465 | 0.854447 | 0.877193 | [0.04 0.96] | 0.79 |
-| (0.75, 20) | 0.00358118 | 0.779419 | 0.783 | [0.035 0.215 0.002 0.748] | 0.00161839 | 0.871703 | 0.873322 | [0.037 0.963] | 0.783 |
-| (0.75, 21) | 0.0250464 | 0.757954 | 0.783 | [0.033 0.217 0. 0.75 ] | 0.0141667 | 0.85945 | 0.873617 | [0.033 0.967] | 0.783 |
-| (0.75, 22) | 0.00593084 | 0.793069 | 0.799 | [0.049 0.201 0. 0.75 ] | 0.00302196 | 0.878812 | 0.881834 | [0.049 0.951] | 0.799 |
-| (0.75, 23) | 0.0645649 | 0.724435 | 0.789 | [0.041 0.209 0.002 0.748] | 0.0377325 | 0.838659 | 0.876391 | [0.043 0.957] | 0.789 |
-| (0.75, 24) | 0.0404161 | 0.745584 | 0.786 | [0.036 0.214 0. 0.75 ] | 0.022775 | 0.852371 | 0.875146 | [0.036 0.964] | 0.786 |
-| (0.75, 25) | 0.0593057 | 0.727694 | 0.787 | [0.038 0.212 0.001 0.749] | 0.0333993 | 0.842112 | 0.875511 | [0.039 0.961] | 0.787 |
-| (0.75, 26) | 0.0611953 | 0.737805 | 0.799 | [0.049 0.201 0. 0.75 ] | 0.0339211 | 0.847913 | 0.881834 | [0.049 0.951] | 0.799 |
-| (0.75, 27) | 0.0335309 | 0.764469 | 0.798 | [0.049 0.201 0.001 0.749] | 0.0187754 | 0.862401 | 0.881176 | [0.05 0.95] | 0.798 |
-| (0.75, 28) | 0.0467563 | 0.734244 | 0.781 | [0.032 0.218 0.001 0.749] | 0.0259504 | 0.846502 | 0.872452 | [0.033 0.967] | 0.781 |
-| (0.75, 29) | 0.0367851 | 0.757215 | 0.794 | [0.045 0.205 0.001 0.749] | 0.0220216 | 0.857086 | 0.879108 | [0.046 0.954] | 0.794 |
-| (0.75, 30) | 0.0561704 | 0.73983 | 0.796 | [0.047 0.203 0.001 0.749] | 0.0301069 | 0.850034 | 0.880141 | [0.048 0.952] | 0.796 |
-| (0.75, 31) | 0.036463 | 0.759537 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0194914 | 0.86079 | 0.880282 | [0.046 0.954] | 0.796 |
-| (0.75, 32) | 0.0115699 | 0.76443 | 0.776 | [0.027 0.223 0.001 0.749] | 0.00582438 | 0.864094 | 0.869919 | [0.028 0.972] | 0.776 |
-| (0.75, 33) | 0.0385213 | 0.755479 | 0.794 | [0.044 0.206 0. 0.75 ] | 0.0240675 | 0.855182 | 0.87925 | [0.044 0.956] | 0.794 |
-| (0.75, 34) | 0.0279748 | 0.762025 | 0.79 | [0.04 0.21 0. 0.75] | 0.0177323 | 0.859461 | 0.877193 | [0.04 0.96] | 0.79 |
-| (0.75, 35) | 0.0437401 | 0.73526 | 0.779 | [0.031 0.219 0.002 0.748] | 0.0250926 | 0.846194 | 0.871287 | [0.033 0.967] | 0.779 |
-| (0.75, 36) | 0.024253 | 0.758747 | 0.783 | [0.034 0.216 0.001 0.749] | 0.0142197 | 0.85925 | 0.873469 | [0.035 0.965] | 0.783 |
-| (0.75, 37) | 0.0511354 | 0.726865 | 0.778 | [0.029 0.221 0.001 0.749] | 0.0319916 | 0.838939 | 0.87093 | [0.03 0.97] | 0.778 |
-| (0.75, 38) | 0.0391688 | 0.741831 | 0.781 | [0.032 0.218 0.001 0.749] | 0.0227259 | 0.849726 | 0.872452 | [0.033 0.967] | 0.781 |
-| (0.75, 39) | 0.049827 | 0.737173 | 0.787 | [0.038 0.212 0.001 0.749] | 0.0270195 | 0.848492 | 0.875511 | [0.039 0.961] | 0.787 |
-| (0.75, 40) | 0.0114272 | 0.785573 | 0.797 | [0.047 0.203 0. 0.75 ] | 0.00614797 | 0.874651 | 0.880799 | [0.047 0.953] | 0.797 |
-| (0.75, 41) | 0.0306715 | 0.762329 | 0.793 | [0.044 0.206 0.001 0.749] | 0.0183691 | 0.860223 | 0.878592 | [0.045 0.955] | 0.793 |
-| (0.75, 42) | 0.0395072 | 0.747493 | 0.787 | [0.039 0.211 0.002 0.748] | 0.0247259 | 0.85064 | 0.875366 | [0.041 0.959] | 0.787 |
-| (0.75, 43) | 0.0434636 | 0.749536 | 0.793 | [0.044 0.206 0.001 0.749] | 0.0248327 | 0.85376 | 0.878592 | [0.045 0.955] | 0.793 |
-| (0.75, 44) | 0.0360129 | 0.744987 | 0.781 | [0.031 0.219 0. 0.75 ] | 0.0199793 | 0.852621 | 0.8726 | [0.031 0.969] | 0.781 |
-| (0.75, 45) | 0.0280378 | 0.755962 | 0.784 | [0.035 0.215 0.001 0.749] | 0.0137074 | 0.860272 | 0.873979 | [0.036 0.964] | 0.784 |
-| (0.75, 46) | 0.0215758 | 0.774424 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0126768 | 0.867605 | 0.880282 | [0.046 0.954] | 0.796 |
-| (0.75, 47) | 0.0523155 | 0.739684 | 0.792 | [0.042 0.208 0. 0.75 ] | 0.0300079 | 0.848212 | 0.87822 | [0.042 0.958] | 0.792 |
-| (0.75, 48) | 0.0602019 | 0.728798 | 0.789 | [0.04 0.21 0.001 0.749] | 0.0383976 | 0.838138 | 0.876536 | [0.041 0.959] | 0.789 |
-| (0.75, 49) | 0.047031 | 0.739969 | 0.787 | [0.038 0.212 0.001 0.749] | 0.0290799 | 0.846431 | 0.875511 | [0.039 0.961] | 0.787 |
-| (0.75, 50) | 0.0273783 | 0.768622 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0135753 | 0.866706 | 0.880282 | [0.046 0.954] | 0.796 |
-| (0.75, 51) | 0.02684 | 0.76216 | 0.789 | [0.041 0.209 0.002 0.748] | 0.0131259 | 0.863265 | 0.876391 | [0.043 0.957] | 0.789 |
-| (0.75, 52) | 0.0400329 | 0.747967 | 0.788 | [0.039 0.211 0.001 0.749] | 0.0219925 | 0.854031 | 0.876023 | [0.04 0.96] | 0.788 |
-| (0.75, 53) | 0.0356267 | 0.753373 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.0208528 | 0.855828 | 0.87668 | [0.039 0.961] | 0.789 |
-| (0.75, 54) | 0.0441881 | 0.744812 | 0.789 | [0.04 0.21 0.001 0.749] | 0.0265353 | 0.850001 | 0.876536 | [0.041 0.959] | 0.789 |
-| (0.75, 55) | 0.0309762 | 0.749024 | 0.78 | [0.031 0.219 0.001 0.749] | 0.0178195 | 0.854125 | 0.871944 | [0.032 0.968] | 0.78 |
-| (0.75, 56) | 0.0161385 | 0.772862 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.00984521 | 0.866835 | 0.87668 | [0.039 0.961] | 0.789 |
-| (0.75, 57) | 0.0170935 | 0.761907 | 0.779 | [0.03 0.22 0.001 0.749] | 0.00916119 | 0.862276 | 0.871437 | [0.031 0.969] | 0.779 |
-| (0.75, 58) | 0.0354674 | 0.749533 | 0.785 | [0.036 0.214 0.001 0.749] | 0.0220898 | 0.852399 | 0.874489 | [0.037 0.963] | 0.785 |
-| (0.75, 59) | 0.025201 | 0.760799 | 0.786 | [0.036 0.214 0. 0.75 ] | 0.0151774 | 0.859968 | 0.875146 | [0.036 0.964] | 0.786 |
-| (0.75, 60) | 0.0272636 | 0.755736 | 0.783 | [0.033 0.217 0. 0.75 ] | 0.0156835 | 0.857933 | 0.873617 | [0.033 0.967] | 0.783 |
-| (0.75, 61) | 0.0433661 | 0.750634 | 0.794 | [0.045 0.205 0.001 0.749] | 0.0228797 | 0.856228 | 0.879108 | [0.046 0.954] | 0.794 |
-| (0.75, 62) | 0.0538387 | 0.737161 | 0.791 | [0.041 0.209 0. 0.75 ] | 0.0292089 | 0.848497 | 0.877706 | [0.041 0.959] | 0.791 |
-| (0.75, 63) | 0.0224127 | 0.764587 | 0.787 | [0.037 0.213 0. 0.75 ] | 0.0128879 | 0.862769 | 0.875657 | [0.037 0.963] | 0.787 |
-| (0.75, 64) | 0.034333 | 0.754667 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.0213609 | 0.855319 | 0.87668 | [0.039 0.961] | 0.789 |
-| (0.75, 65) | 0.00924564 | 0.775754 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.00490077 | 0.869735 | 0.874636 | [0.035 0.965] | 0.785 |
-| (0.75, 66) | 0.00451873 | 0.786481 | 0.791 | [0.041 0.209 0. 0.75 ] | 0.00214582 | 0.87556 | 0.877706 | [0.041 0.959] | 0.791 |
-| (0.75, 67) | 0.0517501 | 0.74025 | 0.792 | [0.044 0.206 0.002 0.748] | 0.028609 | 0.849325 | 0.877934 | [0.046 0.954] | 0.792 |
-| (0.75, 68) | 0.0343641 | 0.754636 | 0.789 | [0.04 0.21 0.001 0.749] | 0.0192369 | 0.857299 | 0.876536 | [0.041 0.959] | 0.789 |
-| (0.75, 69) | 0.0344314 | 0.750569 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.0205979 | 0.854038 | 0.874636 | [0.035 0.965] | 0.785 |
-| (0.75, 70) | 0.0261044 | 0.767896 | 0.794 | [0.045 0.205 0.001 0.749] | 0.0139256 | 0.865182 | 0.879108 | [0.046 0.954] | 0.794 |
-| (0.75, 71) | 0.0363507 | 0.753649 | 0.79 | [0.04 0.21 0. 0.75] | 0.0210632 | 0.85613 | 0.877193 | [0.04 0.96] | 0.79 |
-| (0.75, 72) | 0.0405785 | 0.741422 | 0.782 | [0.035 0.215 0.003 0.747] | 0.0217776 | 0.850886 | 0.872664 | [0.038 0.962] | 0.782 |
-| (0.75, 73) | 0.0170575 | 0.767942 | 0.785 | [0.036 0.214 0.001 0.749] | 0.00850885 | 0.86598 | 0.874489 | [0.037 0.963] | 0.785 |
-| (0.75, 74) | 0.0375071 | 0.750493 | 0.788 | [0.039 0.211 0.001 0.749] | 0.021137 | 0.854886 | 0.876023 | [0.04 0.96] | 0.788 |
-| (0.75, 75) | 0.0371426 | 0.748857 | 0.786 | [0.037 0.213 0.001 0.749] | 0.0210716 | 0.853928 | 0.875 | [0.038 0.962] | 0.786 |
-| (0.75, 76) | 0.0648981 | 0.724102 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.0374199 | 0.83926 | 0.87668 | [0.039 0.961] | 0.789 |
-| (0.75, 77) | 0.0389063 | 0.741094 | 0.78 | [0.031 0.219 0.001 0.749] | 0.0219382 | 0.850006 | 0.871944 | [0.032 0.968] | 0.78 |
-| (0.75, 78) | 0.046141 | 0.745859 | 0.792 | [0.042 0.208 0. 0.75 ] | 0.0284288 | 0.849791 | 0.87822 | [0.042 0.958] | 0.792 |
-| (0.75, 79) | 0.0459182 | 0.746082 | 0.792 | [0.042 0.208 0. 0.75 ] | 0.0254524 | 0.852768 | 0.87822 | [0.042 0.958] | 0.792 |
-| (0.75, 80) | 0.0367849 | 0.750215 | 0.787 | [0.039 0.211 0.002 0.748] | 0.0190088 | 0.856357 | 0.875366 | [0.041 0.959] | 0.787 |
-| (0.75, 81) | 0.0214734 | 0.769527 | 0.791 | [0.042 0.208 0.001 0.749] | 0.0109792 | 0.866584 | 0.877563 | [0.043 0.957] | 0.791 |
-| (0.75, 82) | 0.0606138 | 0.723386 | 0.784 | [0.034 0.216 0. 0.75 ] | 0.0346787 | 0.839447 | 0.874126 | [0.034 0.966] | 0.784 |
-| (0.75, 83) | 0.0179434 | 0.767057 | 0.785 | [0.036 0.214 0.001 0.749] | 0.00789914 | 0.86659 | 0.874489 | [0.037 0.963] | 0.785 |
-| (0.75, 84) | 0.0356262 | 0.747374 | 0.783 | [0.035 0.215 0.002 0.748] | 0.0210658 | 0.852256 | 0.873322 | [0.037 0.963] | 0.783 |
-| (0.75, 85) | 0.0263657 | 0.756634 | 0.783 | [0.034 0.216 0.001 0.749] | 0.0141479 | 0.859321 | 0.873469 | [0.035 0.965] | 0.783 |
-| (0.75, 86) | 0.0293021 | 0.743698 | 0.773 | [0.024 0.226 0.001 0.749] | 0.017352 | 0.851054 | 0.868406 | [0.025 0.975] | 0.773 |
-| (0.75, 87) | 0.026603 | 0.759397 | 0.786 | [0.036 0.214 0. 0.75 ] | 0.016022 | 0.859124 | 0.875146 | [0.036 0.964] | 0.786 |
-| (0.75, 88) | 0.0406937 | 0.747306 | 0.788 | [0.04 0.21 0.002 0.748] | 0.0228616 | 0.853017 | 0.875878 | [0.042 0.958] | 0.788 |
-| (0.75, 89) | 0.0458613 | 0.732139 | 0.778 | [0.028 0.222 0. 0.75 ] | 0.0270263 | 0.844054 | 0.87108 | [0.028 0.972] | 0.778 |
-| (0.75, 90) | 0.0341579 | 0.760842 | 0.795 | [0.045 0.205 0. 0.75 ] | 0.0208155 | 0.85895 | 0.879765 | [0.045 0.955] | 0.795 |
-| (0.75, 91) | 0.038191 | 0.760809 | 0.799 | [0.05 0.2 0.001 0.749] | 0.0213842 | 0.860311 | 0.881695 | [0.051 0.949] | 0.799 |
-| (0.75, 92) | 0.0372172 | 0.743783 | 0.781 | [0.031 0.219 0. 0.75 ] | 0.0198746 | 0.852726 | 0.8726 | [0.031 0.969] | 0.781 |
-| (0.75, 93) | 0.0567933 | 0.727207 | 0.784 | [0.036 0.214 0.002 0.748] | 0.0351011 | 0.838731 | 0.873832 | [0.038 0.962] | 0.784 |
-| (0.75, 94) | 0.0228502 | 0.76015 | 0.783 | [0.034 0.216 0.001 0.749] | 0.0115927 | 0.861877 | 0.873469 | [0.035 0.965] | 0.783 |
-| (0.75, 95) | 0.0450282 | 0.738972 | 0.784 | [0.034 0.216 0. 0.75 ] | 0.0242723 | 0.849854 | 0.874126 | [0.034 0.966] | 0.784 |
-| (0.75, 96) | 0.0540909 | 0.743909 | 0.798 | [0.048 0.202 0. 0.75 ] | 0.0295038 | 0.851812 | 0.881316 | [0.048 0.952] | 0.798 |
-| (0.75, 97) | 0.0563787 | 0.723621 | 0.78 | [0.03 0.22 0. 0.75] | 0.0350677 | 0.837025 | 0.872093 | [0.03 0.97] | 0.78 |
-| (0.75, 98) | 0.028261 | 0.766739 | 0.795 | [0.046 0.204 0.001 0.749] | 0.0140084 | 0.865616 | 0.879624 | [0.047 0.953] | 0.795 |
-| (0.75, 99) | 0.019607 | 0.776393 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0109948 | 0.869287 | 0.880282 | [0.046 0.954] | 0.796 |
-| (0.8, 0) | 0.0409423 | 0.793058 | 0.834 | [0.035 0.165 0.001 0.799] | 0.0217691 | 0.884127 | 0.905896 | [0.036 0.964] | 0.834 |
-| (0.8, 1) | 0.00912837 | 0.815872 | 0.825 | [0.026 0.174 0.001 0.799] | 0.0048623 | 0.896435 | 0.901297 | [0.027 0.973] | 0.825 |
-| (0.8, 2) | 0.0216766 | 0.806323 | 0.828 | [0.03 0.17 0.002 0.798] | 0.010707 | 0.892008 | 0.902715 | [0.032 0.968] | 0.828 |
-| (0.8, 3) | 0.00863246 | 0.816368 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.00504774 | 0.896361 | 0.901408 | [0.025 0.975] | 0.825 |
-| (0.8, 4) | 0.0276359 | 0.796364 | 0.824 | [0.025 0.175 0.001 0.799] | 0.0157953 | 0.884994 | 0.900789 | [0.026 0.974] | 0.824 |
-| (0.8, 5) | 0.00270277 | 0.815297 | 0.818 | [0.018 0.182 0. 0.8 ] | 0.00111215 | 0.896755 | 0.897868 | [0.018 0.982] | 0.818 |
-| (0.8, 6) | 0.0210912 | 0.800909 | 0.822 | [0.023 0.177 0.001 0.799] | 0.0116788 | 0.888096 | 0.899775 | [0.024 0.976] | 0.822 |
-| (0.8, 7) | 0.0458864 | 0.780114 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.0255575 | 0.876359 | 0.901917 | [0.026 0.974] | 0.826 |
-| (0.8, 8) | 0.0325411 | 0.799459 | 0.832 | [0.033 0.167 0.001 0.799] | 0.0179992 | 0.886871 | 0.90487 | [0.034 0.966] | 0.832 |
-| (0.8, 9) | 0.0374835 | 0.792517 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0210132 | 0.882942 | 0.903955 | [0.03 0.97] | 0.83 |
-| (0.8, 10) | 0.0330656 | 0.787934 | 0.821 | [0.022 0.178 0.001 0.799] | 0.0178779 | 0.88139 | 0.899268 | [0.023 0.977] | 0.821 |
-| (0.8, 11) | 0.005432 | 0.826568 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.00301292 | 0.901964 | 0.904977 | [0.032 0.968] | 0.832 |
-| (0.8, 12) | 0.00380289 | 0.822197 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.00202778 | 0.899889 | 0.901917 | [0.026 0.974] | 0.826 |
-| (0.8, 13) | 0.00720171 | 0.815798 | 0.823 | [0.023 0.177 0. 0.8 ] | 0.00305894 | 0.897335 | 0.900394 | [0.023 0.977] | 0.823 |
-| (0.8, 14) | 0.0172814 | 0.807719 | 0.825 | [0.027 0.173 0.002 0.798] | 0.00767473 | 0.893511 | 0.901186 | [0.029 0.971] | 0.825 |
-| (0.8, 15) | 0.0120847 | 0.816915 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.00646782 | 0.896977 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 16) | 0.0263668 | 0.792633 | 0.819 | [0.019 0.181 0. 0.8 ] | 0.0145246 | 0.883847 | 0.898372 | [0.019 0.981] | 0.819 |
-| (0.8, 17) | 0.032205 | 0.797795 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0186486 | 0.885306 | 0.903955 | [0.03 0.97] | 0.83 |
-| (0.8, 18) | 0.0364903 | 0.78451 | 0.821 | [0.023 0.177 0.002 0.798] | 0.0199892 | 0.879166 | 0.899155 | [0.025 0.975] | 0.821 |
-| (0.8, 19) | 0.0445238 | 0.794476 | 0.839 | [0.039 0.161 0. 0.8 ] | 0.025349 | 0.883226 | 0.908575 | [0.039 0.961] | 0.839 |
-| (0.8, 20) | 0.0180783 | 0.798922 | 0.817 | [0.017 0.183 0. 0.8 ] | 0.0101047 | 0.887259 | 0.897364 | [0.017 0.983] | 0.817 |
-| (0.8, 21) | 0.0245807 | 0.804419 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0148101 | 0.888634 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 22) | 0.0244787 | 0.804521 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0137768 | 0.889668 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 23) | 0.0193507 | 0.802649 | 0.822 | [0.022 0.178 0. 0.8 ] | 0.0108588 | 0.889029 | 0.899888 | [0.022 0.978] | 0.822 |
-| (0.8, 24) | 0.0354281 | 0.792572 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.019193 | 0.883741 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 25) | 0.021107 | 0.810893 | 0.832 | [0.033 0.167 0.001 0.799] | 0.0122716 | 0.892598 | 0.90487 | [0.034 0.966] | 0.832 |
-| (0.8, 26) | 0.0189653 | 0.809035 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.0110574 | 0.891877 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 27) | 0.0427835 | 0.783216 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.0234921 | 0.878424 | 0.901917 | [0.026 0.974] | 0.826 |
-| (0.8, 28) | 0.0388648 | 0.795135 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.0206372 | 0.885365 | 0.906002 | [0.034 0.966] | 0.834 |
-| (0.8, 29) | 0.0484156 | 0.780584 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0269235 | 0.876412 | 0.903335 | [0.031 0.969] | 0.829 |
-| (0.8, 30) | 0.0189334 | 0.809067 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.00894551 | 0.893989 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 31) | 0.0348533 | 0.795147 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0206885 | 0.883266 | 0.903955 | [0.03 0.97] | 0.83 |
-| (0.8, 32) | 0.0298236 | 0.797176 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0154133 | 0.887012 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 33) | 0.0308446 | 0.790155 | 0.821 | [0.021 0.179 0. 0.8 ] | 0.0177848 | 0.881597 | 0.899382 | [0.021 0.979] | 0.821 |
-| (0.8, 34) | 0.0173788 | 0.815621 | 0.833 | [0.035 0.165 0.002 0.798] | 0.00986453 | 0.895411 | 0.905275 | [0.037 0.963] | 0.833 |
-| (0.8, 35) | 0.0274772 | 0.797523 | 0.825 | [0.027 0.173 0.002 0.798] | 0.016222 | 0.884964 | 0.901186 | [0.029 0.971] | 0.825 |
-| (0.8, 36) | 0.00890272 | 0.823097 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.0056062 | 0.899371 | 0.904977 | [0.032 0.968] | 0.832 |
-| (0.8, 37) | 0.0382181 | 0.786782 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0212881 | 0.88012 | 0.901408 | [0.025 0.975] | 0.825 |
-| (0.8, 38) | 0.0243138 | 0.802686 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0120784 | 0.890347 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 39) | 0.0384636 | 0.792536 | 0.831 | [0.032 0.168 0.001 0.799] | 0.0225441 | 0.881814 | 0.904358 | [0.033 0.967] | 0.831 |
-| (0.8, 40) | 0.0253619 | 0.801638 | 0.827 | [0.028 0.172 0.001 0.799] | 0.0150565 | 0.887259 | 0.902315 | [0.029 0.971] | 0.827 |
-| (0.8, 41) | 0.000229561 | 0.82877 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.000929264 | 0.904374 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 42) | 0.0225886 | 0.807411 | 0.83 | [0.031 0.169 0.001 0.799] | 0.0118405 | 0.892006 | 0.903846 | [0.032 0.968] | 0.83 |
-| (0.8, 43) | 0.0194196 | 0.80858 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.00990255 | 0.893032 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 44) | 0.00644612 | 0.832554 | 0.839 | [0.04 0.16 0.001 0.799] | 0.00352805 | 0.904943 | 0.908471 | [0.041 0.959] | 0.839 |
-| (0.8, 45) | 0.0505133 | 0.779487 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0279151 | 0.87604 | 0.903955 | [0.03 0.97] | 0.83 |
-| (0.8, 46) | 0.0373503 | 0.79165 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.020021 | 0.883423 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 47) | 0.0360948 | 0.792905 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0211833 | 0.882152 | 0.903335 | [0.031 0.969] | 0.829 |
-| (0.8, 48) | 0.017169 | 0.817831 | 0.835 | [0.035 0.165 0. 0.8 ] | 0.00976995 | 0.896746 | 0.906516 | [0.035 0.965] | 0.835 |
-| (0.8, 49) | 0.0305348 | 0.803465 | 0.834 | [0.035 0.165 0.001 0.799] | 0.0180311 | 0.887865 | 0.905896 | [0.036 0.964] | 0.834 |
-| (0.8, 50) | 0.0293145 | 0.797686 | 0.827 | [0.029 0.171 0.002 0.798] | 0.0166065 | 0.885598 | 0.902205 | [0.031 0.969] | 0.827 |
-| (0.8, 51) | 0.0280583 | 0.802942 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0152134 | 0.889252 | 0.904466 | [0.031 0.969] | 0.831 |
-| (0.8, 52) | 0.0273535 | 0.798646 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.0140662 | 0.88785 | 0.901917 | [0.026 0.974] | 0.826 |
-| (0.8, 53) | 0.037029 | 0.794971 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.0200333 | 0.884944 | 0.904977 | [0.032 0.968] | 0.832 |
-| (0.8, 54) | 0.02648 | 0.79652 | 0.823 | [0.023 0.177 0. 0.8 ] | 0.0137327 | 0.886661 | 0.900394 | [0.023 0.977] | 0.823 |
-| (0.8, 55) | 0.0147235 | 0.812277 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.00601093 | 0.896414 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 56) | 0.0248399 | 0.81016 | 0.835 | [0.035 0.165 0. 0.8 ] | 0.0143239 | 0.892192 | 0.906516 | [0.035 0.965] | 0.835 |
-| (0.8, 57) | 0.0104378 | 0.837438 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.00708952 | 0.909515 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 58) | 0.0244922 | 0.799508 | 0.824 | [0.024 0.176 0. 0.8 ] | 0.0127094 | 0.888191 | 0.900901 | [0.024 0.976] | 0.824 |
-| (0.8, 59) | 0.0260415 | 0.800959 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0150998 | 0.887325 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 60) | 0.0267759 | 0.809224 | 0.836 | [0.036 0.164 0. 0.8 ] | 0.0160896 | 0.89094 | 0.907029 | [0.036 0.964] | 0.836 |
-| (0.8, 61) | 0.0225115 | 0.797488 | 0.82 | [0.021 0.179 0.001 0.799] | 0.0122826 | 0.88648 | 0.898763 | [0.022 0.978] | 0.82 |
-| (0.8, 62) | 0.0343597 | 0.79264 | 0.827 | [0.029 0.171 0.002 0.798] | 0.0190629 | 0.883142 | 0.902205 | [0.031 0.969] | 0.827 |
-| (0.8, 63) | 0.0159727 | 0.813027 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0089236 | 0.894521 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 64) | 0.0416964 | 0.791304 | 0.833 | [0.033 0.167 0. 0.8 ] | 0.0222044 | 0.883285 | 0.90549 | [0.033 0.967] | 0.833 |
-| (0.8, 65) | 0.0316177 | 0.796382 | 0.828 | [0.031 0.169 0.003 0.797] | 0.0189897 | 0.883615 | 0.902605 | [0.034 0.966] | 0.828 |
-| (0.8, 66) | 0.0404031 | 0.794597 | 0.835 | [0.035 0.165 0. 0.8 ] | 0.0213009 | 0.885215 | 0.906516 | [0.035 0.965] | 0.835 |
-| (0.8, 67) | 0.0437875 | 0.790213 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.0242558 | 0.881746 | 0.906002 | [0.034 0.966] | 0.834 |
-| (0.8, 68) | 0.0164454 | 0.817555 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.00894291 | 0.897059 | 0.906002 | [0.034 0.966] | 0.834 |
-| (0.8, 69) | 0.0331339 | 0.794866 | 0.828 | [0.029 0.171 0.001 0.799] | 0.0186214 | 0.884203 | 0.902825 | [0.03 0.97] | 0.828 |
-| (0.8, 70) | 0.0282686 | 0.803731 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.0170943 | 0.887883 | 0.904977 | [0.032 0.968] | 0.832 |
-| (0.8, 71) | 0.0266922 | 0.803308 | 0.83 | [0.031 0.169 0.001 0.799] | 0.0152941 | 0.888552 | 0.903846 | [0.032 0.968] | 0.83 |
-| (0.8, 72) | 0.0192176 | 0.805782 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0112241 | 0.890184 | 0.901408 | [0.025 0.975] | 0.825 |
-| (0.8, 73) | 0.0452923 | 0.778708 | 0.824 | [0.024 0.176 0. 0.8 ] | 0.0253478 | 0.875553 | 0.900901 | [0.024 0.976] | 0.824 |
-| (0.8, 74) | 0.0284065 | 0.800593 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0153539 | 0.887981 | 0.903335 | [0.031 0.969] | 0.829 |
-| (0.8, 75) | 0.019628 | 0.811372 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0115092 | 0.892957 | 0.904466 | [0.031 0.969] | 0.831 |
-| (0.8, 76) | 0.0254376 | 0.802562 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.0147003 | 0.888234 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 77) | 0.0274572 | 0.797543 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0140591 | 0.887349 | 0.901408 | [0.025 0.975] | 0.825 |
-| (0.8, 78) | 0.0268882 | 0.806112 | 0.833 | [0.035 0.165 0.002 0.798] | 0.0145238 | 0.890751 | 0.905275 | [0.037 0.963] | 0.833 |
-| (0.8, 79) | 0.0274169 | 0.803583 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0154312 | 0.889035 | 0.904466 | [0.031 0.969] | 0.831 |
-| (0.8, 80) | 0.0421947 | 0.792805 | 0.835 | [0.037 0.163 0.002 0.798] | 0.0234039 | 0.882899 | 0.906303 | [0.039 0.961] | 0.835 |
-| (0.8, 81) | 0.0341685 | 0.791831 | 0.826 | [0.029 0.171 0.003 0.797] | 0.0188428 | 0.882741 | 0.901584 | [0.032 0.968] | 0.826 |
-| (0.8, 82) | 0.0425206 | 0.791479 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.0250496 | 0.880953 | 0.906002 | [0.034 0.966] | 0.834 |
-| (0.8, 83) | 0.0240059 | 0.805994 | 0.83 | [0.031 0.169 0.001 0.799] | 0.0139455 | 0.889901 | 0.903846 | [0.032 0.968] | 0.83 |
-| (0.8, 84) | 0.0177441 | 0.804256 | 0.822 | [0.022 0.178 0. 0.8 ] | 0.00957679 | 0.890311 | 0.899888 | [0.022 0.978] | 0.822 |
-| (0.8, 85) | 0.00355815 | 0.829442 | 0.833 | [0.034 0.166 0.001 0.799] | 0.000679917 | 0.904703 | 0.905382 | [0.035 0.965] | 0.833 |
-| (0.8, 86) | 0.0074582 | 0.823542 | 0.831 | [0.032 0.168 0.001 0.799] | 0.00372776 | 0.90063 | 0.904358 | [0.033 0.967] | 0.831 |
-| (0.8, 87) | 0.0431926 | 0.785807 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0239931 | 0.879451 | 0.903444 | [0.029 0.971] | 0.829 |
-| (0.8, 88) | 0.0312967 | 0.793703 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0164912 | 0.884917 | 0.901408 | [0.025 0.975] | 0.825 |
-| (0.8, 89) | 0.0111373 | 0.815863 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.00594957 | 0.896476 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 90) | 0.0255766 | 0.802423 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.013677 | 0.889258 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 91) | 0.0221193 | 0.808881 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0110527 | 0.893413 | 0.904466 | [0.031 0.969] | 0.831 |
-| (0.8, 92) | 0.0231501 | 0.80585 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0134434 | 0.889892 | 0.903335 | [0.031 0.969] | 0.829 |
-| (0.8, 93) | 0.0233668 | 0.797633 | 0.821 | [0.021 0.179 0. 0.8 ] | 0.0137534 | 0.885628 | 0.899382 | [0.021 0.979] | 0.821 |
-| (0.8, 94) | 0.00688933 | 0.826111 | 0.833 | [0.034 0.166 0.001 0.799] | 0.0037811 | 0.901601 | 0.905382 | [0.035 0.965] | 0.833 |
-| (0.8, 95) | 0.0243997 | 0.8096 | 0.834 | [0.036 0.164 0.002 0.798] | 0.0114362 | 0.894353 | 0.905789 | [0.038 0.962] | 0.834 |
-| (0.8, 96) | 0.0228605 | 0.80514 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.0123032 | 0.890631 | 0.902935 | [0.028 0.972] | 0.828 |
-| (0.8, 97) | 0.0287869 | 0.797213 | 0.826 | [0.027 0.173 0.001 0.799] | 0.0146776 | 0.887128 | 0.901806 | [0.028 0.972] | 0.826 |
-| (0.8, 98) | 0.0243104 | 0.80269 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0133648 | 0.88906 | 0.902425 | [0.027 0.973] | 0.827 |
-| (0.8, 99) | 0.034638 | 0.793362 | 0.828 | [0.029 0.171 0.001 0.799] | 0.0180954 | 0.884729 | 0.902825 | [0.03 0.97] | 0.828 |
-| (0.85, 0) | 0.00916264 | 0.856837 | 0.866 | [0.017 0.133 0.001 0.849] | 0.00395676 | 0.922899 | 0.926856 | [0.018 0.982] | 0.866 |
-| (0.85, 1) | 0.0242384 | 0.842762 | 0.867 | [0.019 0.131 0.002 0.848] | 0.0126504 | 0.914632 | 0.927283 | [0.021 0.979] | 0.867 |
-| (0.85, 2) | 0.0059672 | 0.874967 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00366687 | 0.932043 | 0.928376 | [0.021 0.979] | 0.869 |
-| (0.85, 3) | 0.0185452 | 0.856455 | 0.875 | [0.025 0.125 0. 0.85 ] | 0.00887886 | 0.922628 | 0.931507 | [0.025 0.975] | 0.875 |
-| (0.85, 4) | 0.0223926 | 0.854607 | 0.877 | [0.027 0.123 0. 0.85 ] | 0.0109393 | 0.921589 | 0.932529 | [0.027 0.973] | 0.877 |
-| (0.85, 5) | 0.0275382 | 0.843462 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.0144402 | 0.915029 | 0.92947 | [0.021 0.979] | 0.871 |
-| (0.85, 6) | 0.0116306 | 0.864369 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0066333 | 0.925384 | 0.932018 | [0.026 0.974] | 0.876 |
-| (0.85, 7) | 0.0293276 | 0.839672 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0167791 | 0.911675 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 8) | 0.00853504 | 0.862465 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.00453054 | 0.924939 | 0.92947 | [0.021 0.979] | 0.871 |
-| (0.85, 9) | 0.00844529 | 0.877445 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00527631 | 0.933731 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 10) | 0.0174929 | 0.851507 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00949055 | 0.918886 | 0.928376 | [0.021 0.979] | 0.869 |
-| (0.85, 11) | 0.032037 | 0.834963 | 0.867 | [0.017 0.133 0. 0.85 ] | 0.0178529 | 0.909588 | 0.927441 | [0.017 0.983] | 0.867 |
-| (0.85, 12) | 0.02062 | 0.85538 | 0.876 | [0.027 0.123 0.001 0.849] | 0.0106596 | 0.921283 | 0.931943 | [0.028 0.972] | 0.876 |
-| (0.85, 13) | 0.0300872 | 0.839913 | 0.87 | [0.02 0.13 0. 0.85] | 0.0169147 | 0.912047 | 0.928962 | [0.02 0.98] | 0.87 |
-| (0.85, 14) | 0.0185164 | 0.847484 | 0.866 | [0.016 0.134 0. 0.85 ] | 0.0095133 | 0.917422 | 0.926936 | [0.016 0.984] | 0.866 |
-| (0.85, 15) | 0.00594455 | 0.867055 | 0.873 | [0.023 0.127 0. 0.85 ] | 0.00319687 | 0.92729 | 0.930487 | [0.023 0.977] | 0.873 |
-| (0.85, 16) | 0.0159766 | 0.858023 | 0.874 | [0.025 0.125 0.001 0.849] | 0.00772593 | 0.923195 | 0.930921 | [0.026 0.974] | 0.874 |
-| (0.85, 17) | 0.0102021 | 0.862798 | 0.873 | [0.024 0.126 0.001 0.849] | 0.00582044 | 0.924591 | 0.930411 | [0.025 0.975] | 0.873 |
-| (0.85, 18) | 0.0345923 | 0.835408 | 0.87 | [0.021 0.129 0.001 0.849] | 0.0201934 | 0.908691 | 0.928884 | [0.022 0.978] | 0.87 |
-| (0.85, 19) | 0.0164631 | 0.855537 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00789905 | 0.922079 | 0.929978 | [0.022 0.978] | 0.872 |
-| (0.85, 20) | 0.0369302 | 0.83707 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.0197393 | 0.911257 | 0.930997 | [0.024 0.976] | 0.874 |
-| (0.85, 21) | 0.0297006 | 0.844299 | 0.874 | [0.026 0.124 0.002 0.848] | 0.0157164 | 0.915129 | 0.930845 | [0.028 0.972] | 0.874 |
-| (0.85, 22) | 0.00637133 | 0.869629 | 0.876 | [0.027 0.123 0.001 0.849] | 0.00337797 | 0.928565 | 0.931943 | [0.028 0.972] | 0.876 |
-| (0.85, 23) | 0.0257953 | 0.836205 | 0.862 | [0.015 0.135 0.003 0.847] | 0.0138807 | 0.910792 | 0.924672 | [0.018 0.982] | 0.862 |
-| (0.85, 24) | 0.00337444 | 0.868626 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00166765 | 0.92831 | 0.929978 | [0.022 0.978] | 0.872 |
-| (0.85, 25) | 0.024588 | 0.851412 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0122872 | 0.91973 | 0.932018 | [0.026 0.974] | 0.876 |
-| (0.85, 26) | 0.0175407 | 0.853459 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00848404 | 0.920908 | 0.929392 | [0.023 0.977] | 0.871 |
-| (0.85, 27) | 0.0188113 | 0.853189 | 0.872 | [0.023 0.127 0.001 0.849] | 0.00993147 | 0.91997 | 0.929901 | [0.024 0.976] | 0.872 |
-| (0.85, 28) | 0.0102198 | 0.88022 | 0.87 | [0.021 0.129 0.001 0.849] | 0.0060185 | 0.934903 | 0.928884 | [0.022 0.978] | 0.87 |
-| (0.85, 29) | 0.0236431 | 0.844357 | 0.868 | [0.018 0.132 0. 0.85 ] | 0.0131277 | 0.91482 | 0.927948 | [0.018 0.982] | 0.868 |
-| (0.85, 30) | 0.0294663 | 0.840534 | 0.87 | [0.02 0.13 0. 0.85] | 0.0164557 | 0.912506 | 0.928962 | [0.02 0.98] | 0.87 |
-| (0.85, 31) | 0.0125447 | 0.858455 | 0.871 | [0.023 0.127 0.002 0.848] | 0.00581342 | 0.923502 | 0.929315 | [0.025 0.975] | 0.871 |
-| (0.85, 32) | 0.0168929 | 0.851107 | 0.868 | [0.018 0.132 0. 0.85 ] | 0.00838249 | 0.919565 | 0.927948 | [0.018 0.982] | 0.868 |
-| (0.85, 33) | 0.0416726 | 0.827327 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0237554 | 0.904699 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 34) | 0.00899809 | 0.860002 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00365011 | 0.924726 | 0.928376 | [0.021 0.979] | 0.869 |
-| (0.85, 35) | 0.012989 | 0.855011 | 0.868 | [0.02 0.13 0.002 0.848] | 0.00666622 | 0.921124 | 0.92779 | [0.022 0.978] | 0.868 |
-| (0.85, 36) | 0.0118965 | 0.859103 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00526969 | 0.924123 | 0.929392 | [0.023 0.977] | 0.871 |
-| (0.85, 37) | 0.0351497 | 0.83185 | 0.867 | [0.019 0.131 0.002 0.848] | 0.0192705 | 0.908012 | 0.927283 | [0.021 0.979] | 0.867 |
-| (0.85, 38) | 0.000781362 | 0.875781 | 0.875 | [0.025 0.125 0. 0.85 ] | 0.000880589 | 0.932387 | 0.931507 | [0.025 0.975] | 0.875 |
-| (0.85, 39) | 0.0148084 | 0.861192 | 0.876 | [0.028 0.122 0.002 0.848] | 0.00707788 | 0.92479 | 0.931868 | [0.03 0.97] | 0.876 |
-| (0.85, 40) | 0.033094 | 0.839906 | 0.873 | [0.024 0.126 0.001 0.849] | 0.0174848 | 0.912926 | 0.930411 | [0.025 0.975] | 0.873 |
-| (0.85, 41) | 0.00491038 | 0.87191 | 0.867 | [0.018 0.132 0.001 0.849] | 0.00317792 | 0.93054 | 0.927362 | [0.019 0.981] | 0.867 |
-| (0.85, 42) | 0.0118285 | 0.859172 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.00646193 | 0.923008 | 0.92947 | [0.021 0.979] | 0.871 |
-| (0.85, 43) | 0.0222668 | 0.853733 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0109554 | 0.921062 | 0.932018 | [0.026 0.974] | 0.876 |
-| (0.85, 44) | 0.0208303 | 0.85017 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.0116156 | 0.917854 | 0.92947 | [0.021 0.979] | 0.871 |
-| (0.85, 45) | 0.0232634 | 0.844737 | 0.868 | [0.018 0.132 0. 0.85 ] | 0.0132446 | 0.914703 | 0.927948 | [0.018 0.982] | 0.868 |
-| (0.85, 46) | 0.0286176 | 0.837382 | 0.866 | [0.018 0.132 0.002 0.848] | 0.0152861 | 0.91149 | 0.926776 | [0.02 0.98] | 0.866 |
-| (0.85, 47) | 0.0189883 | 0.848012 | 0.867 | [0.018 0.132 0.001 0.849] | 0.0098411 | 0.917521 | 0.927362 | [0.019 0.981] | 0.867 |
-| (0.85, 48) | 0.0291667 | 0.846833 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0162761 | 0.915741 | 0.932018 | [0.026 0.974] | 0.876 |
-| (0.85, 49) | 0.0139737 | 0.852026 | 0.866 | [0.017 0.133 0.001 0.849] | 0.00675732 | 0.920099 | 0.926856 | [0.018 0.982] | 0.866 |
-| (0.85, 50) | 0.028988 | 0.840012 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0155634 | 0.912891 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 51) | 0.019931 | 0.850069 | 0.87 | [0.021 0.129 0.001 0.849] | 0.0114954 | 0.917389 | 0.928884 | [0.022 0.978] | 0.87 |
-| (0.85, 52) | 0.0126395 | 0.86136 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.00694487 | 0.924052 | 0.930997 | [0.024 0.976] | 0.874 |
-| (0.85, 53) | 0.0174681 | 0.847532 | 0.865 | [0.016 0.134 0.001 0.849] | 0.00971912 | 0.916631 | 0.92635 | [0.017 0.983] | 0.865 |
-| (0.85, 54) | 0.000984246 | 0.871984 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00097317 | 0.930366 | 0.929392 | [0.023 0.977] | 0.871 |
-| (0.85, 55) | 0.00821199 | 0.860788 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00444453 | 0.92401 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 56) | 0.00862268 | 0.861377 | 0.87 | [0.02 0.13 0. 0.85] | 0.00347912 | 0.925483 | 0.928962 | [0.02 0.98] | 0.87 |
-| (0.85, 57) | 0.00934159 | 0.878342 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00568831 | 0.934143 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 58) | 0.0128164 | 0.857184 | 0.87 | [0.021 0.129 0.001 0.849] | 0.00699737 | 0.921887 | 0.928884 | [0.022 0.978] | 0.87 |
-| (0.85, 59) | 0.0331427 | 0.850857 | 0.884 | [0.034 0.116 0. 0.85 ] | 0.0172442 | 0.918879 | 0.936123 | [0.034 0.966] | 0.884 |
-| (0.85, 60) | 0.00682919 | 0.856171 | 0.863 | [0.013 0.137 0. 0.85 ] | 0.00356046 | 0.921861 | 0.925422 | [0.013 0.987] | 0.863 |
-| (0.85, 61) | 0.0141476 | 0.853852 | 0.868 | [0.019 0.131 0.001 0.849] | 0.00671517 | 0.921154 | 0.927869 | [0.02 0.98] | 0.868 |
-| (0.85, 62) | 0.0187097 | 0.85029 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0105429 | 0.917911 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 63) | 0.00948473 | 0.851515 | 0.861 | [0.013 0.137 0.002 0.848] | 0.00445686 | 0.919794 | 0.924251 | [0.015 0.985] | 0.861 |
-| (0.85, 64) | 0.0145757 | 0.854424 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00689778 | 0.921478 | 0.928376 | [0.021 0.979] | 0.869 |
-| (0.85, 65) | 0.00214502 | 0.869145 | 0.867 | [0.02 0.13 0.003 0.847] | 0.00168839 | 0.928891 | 0.927203 | [0.023 0.977] | 0.867 |
-| (0.85, 66) | 0.0170768 | 0.846923 | 0.864 | [0.014 0.136 0. 0.85 ] | 0.00957014 | 0.916356 | 0.925926 | [0.014 0.986] | 0.864 |
-| (0.85, 67) | 0.0227065 | 0.850294 | 0.873 | [0.026 0.124 0.003 0.847] | 0.0130022 | 0.917256 | 0.930258 | [0.029 0.971] | 0.873 |
-| (0.85, 68) | 0.0145889 | 0.860411 | 0.875 | [0.026 0.124 0.001 0.849] | 0.00836658 | 0.923065 | 0.931432 | [0.027 0.973] | 0.875 |
-| (0.85, 69) | 0.0364083 | 0.831592 | 0.868 | [0.02 0.13 0.002 0.848] | 0.019737 | 0.908053 | 0.92779 | [0.022 0.978] | 0.868 |
-| (0.85, 70) | 0.0242443 | 0.847756 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.0123723 | 0.917606 | 0.929978 | [0.022 0.978] | 0.872 |
-| (0.85, 71) | 0.00301728 | 0.867983 | 0.871 | [0.022 0.128 0.001 0.849] | 0.000460011 | 0.928932 | 0.929392 | [0.023 0.977] | 0.871 |
-| (0.85, 72) | 0.027528 | 0.846472 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.0146329 | 0.916364 | 0.930997 | [0.024 0.976] | 0.874 |
-| (0.85, 73) | 0.00503926 | 0.868961 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.00273599 | 0.928261 | 0.930997 | [0.024 0.976] | 0.874 |
-| (0.85, 74) | 0.00180717 | 0.867807 | 0.866 | [0.017 0.133 0.001 0.849] | 0.00122006 | 0.928076 | 0.926856 | [0.018 0.982] | 0.866 |
-| (0.85, 75) | 0.0113285 | 0.863672 | 0.875 | [0.029 0.121 0.004 0.846] | 0.00642303 | 0.924782 | 0.931205 | [0.033 0.967] | 0.875 |
-| (0.85, 76) | 0.0245245 | 0.853476 | 0.878 | [0.028 0.122 0. 0.85 ] | 0.0126659 | 0.920375 | 0.933041 | [0.028 0.972] | 0.878 |
-| (0.85, 77) | 0.0227488 | 0.846251 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0117367 | 0.916718 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 78) | 0.00669301 | 0.875693 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00422216 | 0.932677 | 0.928454 | [0.019 0.981] | 0.869 |
-| (0.85, 79) | 0.00956554 | 0.856434 | 0.866 | [0.016 0.134 0. 0.85 ] | 0.00474536 | 0.92219 | 0.926936 | [0.016 0.984] | 0.866 |
-| (0.85, 80) | 0.00108528 | 0.872915 | 0.874 | [0.025 0.125 0.001 0.849] | 0.000293925 | 0.930627 | 0.930921 | [0.026 0.974] | 0.874 |
-| (0.85, 81) | 0.0139251 | 0.857075 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00655939 | 0.922833 | 0.929392 | [0.023 0.977] | 0.871 |
-| (0.85, 82) | 0.0224209 | 0.851579 | 0.874 | [0.026 0.124 0.002 0.848] | 0.0118784 | 0.918967 | 0.930845 | [0.028 0.972] | 0.874 |
-| (0.85, 83) | 0.0234424 | 0.843558 | 0.867 | [0.017 0.133 0. 0.85 ] | 0.0127119 | 0.914729 | 0.927441 | [0.017 0.983] | 0.867 |
-| (0.85, 84) | 0.0127184 | 0.859282 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00659153 | 0.923387 | 0.929978 | [0.022 0.978] | 0.872 |
-| (0.85, 85) | 0.0139557 | 0.858044 | 0.872 | [0.023 0.127 0.001 0.849] | 0.0076882 | 0.922213 | 0.929901 | [0.024 0.976] | 0.872 |
-| (0.85, 86) | 0.00034068 | 0.870341 | 0.87 | [0.02 0.13 0. 0.85] | 0.001697 | 0.930659 | 0.928962 | [0.02 0.98] | 0.87 |
-| (0.85, 87) | 0.0113094 | 0.862691 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.00628484 | 0.924712 | 0.930997 | [0.024 0.976] | 0.874 |
-| (0.85, 88) | 0.0272791 | 0.838721 | 0.866 | [0.016 0.134 0. 0.85 ] | 0.015109 | 0.911827 | 0.926936 | [0.016 0.984] | 0.866 |
-| (0.85, 89) | 0.014482 | 0.892482 | 0.878 | [0.028 0.122 0. 0.85 ] | 0.00856509 | 0.941606 | 0.933041 | [0.028 0.972] | 0.878 |
-| (0.85, 90) | 0.0142999 | 0.8577 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00755693 | 0.922421 | 0.929978 | [0.022 0.978] | 0.872 |
-| (0.85, 91) | 0.0421117 | 0.827888 | 0.87 | [0.02 0.13 0. 0.85] | 0.0233165 | 0.905645 | 0.928962 | [0.02 0.98] | 0.87 |
-| (0.85, 92) | 0.0311295 | 0.84587 | 0.877 | [0.027 0.123 0. 0.85 ] | 0.0160312 | 0.916498 | 0.932529 | [0.027 0.973] | 0.877 |
-| (0.85, 93) | 0.0141491 | 0.848851 | 0.863 | [0.015 0.135 0.002 0.848] | 0.00791631 | 0.917343 | 0.925259 | [0.017 0.983] | 0.863 |
-| (0.85, 94) | 0.0200191 | 0.851981 | 0.872 | [0.024 0.126 0.002 0.848] | 0.0103975 | 0.919427 | 0.929825 | [0.026 0.974] | 0.872 |
-| (0.85, 95) | 0.0261024 | 0.844898 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.014257 | 0.915213 | 0.92947 | [0.021 0.979] | 0.871 |
-| (0.85, 96) | 0.0153376 | 0.855662 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.0082263 | 0.921243 | 0.92947 | [0.021 0.979] | 0.871 |
-| (0.85, 97) | 0.0226085 | 0.845392 | 0.868 | [0.019 0.131 0.001 0.849] | 0.0117309 | 0.916138 | 0.927869 | [0.02 0.98] | 0.868 |
-| (0.85, 98) | 0.0373645 | 0.833636 | 0.871 | [0.022 0.128 0.001 0.849] | 0.0202228 | 0.90917 | 0.929392 | [0.023 0.977] | 0.871 |
-| (0.85, 99) | 0.0195995 | 0.8574 | 0.877 | [0.027 0.123 0. 0.85 ] | 0.0100396 | 0.922489 | 0.932529 | [0.027 0.973] | 0.877 |
-| (0.9, 0) | 0.0301308 | 0.880869 | 0.911 | [0.012 0.088 0.001 0.899] | 0.0161845 | 0.936651 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 1) | 0.00656327 | 0.919563 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00410703 | 0.958002 | 0.953895 | [0.013 0.987] | 0.913 |
-| (0.9, 2) | 0.0144244 | 0.896576 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00736751 | 0.945468 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 3) | 0.0273018 | 0.891698 | 0.919 | [0.02 0.08 0.001 0.899] | 0.0150242 | 0.941868 | 0.956892 | [0.021 0.979] | 0.919 |
-| (0.9, 4) | 0.0168992 | 0.899101 | 0.916 | [0.016 0.084 0. 0.9 ] | 0.0085499 | 0.946864 | 0.955414 | [0.016 0.984] | 0.916 |
-| (0.9, 5) | 0.00223583 | 0.908764 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00063496 | 0.9522 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 6) | 0.00952175 | 0.904478 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00494578 | 0.949455 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 7) | 0.014533 | 0.899467 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.0074706 | 0.94693 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 8) | 0.01088 | 0.90212 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00584198 | 0.948053 | 0.953895 | [0.013 0.987] | 0.913 |
-| (0.9, 9) | 0.00749745 | 0.899503 | 0.907 | [0.008 0.092 0.001 0.899] | 0.00393881 | 0.946881 | 0.95082 | [0.009 0.991] | 0.907 |
-| (0.9, 10) | 0.0218657 | 0.890134 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.0115157 | 0.941874 | 0.95339 | [0.012 0.988] | 0.912 |
-| (0.9, 11) | 0.00199519 | 0.915005 | 0.917 | [0.018 0.082 0.001 0.899] | 0.0011787 | 0.954696 | 0.955875 | [0.019 0.981] | 0.917 |
-| (0.9, 12) | 0.00284903 | 0.924849 | 0.922 | [0.022 0.078 0. 0.9 ] | 0.00168534 | 0.960152 | 0.958466 | [0.022 0.978] | 0.922 |
-| (0.9, 13) | 0.00074074 | 0.910741 | 0.91 | [0.012 0.088 0.002 0.898] | 0.000999632 | 0.95328 | 0.95228 | [0.014 0.986] | 0.91 |
-| (0.9, 14) | 0.00416334 | 0.911837 | 0.916 | [0.016 0.084 0. 0.9 ] | 0.00221976 | 0.953194 | 0.955414 | [0.016 0.984] | 0.916 |
-| (0.9, 15) | 0.0169214 | 0.897079 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00901792 | 0.945383 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 16) | 0.0165161 | 0.900484 | 0.917 | [0.017 0.083 0. 0.9 ] | 0.00913514 | 0.946786 | 0.955921 | [0.017 0.983] | 0.917 |
-| (0.9, 17) | 0.00866541 | 0.909335 | 0.918 | [0.019 0.081 0.001 0.899] | 0.00399855 | 0.952384 | 0.956383 | [0.02 0.98] | 0.918 |
-| (0.9, 18) | 0.011116 | 0.929116 | 0.918 | [0.019 0.081 0.001 0.899] | 0.00686953 | 0.963253 | 0.956383 | [0.02 0.98] | 0.918 |
-| (0.9, 19) | 0.00628126 | 0.906719 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00329276 | 0.950602 | 0.953895 | [0.013 0.987] | 0.913 |
-| (0.9, 20) | 0.00487117 | 0.909129 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00222355 | 0.952129 | 0.954352 | [0.016 0.984] | 0.914 |
-| (0.9, 21) | 0.00958671 | 0.897413 | 0.907 | [0.008 0.092 0.001 0.899] | 0.0050069 | 0.945813 | 0.95082 | [0.009 0.991] | 0.907 |
-| (0.9, 22) | 0.00296476 | 0.912035 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00143269 | 0.953427 | 0.954859 | [0.017 0.983] | 0.915 |
-| (0.9, 23) | 0.00900789 | 0.907992 | 0.917 | [0.017 0.083 0. 0.9 ] | 0.00414382 | 0.951778 | 0.955921 | [0.017 0.983] | 0.917 |
-| (0.9, 24) | 0.00113461 | 0.924135 | 0.923 | [0.024 0.076 0.001 0.899] | 0.00144543 | 0.960379 | 0.958933 | [0.025 0.975] | 0.923 |
-| (0.9, 25) | 0.0173475 | 0.895653 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00891637 | 0.94493 | 0.953846 | [0.015 0.985] | 0.913 |
-| (0.9, 26) | 0.000654213 | 0.909346 | 0.91 | [0.011 0.089 0.001 0.899] | 0.000174876 | 0.952156 | 0.952331 | [0.012 0.988] | 0.91 |
-| (0.9, 27) | 0.00520818 | 0.908792 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00248187 | 0.951919 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 28) | 0.00428414 | 0.917284 | 0.913 | [0.015 0.085 0.002 0.898] | 0.00242611 | 0.956223 | 0.953797 | [0.017 0.983] | 0.913 |
-| (0.9, 29) | 0.00155474 | 0.922555 | 0.921 | [0.021 0.079 0. 0.9 ] | 0.00142622 | 0.959383 | 0.957956 | [0.021 0.979] | 0.921 |
-| (0.9, 30) | 0.015075 | 0.898925 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00843417 | 0.945918 | 0.954352 | [0.016 0.984] | 0.914 |
-| (0.9, 31) | 0.00664218 | 0.922642 | 0.916 | [0.017 0.083 0.001 0.899] | 0.00408139 | 0.959448 | 0.955367 | [0.018 0.982] | 0.916 |
-| (0.9, 32) | 0.00409654 | 0.908903 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00195499 | 0.951891 | 0.953846 | [0.015 0.985] | 0.913 |
-| (0.9, 33) | 0.0100621 | 0.903938 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00487939 | 0.949521 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 34) | 0.00666714 | 0.909333 | 0.916 | [0.018 0.082 0.002 0.898] | 0.00354481 | 0.951774 | 0.955319 | [0.02 0.98] | 0.916 |
-| (0.9, 35) | 0.00700774 | 0.904992 | 0.912 | [0.013 0.087 0.001 0.899] | 0.00362466 | 0.949716 | 0.95334 | [0.014 0.986] | 0.912 |
-| (0.9, 36) | 0.00340552 | 0.913594 | 0.917 | [0.017 0.083 0. 0.9 ] | 0.00179529 | 0.954126 | 0.955921 | [0.017 0.983] | 0.917 |
-| (0.9, 37) | 0.00453426 | 0.910466 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00190253 | 0.952957 | 0.954859 | [0.017 0.983] | 0.915 |
-| (0.9, 38) | 0.00414505 | 0.916145 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00284759 | 0.956237 | 0.95339 | [0.012 0.988] | 0.912 |
-| (0.9, 39) | 0.00205744 | 0.918943 | 0.921 | [0.021 0.079 0. 0.9 ] | 0.000530198 | 0.957426 | 0.957956 | [0.021 0.979] | 0.921 |
-| (0.9, 40) | 0.00382936 | 0.915171 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.00180558 | 0.955132 | 0.956938 | [0.019 0.981] | 0.919 |
-| (0.9, 41) | 0.00497108 | 0.904029 | 0.909 | [0.011 0.089 0.002 0.898] | 0.00217952 | 0.949596 | 0.951775 | [0.013 0.987] | 0.909 |
-| (0.9, 42) | 0.0112273 | 0.901773 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00593944 | 0.947956 | 0.953895 | [0.013 0.987] | 0.913 |
-| (0.9, 43) | 0.0170636 | 0.892936 | 0.91 | [0.01 0.09 0. 0.9 ] | 0.00909284 | 0.943288 | 0.952381 | [0.01 0.99] | 0.91 |
-| (0.9, 44) | 0.0162799 | 0.89772 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00884155 | 0.945511 | 0.954352 | [0.016 0.984] | 0.914 |
-| (0.9, 45) | 0.00426367 | 0.922264 | 0.918 | [0.018 0.082 0. 0.9 ] | 0.00234195 | 0.958771 | 0.956429 | [0.018 0.982] | 0.918 |
-| (0.9, 46) | 0.00151459 | 0.918485 | 0.92 | [0.02 0.08 0. 0.9 ] | 0.000635751 | 0.956811 | 0.957447 | [0.02 0.98] | 0.92 |
-| (0.9, 47) | 0.0134137 | 0.897586 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00688702 | 0.945948 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 48) | 0.0125112 | 0.902489 | 0.915 | [0.015 0.085 0. 0.9 ] | 0.00641199 | 0.948495 | 0.954907 | [0.015 0.985] | 0.915 |
-| (0.9, 49) | 0.00639305 | 0.914393 | 0.908 | [0.008 0.092 0. 0.9 ] | 0.00362208 | 0.954996 | 0.951374 | [0.008 0.992] | 0.908 |
-| (0.9, 50) | 0.00774922 | 0.906251 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.0041113 | 0.95029 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 51) | 0.0122481 | 0.898752 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00615901 | 0.946676 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 52) | 0.0058903 | 0.90511 | 0.911 | [0.011 0.089 0. 0.9 ] | 0.00296234 | 0.949923 | 0.952885 | [0.011 0.989] | 0.911 |
-| (0.9, 53) | 0.00697218 | 0.912028 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.0035033 | 0.953435 | 0.956938 | [0.019 0.981] | 0.919 |
-| (0.9, 54) | 0.00297486 | 0.912025 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00088718 | 0.953972 | 0.954859 | [0.017 0.983] | 0.915 |
-| (0.9, 55) | 0.0137413 | 0.898259 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00730465 | 0.946085 | 0.95339 | [0.012 0.988] | 0.912 |
-| (0.9, 56) | 0.0064383 | 0.918438 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00363441 | 0.957024 | 0.95339 | [0.012 0.988] | 0.912 |
-| (0.9, 57) | 0.00642233 | 0.902578 | 0.909 | [0.012 0.088 0.003 0.897] | 0.00295656 | 0.948768 | 0.951724 | [0.015 0.985] | 0.909 |
-| (0.9, 58) | 0.0107958 | 0.920796 | 0.91 | [0.011 0.089 0.001 0.899] | 0.00590905 | 0.95824 | 0.952331 | [0.012 0.988] | 0.91 |
-| (0.9, 59) | 0.000578272 | 0.908422 | 0.909 | [0.009 0.091 0. 0.9 ] | 0.000168299 | 0.951709 | 0.951877 | [0.009 0.991] | 0.909 |
-| (0.9, 60) | 0.0124924 | 0.906508 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.00642065 | 0.950517 | 0.956938 | [0.019 0.981] | 0.919 |
-| (0.9, 61) | 0.0155213 | 0.894479 | 0.91 | [0.012 0.088 0.002 0.898] | 0.00832079 | 0.943959 | 0.95228 | [0.014 0.986] | 0.91 |
-| (0.9, 62) | 0.0116735 | 0.899327 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00587826 | 0.946957 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 63) | 0.00207603 | 0.911924 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.0011058 | 0.953295 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 64) | 0.000689676 | 0.91331 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.000139088 | 0.954262 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 65) | 0.014441 | 0.900559 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00718125 | 0.947678 | 0.954859 | [0.017 0.983] | 0.915 |
-| (0.9, 66) | 0.0176499 | 0.89435 | 0.912 | [0.013 0.087 0.001 0.899] | 0.00954539 | 0.943795 | 0.95334 | [0.014 0.986] | 0.912 |
-| (0.9, 67) | 0.00501621 | 0.908984 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00243601 | 0.951965 | 0.954401 | [0.014 0.986] | 0.914 |
-| (0.9, 68) | 0.00606039 | 0.90894 | 0.915 | [0.015 0.085 0. 0.9 ] | 0.00265232 | 0.952255 | 0.954907 | [0.015 0.985] | 0.915 |
-| (0.9, 69) | 0.0197135 | 0.898286 | 0.918 | [0.021 0.079 0.003 0.897] | 0.0098805 | 0.946409 | 0.95629 | [0.024 0.976] | 0.918 |
-| (0.9, 70) | 0.0116814 | 0.900319 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00584883 | 0.947541 | 0.95339 | [0.012 0.988] | 0.912 |
-| (0.9, 71) | 0.00793232 | 0.899068 | 0.907 | [0.008 0.092 0.001 0.899] | 0.00400617 | 0.946813 | 0.95082 | [0.009 0.991] | 0.907 |
-| (0.9, 72) | 0.00787936 | 0.909121 | 0.917 | [0.018 0.082 0.001 0.899] | 0.00347757 | 0.952397 | 0.955875 | [0.019 0.981] | 0.917 |
-| (0.9, 73) | 0.0128338 | 0.901166 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00633845 | 0.948014 | 0.954352 | [0.016 0.984] | 0.914 |
-| (0.9, 74) | 0.000822019 | 0.912822 | 0.912 | [0.013 0.087 0.001 0.899] | 0.00056394 | 0.953904 | 0.95334 | [0.014 0.986] | 0.912 |
-| (0.9, 75) | 0.00670409 | 0.917704 | 0.911 | [0.011 0.089 0. 0.9 ] | 0.00386719 | 0.956752 | 0.952885 | [0.011 0.989] | 0.911 |
-| (0.9, 76) | 0.0180635 | 0.894936 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00958846 | 0.944258 | 0.953846 | [0.015 0.985] | 0.913 |
-| (0.9, 77) | 0.0148393 | 0.900161 | 0.915 | [0.017 0.083 0.002 0.898] | 0.00809086 | 0.94672 | 0.954811 | [0.019 0.981] | 0.915 |
-| (0.9, 78) | 0.00479696 | 0.903203 | 0.908 | [0.01 0.09 0.002 0.898] | 0.00213129 | 0.94914 | 0.951271 | [0.012 0.988] | 0.908 |
-| (0.9, 79) | 0.00734862 | 0.903651 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00346162 | 0.949374 | 0.952835 | [0.013 0.987] | 0.911 |
-| (0.9, 80) | 0.00871425 | 0.906286 | 0.915 | [0.015 0.085 0. 0.9 ] | 0.00469793 | 0.950209 | 0.954907 | [0.015 0.985] | 0.915 |
-| (0.9, 81) | 0.0288783 | 0.884122 | 0.913 | [0.014 0.086 0.001 0.899] | 0.0153488 | 0.938497 | 0.953846 | [0.015 0.985] | 0.913 |
-| (0.9, 82) | 0.00636029 | 0.90364 | 0.91 | [0.011 0.089 0.001 0.899] | 0.00336515 | 0.948965 | 0.952331 | [0.012 0.988] | 0.91 |
-| (0.9, 83) | 0.0398032 | 0.876197 | 0.916 | [0.016 0.084 0. 0.9 ] | 0.0216551 | 0.933759 | 0.955414 | [0.016 0.984] | 0.916 |
-| (0.9, 84) | 0.00975212 | 0.903248 | 0.913 | [0.015 0.085 0.002 0.898] | 0.00525826 | 0.948539 | 0.953797 | [0.017 0.983] | 0.913 |
-| (0.9, 85) | 0.00793273 | 0.920933 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00455126 | 0.958397 | 0.953846 | [0.015 0.985] | 0.913 |
-| (0.9, 86) | 0.0174908 | 0.886509 | 0.904 | [0.006 0.094 0.002 0.898] | 0.00949516 | 0.939765 | 0.94926 | [0.008 0.992] | 0.904 |
-| (0.9, 87) | 0.0180295 | 0.893971 | 0.912 | [0.014 0.086 0.002 0.898] | 0.00968631 | 0.943605 | 0.953291 | [0.016 0.984] | 0.912 |
-| (0.9, 88) | 0.00443638 | 0.909564 | 0.914 | [0.017 0.083 0.003 0.897] | 0.00168449 | 0.952571 | 0.954255 | [0.02 0.98] | 0.914 |
-| (0.9, 89) | 0.0109881 | 0.907012 | 0.918 | [0.019 0.081 0.001 0.899] | 0.00541001 | 0.950973 | 0.956383 | [0.02 0.98] | 0.918 |
-| (0.9, 90) | 0.00504521 | 0.910045 | 0.905 | [0.006 0.094 0.001 0.899] | 0.00289806 | 0.952713 | 0.949815 | [0.007 0.993] | 0.905 |
-| (0.9, 91) | 0.00880224 | 0.910198 | 0.919 | [0.02 0.08 0.001 0.899] | 0.00480602 | 0.952086 | 0.956892 | [0.021 0.979] | 0.919 |
-| (0.9, 92) | 0.00684515 | 0.916155 | 0.923 | [0.023 0.077 0. 0.9 ] | 0.00299495 | 0.955982 | 0.958977 | [0.023 0.977] | 0.923 |
-| (0.9, 93) | 0.00277936 | 0.916221 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.00155942 | 0.955378 | 0.956938 | [0.019 0.981] | 0.919 |
-| (0.9, 94) | 0.00155124 | 0.907449 | 0.909 | [0.009 0.091 0. 0.9 ] | 0.000742878 | 0.951134 | 0.951877 | [0.009 0.991] | 0.909 |
-| (0.9, 95) | 0.0102061 | 0.926206 | 0.916 | [0.017 0.083 0.001 0.899] | 0.00570406 | 0.961071 | 0.955367 | [0.018 0.982] | 0.916 |
-| (0.9, 96) | 0.00659766 | 0.923598 | 0.917 | [0.018 0.082 0.001 0.899] | 0.0037311 | 0.959606 | 0.955875 | [0.019 0.981] | 0.917 |
-| (0.9, 97) | 0.0133374 | 0.903663 | 0.917 | [0.018 0.082 0.001 0.899] | 0.00714786 | 0.948727 | 0.955875 | [0.019 0.981] | 0.917 |
-| (0.9, 98) | 0.0268155 | 0.890185 | 0.917 | [0.019 0.081 0.002 0.898] | 0.0139259 | 0.941902 | 0.955828 | [0.021 0.979] | 0.917 |
-| (0.9, 99) | 0.0100532 | 0.893947 | 0.904 | [0.006 0.094 0.002 0.898] | 0.00525952 | 0.944001 | 0.94926 | [0.008 0.992] | 0.904 |
-| (0.95, 0) | 0.0130864 | 0.969086 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00681747 | 0.98416 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 1) | 0.0112369 | 0.945763 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00590501 | 0.971941 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 2) | 0.000913955 | 0.959086 | 0.96 | [0.01 0.04 0. 0.95] | 0.000476725 | 0.978905 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 3) | 0.00282916 | 0.957829 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00161856 | 0.978458 | 0.97684 | [0.007 0.993] | 0.955 |
-| (0.95, 4) | 0.00252074 | 0.956479 | 0.959 | [0.01 0.04 0.001 0.949] | 0.00124336 | 0.977612 | 0.978855 | [0.011 0.989] | 0.959 |
-| (0.95, 5) | 0.00253113 | 0.957469 | 0.96 | [0.01 0.04 0. 0.95] | 0.00138245 | 0.977999 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 6) | 0.00451495 | 0.951485 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00222678 | 0.975139 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 7) | 0.00417619 | 0.955824 | 0.96 | [0.01 0.04 0. 0.95] | 0.00218906 | 0.977192 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 8) | 0.00512566 | 0.950874 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00255172 | 0.974815 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 9) | 0.00543415 | 0.946566 | 0.952 | [0.005 0.045 0.003 0.947] | 0.00273372 | 0.972549 | 0.975283 | [0.008 0.992] | 0.952 |
-| (0.95, 10) | 0.00479567 | 0.960796 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00253629 | 0.979879 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 11) | 0.0059848 | 0.953015 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00308922 | 0.975788 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 12) | 0.0142771 | 0.971277 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00746109 | 0.98533 | 0.977869 | [0.007 0.993] | 0.957 |
-| (0.95, 13) | 0.00276339 | 0.956237 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00140162 | 0.977475 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 14) | 0.00478025 | 0.95022 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00252338 | 0.974317 | 0.97684 | [0.007 0.993] | 0.955 |
-| (0.95, 15) | 0.0046799 | 0.94932 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00238639 | 0.973951 | 0.976337 | [0.006 0.994] | 0.954 |
-| (0.95, 16) | 0.00442474 | 0.955425 | 0.951 | [0.003 0.047 0.002 0.948] | 0.00232928 | 0.977136 | 0.974807 | [0.005 0.995] | 0.951 |
-| (0.95, 17) | 0.0114726 | 0.945527 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00597459 | 0.971872 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 18) | 0.00567983 | 0.95132 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00293726 | 0.974909 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 19) | 0.0147145 | 0.939286 | 0.954 | [0.004 0.046 0. 0.95 ] | 0.0076719 | 0.96869 | 0.976362 | [0.004 0.996] | 0.954 |
-| (0.95, 20) | 0.0086796 | 0.94732 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00446135 | 0.972905 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 21) | 0.00869415 | 0.951306 | 0.96 | [0.011 0.039 0.001 0.949] | 0.00446133 | 0.974899 | 0.97936 | [0.012 0.988] | 0.96 |
-| (0.95, 22) | 0.00115897 | 0.956159 | 0.955 | [0.005 0.045 0. 0.95 ] | 0.000685432 | 0.977549 | 0.976864 | [0.005 0.995] | 0.955 |
-| (0.95, 23) | 0.0135314 | 0.950469 | 0.964 | [0.014 0.036 0. 0.95 ] | 0.00711114 | 0.974294 | 0.981405 | [0.014 0.986] | 0.964 |
-| (0.95, 24) | 0.000263541 | 0.955736 | 0.956 | [0.007 0.043 0.001 0.949] | 2.1201e-05 | 0.977364 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 25) | 0.0147964 | 0.942204 | 0.957 | [0.01 0.04 0.003 0.947] | 0.00755989 | 0.970241 | 0.977801 | [0.013 0.987] | 0.957 |
-| (0.95, 26) | 0.00568312 | 0.951317 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00294096 | 0.974928 | 0.977869 | [0.007 0.993] | 0.957 |
-| (0.95, 27) | 0.00402375 | 0.954976 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00190956 | 0.976967 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 28) | 0.00112943 | 0.957129 | 0.956 | [0.008 0.042 0.002 0.948] | 0.000543759 | 0.977863 | 0.97732 | [0.01 0.99] | 0.956 |
-| (0.95, 29) | 0.0129274 | 0.950073 | 0.963 | [0.014 0.036 0.001 0.949] | 0.00676198 | 0.974117 | 0.980879 | [0.015 0.985] | 0.963 |
-| (0.95, 30) | 0.00401177 | 0.962012 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00225901 | 0.980632 | 0.978373 | [0.008 0.992] | 0.958 |
-| (0.95, 31) | 0.0084593 | 0.948541 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00432719 | 0.973519 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 32) | 0.00247352 | 0.959474 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00135301 | 0.979199 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 33) | 0.00287278 | 0.957127 | 0.96 | [0.01 0.04 0. 0.95] | 0.00148084 | 0.977901 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 34) | 0.00586271 | 0.951137 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00297376 | 0.974896 | 0.977869 | [0.007 0.993] | 0.957 |
-| (0.95, 35) | 0.00212307 | 0.953877 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00111809 | 0.976225 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 36) | 0.00105894 | 0.961059 | 0.96 | [0.01 0.04 0. 0.95] | 0.000574108 | 0.979956 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 37) | 0.0105679 | 0.943432 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00545768 | 0.97088 | 0.976337 | [0.006 0.994] | 0.954 |
-| (0.95, 38) | 0.005027 | 0.963027 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00259891 | 0.980972 | 0.978373 | [0.008 0.992] | 0.958 |
-| (0.95, 39) | 0.00677662 | 0.950223 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00342102 | 0.974448 | 0.977869 | [0.007 0.993] | 0.957 |
-| (0.95, 40) | 0.0132115 | 0.968212 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00686927 | 0.983709 | 0.97684 | [0.007 0.993] | 0.955 |
-| (0.95, 41) | 0.012049 | 0.944951 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00625242 | 0.971594 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 42) | 0.00143589 | 0.960436 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.000937985 | 0.979815 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 43) | 0.00898241 | 0.952018 | 0.961 | [0.011 0.039 0. 0.95 ] | 0.00471306 | 0.975173 | 0.979887 | [0.011 0.989] | 0.961 |
-| (0.95, 44) | 0.00919265 | 0.947807 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00470138 | 0.973168 | 0.977869 | [0.007 0.993] | 0.957 |
-| (0.95, 45) | 0.00175008 | 0.95325 | 0.955 | [0.01 0.04 0.005 0.945] | 0.000737709 | 0.976006 | 0.976744 | [0.015 0.985] | 0.955 |
-| (0.95, 46) | 0.00710272 | 0.958103 | 0.951 | [0.005 0.045 0.004 0.946] | 0.00365538 | 0.978411 | 0.974755 | [0.009 0.991] | 0.951 |
-| (0.95, 47) | 0.00418356 | 0.955816 | 0.96 | [0.01 0.04 0. 0.95] | 0.00214877 | 0.977233 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 48) | 0.00453778 | 0.960538 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.0023711 | 0.979737 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 49) | 0.0149231 | 0.972923 | 0.958 | [0.009 0.041 0.001 0.949] | 0.00778307 | 0.986134 | 0.978351 | [0.01 0.99] | 0.958 |
-| (0.95, 50) | 7.40124e-05 | 0.954926 | 0.955 | [0.005 0.045 0. 0.95 ] | 7.84744e-05 | 0.976942 | 0.976864 | [0.005 0.995] | 0.955 |
-| (0.95, 51) | 0.003751 | 0.955751 | 0.952 | [0.002 0.048 0. 0.95 ] | 0.00201513 | 0.977374 | 0.975359 | [0.002 0.998] | 0.952 |
-| (0.95, 52) | 0.00456641 | 0.947434 | 0.952 | [0.005 0.045 0.003 0.947] | 0.00227595 | 0.973007 | 0.975283 | [0.008 0.992] | 0.952 |
-| (0.95, 53) | 0.00276139 | 0.955239 | 0.958 | [0.009 0.041 0.001 0.949] | 0.00132328 | 0.977027 | 0.978351 | [0.01 0.99] | 0.958 |
-| (0.95, 54) | 0.0164937 | 0.941506 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00857274 | 0.9698 | 0.978373 | [0.008 0.992] | 0.958 |
-| (0.95, 55) | 0.00856963 | 0.94243 | 0.951 | [0.002 0.048 0.001 0.949] | 0.00451159 | 0.970321 | 0.974833 | [0.003 0.997] | 0.951 |
-| (0.95, 56) | 0.00327117 | 0.958271 | 0.955 | [0.005 0.045 0. 0.95 ] | 0.00173844 | 0.978602 | 0.976864 | [0.005 0.995] | 0.955 |
-| (0.95, 57) | 0.007871 | 0.944129 | 0.952 | [0.002 0.048 0. 0.95 ] | 0.00409843 | 0.971261 | 0.975359 | [0.002 0.998] | 0.952 |
-| (0.95, 58) | 0.000601234 | 0.956601 | 0.956 | [0.008 0.042 0.002 0.948] | 0.000499576 | 0.977819 | 0.97732 | [0.01 0.99] | 0.956 |
-| (0.95, 59) | 0.0032114 | 0.959211 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00173182 | 0.979075 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 60) | 0.0155299 | 0.93947 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00804949 | 0.96879 | 0.97684 | [0.007 0.993] | 0.955 |
-| (0.95, 61) | 0.0318797 | 0.92512 | 0.957 | [0.009 0.041 0.002 0.948] | 0.0168799 | 0.960944 | 0.977824 | [0.011 0.989] | 0.957 |
-| (0.95, 62) | 0.00587987 | 0.96288 | 0.957 | [0.009 0.041 0.002 0.948] | 0.0030603 | 0.980884 | 0.977824 | [0.011 0.989] | 0.957 |
-| (0.95, 63) | 0.00842203 | 0.947578 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00443652 | 0.97293 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 64) | 0.00752341 | 0.967523 | 0.96 | [0.01 0.04 0. 0.95] | 0.00394008 | 0.983322 | 0.979381 | [0.01 0.99] | 0.96 |
-| (0.95, 65) | 0.000204061 | 0.950204 | 0.95 | [0.005 0.045 0.005 0.945] | 0.000158767 | 0.974386 | 0.974227 | [0.01 0.99] | 0.95 |
-| (0.95, 66) | 0.0121659 | 0.945834 | 0.958 | [0.01 0.04 0.002 0.948] | 0.00618715 | 0.972141 | 0.978328 | [0.012 0.988] | 0.958 |
-| (0.95, 67) | 0.00567601 | 0.952324 | 0.958 | [0.009 0.041 0.001 0.949] | 0.00277065 | 0.97558 | 0.978351 | [0.01 0.99] | 0.958 |
-| (0.95, 68) | 0.000954144 | 0.958046 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.000375038 | 0.978502 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 69) | 0.00060172 | 0.957398 | 0.958 | [0.009 0.041 0.001 0.949] | 0.000289562 | 0.978061 | 0.978351 | [0.01 0.99] | 0.958 |
-| (0.95, 70) | 0.00426978 | 0.96327 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00227676 | 0.981154 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 71) | 0.019713 | 0.937287 | 0.957 | [0.009 0.041 0.002 0.948] | 0.0104357 | 0.967388 | 0.977824 | [0.011 0.989] | 0.957 |
-| (0.95, 72) | 0.00756189 | 0.949438 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00387345 | 0.973973 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 73) | 0.00469595 | 0.951304 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00241727 | 0.974926 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 74) | 0.00317693 | 0.956177 | 0.953 | [0.005 0.045 0.002 0.948] | 0.00168466 | 0.977495 | 0.975811 | [0.007 0.993] | 0.953 |
-| (0.95, 75) | 0.00994606 | 0.968946 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.0053118 | 0.984189 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 76) | 0.00516192 | 0.959162 | 0.954 | [0.006 0.044 0.002 0.948] | 0.00269651 | 0.97901 | 0.976313 | [0.008 0.992] | 0.954 |
-| (0.95, 77) | 0.000941681 | 0.955058 | 0.956 | [0.007 0.043 0.001 0.949] | 0.000330332 | 0.977013 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 78) | 0.0185866 | 0.980587 | 0.962 | [0.014 0.036 0.002 0.948] | 0.00965988 | 0.990011 | 0.980352 | [0.016 0.984] | 0.962 |
-| (0.95, 79) | 0.00133473 | 0.959335 | 0.958 | [0.009 0.041 0.001 0.949] | 0.000654896 | 0.979005 | 0.978351 | [0.01 0.99] | 0.958 |
-| (0.95, 80) | 0.00956923 | 0.944431 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00491612 | 0.971421 | 0.976337 | [0.006 0.994] | 0.954 |
-| (0.95, 81) | 0.00636464 | 0.950635 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00326916 | 0.974577 | 0.977846 | [0.009 0.991] | 0.957 |
-| (0.95, 82) | 0.000789837 | 0.95721 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00023548 | 0.978137 | 0.978373 | [0.008 0.992] | 0.958 |
-| (0.95, 83) | 0.0029409 | 0.961941 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00171311 | 0.98059 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 84) | 0.00884236 | 0.946158 | 0.955 | [0.005 0.045 0. 0.95 ] | 0.00453154 | 0.972332 | 0.976864 | [0.005 0.995] | 0.955 |
-| (0.95, 85) | 0.000941489 | 0.958941 | 0.958 | [0.01 0.04 0.002 0.948] | 0.000520676 | 0.978849 | 0.978328 | [0.012 0.988] | 0.958 |
-| (0.95, 86) | 0.0140395 | 0.93996 | 0.954 | [0.006 0.044 0.002 0.948] | 0.00744394 | 0.968869 | 0.976313 | [0.008 0.992] | 0.954 |
-| (0.95, 87) | 0.00377863 | 0.961779 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00200204 | 0.980375 | 0.978373 | [0.008 0.992] | 0.958 |
-| (0.95, 88) | 0.000211864 | 0.959212 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.000207292 | 0.979084 | 0.978877 | [0.009 0.991] | 0.959 |
-| (0.95, 89) | 0.0037105 | 0.952289 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00180449 | 0.975562 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 90) | 0.000369451 | 0.955631 | 0.956 | [0.006 0.044 0. 0.95 ] | 5.4309e-05 | 0.977312 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 91) | 0.00221093 | 0.958211 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00129289 | 0.978659 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 92) | 0.00325314 | 0.958253 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00182254 | 0.978662 | 0.97684 | [0.007 0.993] | 0.955 |
-| (0.95, 93) | 0.0021091 | 0.959109 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.0011343 | 0.979004 | 0.977869 | [0.007 0.993] | 0.957 |
-| (0.95, 94) | 0.0031392 | 0.952861 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00151907 | 0.975847 | 0.977366 | [0.006 0.994] | 0.956 |
-| (0.95, 95) | 0.0117605 | 0.965761 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00613714 | 0.982475 | 0.976337 | [0.006 0.994] | 0.954 |
-| (0.95, 96) | 0.0128302 | 0.94117 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00671104 | 0.969626 | 0.976337 | [0.006 0.994] | 0.954 |
-| (0.95, 97) | 0.00541577 | 0.955584 | 0.961 | [0.011 0.039 0. 0.95 ] | 0.00261709 | 0.977269 | 0.979887 | [0.011 0.989] | 0.961 |
-| (0.95, 98) | 0.0028626 | 0.953137 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00149962 | 0.975843 | 0.977343 | [0.008 0.992] | 0.956 |
-| (0.95, 99) | 0.00686275 | 0.949137 | 0.956 | [0.007 0.043 0.001 0.949] | 0.0035354 | 0.973808 | 0.977343 | [0.008 0.992] | 0.956 |
-| (1.0, 0) | 0.00038766 | 0.999612 | 1 | [0. 0. 0. 1.] | 0.000193868 | 0.999806 | 1 | [0. 1.] | 1 |
-| (1.0, 1) | 0.000768513 | 0.997231 | 0.998 | [0. 0. 0.002 0.998] | 0.000387314 | 0.998612 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 2) | 0.0110783 | 0.985922 | 0.997 | [0. 0. 0.003 0.997] | 0.00558684 | 0.992911 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 3) | 0.00656081 | 0.990439 | 0.997 | [0. 0. 0.003 0.997] | 0.00330234 | 0.995195 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 4) | 0.00261978 | 0.99538 | 0.998 | [0. 0. 0.002 0.998] | 0.00131429 | 0.997685 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 5) | 0.00163194 | 0.998368 | 1 | [0. 0. 0. 1.] | 0.000816636 | 0.999183 | 1 | [0. 1.] | 1 |
-| (1.0, 6) | 0.00407542 | 0.995925 | 1 | [0. 0. 0. 1.] | 0.00204187 | 0.997958 | 1 | [0. 1.] | 1 |
-| (1.0, 7) | 0.010548 | 0.987452 | 0.998 | [0. 0. 0.002 0.998] | 0.0053126 | 0.993686 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 8) | 0.00242359 | 0.996576 | 0.999 | [0. 0. 0.001 0.999] | 0.00121665 | 0.998283 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 9) | 0.00321056 | 0.995789 | 0.999 | [0. 0. 0.001 0.999] | 0.00160947 | 0.99789 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 10) | 0.00323781 | 0.996762 | 1 | [0. 0. 0. 1.] | 0.00162153 | 0.998378 | 1 | [0. 1.] | 1 |
-| (1.0, 11) | 0.000783789 | 0.999216 | 1 | [0. 0. 0. 1.] | 0.000392048 | 0.999608 | 1 | [0. 1.] | 1 |
-| (1.0, 12) | 0.00695127 | 0.993049 | 1 | [0. 0. 0. 1.] | 0.00348776 | 0.996512 | 1 | [0. 1.] | 1 |
-| (1.0, 13) | 0.00228645 | 0.995714 | 0.998 | [0. 0. 0.002 0.998] | 0.00114683 | 0.997852 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 14) | 0.0112308 | 0.988769 | 1 | [0. 0. 0. 1.] | 0.00564713 | 0.994353 | 1 | [0. 1.] | 1 |
-| (1.0, 15) | 0.012585 | 0.984415 | 0.997 | [0. 0. 0.003 0.997] | 0.00635148 | 0.992146 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 16) | 0.00115313 | 0.998847 | 1 | [0. 0. 0. 1.] | 0.000576897 | 0.999423 | 1 | [0. 1.] | 1 |
-| (1.0, 17) | 0.00564588 | 0.993354 | 0.999 | [0. 0. 0.001 0.999] | 0.00283377 | 0.996666 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 18) | 0.00350382 | 0.995496 | 0.999 | [0. 0. 0.001 0.999] | 0.00175679 | 0.997743 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 19) | 0.00979927 | 0.990201 | 1 | [0. 0. 0. 1.] | 0.00492376 | 0.995076 | 1 | [0. 1.] | 1 |
-| (1.0, 20) | 0.00602819 | 0.991972 | 0.998 | [0. 0. 0.002 0.998] | 0.00302928 | 0.99597 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 21) | 0.00330174 | 0.995698 | 0.999 | [0. 0. 0.001 0.999] | 0.00165551 | 0.997844 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 22) | 0.00237333 | 0.996627 | 0.999 | [0. 0. 0.001 0.999] | 0.00118927 | 0.99831 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 23) | 0.00497561 | 0.994024 | 0.999 | [0. 0. 0.001 0.999] | 0.00249651 | 0.997003 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 24) | 0.0045159 | 0.995484 | 1 | [0. 0. 0. 1.] | 0.00226306 | 0.997737 | 1 | [0. 1.] | 1 |
-| (1.0, 25) | 0.00159816 | 0.999598 | 0.998 | [0. 0. 0.002 0.998] | 0.000799555 | 0.999799 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 26) | 0.00282877 | 0.996171 | 0.999 | [0. 0. 0.001 0.999] | 0.00142084 | 0.998079 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 27) | 0.0055852 | 0.992415 | 0.998 | [0. 0. 0.002 0.998] | 0.00280651 | 0.996192 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 28) | 0.00522598 | 0.994774 | 1 | [0. 0. 0. 1.] | 0.00261984 | 0.99738 | 1 | [0. 1.] | 1 |
-| (1.0, 29) | 0.00351762 | 0.995482 | 0.999 | [0. 0. 0.001 0.999] | 0.00176397 | 0.997736 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 30) | 0.00530586 | 0.993694 | 0.999 | [0. 0. 0.001 0.999] | 0.00266265 | 0.996837 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 31) | 3.04145e-05 | 0.99897 | 0.999 | [0. 0. 0.001 0.999] | 1.59575e-05 | 0.999484 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 32) | 0.00892355 | 0.990076 | 0.999 | [0. 0. 0.001 0.999] | 0.00448628 | 0.995013 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 33) | 0.00909471 | 0.990905 | 1 | [0. 0. 0. 1.] | 0.00456814 | 0.995432 | 1 | [0. 1.] | 1 |
-| (1.0, 34) | 0.00174823 | 0.997252 | 0.999 | [0. 0. 0.001 0.999] | 0.000876536 | 0.998623 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 35) | 0.00144624 | 0.996554 | 0.998 | [0. 0. 0.002 0.998] | 0.000725097 | 0.998274 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 36) | 0.0104275 | 0.989573 | 1 | [0. 0. 0. 1.] | 0.00524108 | 0.994759 | 1 | [0. 1.] | 1 |
-| (1.0, 37) | 0.00680342 | 0.992197 | 0.999 | [0. 0. 0.001 0.999] | 0.00341675 | 0.996083 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 38) | 0.0005654 | 0.998565 | 0.998 | [0. 0. 0.002 0.998] | 0.000281429 | 0.99928 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 39) | 0.0103369 | 0.988663 | 0.999 | [0. 0. 0.001 0.999] | 0.0052012 | 0.994299 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 40) | 0.00464786 | 0.994352 | 0.999 | [0. 0. 0.001 0.999] | 0.00233173 | 0.997168 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 41) | 0.00555467 | 0.993445 | 0.999 | [0. 0. 0.001 0.999] | 0.00278786 | 0.996712 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 42) | 0.000538905 | 0.999461 | 1 | [0. 0. 0. 1.] | 0.000269525 | 0.99973 | 1 | [0. 1.] | 1 |
-| (1.0, 43) | 0.000103208 | 0.999897 | 1 | [0. 0. 0. 1.] | 5.16066e-05 | 0.999948 | 1 | [0. 1.] | 1 |
-| (1.0, 44) | 0.000659831 | 0.99834 | 0.999 | [0. 0. 0.001 0.999] | 0.00033133 | 0.999168 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 45) | 0.00772108 | 0.991279 | 0.999 | [0. 0. 0.001 0.999] | 0.00388279 | 0.995617 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 46) | 0.0105663 | 0.986434 | 0.997 | [0. 0. 0.003 0.997] | 0.00532721 | 0.993171 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 47) | 0.00475672 | 0.995243 | 1 | [0. 0. 0. 1.] | 0.00238403 | 0.997616 | 1 | [0. 1.] | 1 |
-| (1.0, 48) | 0.00098032 | 0.99902 | 1 | [0. 0. 0. 1.] | 0.0004904 | 0.99951 | 1 | [0. 1.] | 1 |
-| (1.0, 49) | 0.00485684 | 0.995143 | 1 | [0. 0. 0. 1.] | 0.00243433 | 0.997566 | 1 | [0. 1.] | 1 |
-| (1.0, 50) | 0.000364171 | 0.999636 | 1 | [0. 0. 0. 1.] | 0.000182119 | 0.999818 | 1 | [0. 1.] | 1 |
-| (1.0, 51) | 0.00901725 | 0.989983 | 0.999 | [0. 0. 0.001 0.999] | 0.00453359 | 0.994966 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 52) | 0.00401398 | 0.995986 | 1 | [0. 0. 0. 1.] | 0.00201102 | 0.997989 | 1 | [0. 1.] | 1 |
-| (1.0, 53) | 6.02743e-05 | 0.99994 | 1 | [0. 0. 0. 1.] | 3.0138e-05 | 0.99997 | 1 | [0. 1.] | 1 |
-| (1.0, 54) | 0.00525217 | 0.993748 | 0.999 | [0. 0. 0.001 0.999] | 0.00263592 | 0.996864 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 55) | 0.00586705 | 0.992133 | 0.998 | [0. 0. 0.002 0.998] | 0.00294815 | 0.996051 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 56) | 0.0047068 | 0.993293 | 0.998 | [0. 0. 0.002 0.998] | 0.00236369 | 0.996635 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 57) | 0.000832389 | 0.999168 | 1 | [0. 0. 0. 1.] | 0.000416368 | 0.999584 | 1 | [0. 1.] | 1 |
-| (1.0, 58) | 0.00219301 | 0.997807 | 1 | [0. 0. 0. 1.] | 0.00109771 | 0.998902 | 1 | [0. 1.] | 1 |
-| (1.0, 59) | 0.00652092 | 0.991479 | 0.998 | [0. 0. 0.002 0.998] | 0.0032777 | 0.995721 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 60) | 0.00533726 | 0.991663 | 0.997 | [0. 0. 0.003 0.997] | 0.0026845 | 0.995813 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 61) | 0.00188364 | 0.997116 | 0.999 | [0. 0. 0.001 0.999] | 0.000945307 | 0.998554 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 62) | 0.00960516 | 0.990395 | 1 | [0. 0. 0. 1.] | 0.00482576 | 0.995174 | 1 | [0. 1.] | 1 |
-| (1.0, 63) | 0.000144585 | 0.999855 | 1 | [0. 0. 0. 1.] | 7.22978e-05 | 0.999928 | 1 | [0. 1.] | 1 |
-| (1.0, 64) | 0.0125929 | 0.984407 | 0.997 | [0. 0. 0.003 0.997] | 0.00635546 | 0.992142 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 65) | 0.00338717 | 0.995613 | 0.999 | [0. 0. 0.001 0.999] | 0.00169816 | 0.997802 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 66) | 0.00079801 | 0.998202 | 0.999 | [0. 0. 0.001 0.999] | 0.000401174 | 0.999099 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 67) | 0.00224744 | 0.997753 | 1 | [0. 0. 0. 1.] | 0.00112499 | 0.998875 | 1 | [0. 1.] | 1 |
-| (1.0, 68) | 0.00487772 | 0.995122 | 1 | [0. 0. 0. 1.] | 0.00244482 | 0.997555 | 1 | [0. 1.] | 1 |
-| (1.0, 69) | 0.000371242 | 0.999629 | 1 | [0. 0. 0. 1.] | 0.000185655 | 0.999814 | 1 | [0. 1.] | 1 |
-| (1.0, 70) | 0.00206798 | 0.997932 | 1 | [0. 0. 0. 1.] | 0.00103506 | 0.998965 | 1 | [0. 1.] | 1 |
-| (1.0, 71) | 0.000710046 | 0.99929 | 1 | [0. 0. 0. 1.] | 0.000355149 | 0.999645 | 1 | [0. 1.] | 1 |
-| (1.0, 72) | 0.00335647 | 0.993644 | 0.997 | [0. 0. 0.003 0.997] | 0.00168683 | 0.996811 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 73) | 0.00405536 | 0.994945 | 0.999 | [0. 0. 0.001 0.999] | 0.00203386 | 0.997466 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 74) | 0.00439108 | 0.995609 | 1 | [0. 0. 0. 1.] | 0.00220037 | 0.9978 | 1 | [0. 1.] | 1 |
-| (1.0, 75) | 0.000376378 | 0.999624 | 1 | [0. 0. 0. 1.] | 0.000188225 | 0.999812 | 1 | [0. 1.] | 1 |
-| (1.0, 76) | 2.2775e-05 | 0.999977 | 1 | [0. 0. 0. 1.] | 1.13876e-05 | 0.999989 | 1 | [0. 1.] | 1 |
-| (1.0, 77) | 0.000470373 | 0.99953 | 1 | [0. 0. 0. 1.] | 0.000235242 | 0.999765 | 1 | [0. 1.] | 1 |
-| (1.0, 78) | 0.000160133 | 0.99984 | 1 | [0. 0. 0. 1.] | 8.00731e-05 | 0.99992 | 1 | [0. 1.] | 1 |
-| (1.0, 79) | 0.00207087 | 0.997929 | 1 | [0. 0. 0. 1.] | 0.00103651 | 0.998963 | 1 | [0. 1.] | 1 |
-| (1.0, 80) | 0.00810417 | 0.989896 | 0.998 | [0. 0. 0.002 0.998] | 0.00407733 | 0.994922 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 81) | 0.00617284 | 0.993827 | 1 | [0. 0. 0. 1.] | 0.00309598 | 0.996904 | 1 | [0. 1.] | 1 |
-| (1.0, 82) | 0.000753367 | 0.999247 | 1 | [0. 0. 0. 1.] | 0.000376825 | 0.999623 | 1 | [0. 1.] | 1 |
-| (1.0, 83) | 0.00409922 | 0.995901 | 1 | [0. 0. 0. 1.] | 0.00205382 | 0.997946 | 1 | [0. 1.] | 1 |
-| (1.0, 84) | 0.00782572 | 0.990174 | 0.998 | [0. 0. 0.002 0.998] | 0.00393612 | 0.995063 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 85) | 0.0045099 | 0.99349 | 0.998 | [0. 0. 0.002 0.998] | 0.0022646 | 0.996734 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 86) | 0.00363821 | 0.994362 | 0.998 | [0. 0. 0.002 0.998] | 0.00182623 | 0.997173 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 87) | 0.00481349 | 0.995187 | 1 | [0. 0. 0. 1.] | 0.00241255 | 0.997587 | 1 | [0. 1.] | 1 |
-| (1.0, 88) | 0.00433078 | 0.995669 | 1 | [0. 0. 0. 1.] | 0.00217009 | 0.99783 | 1 | [0. 1.] | 1 |
-| (1.0, 89) | 0.00589255 | 0.992107 | 0.998 | [0. 0. 0.002 0.998] | 0.00296091 | 0.996038 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 90) | 0.000687943 | 0.999312 | 1 | [0. 0. 0. 1.] | 0.00034409 | 0.999656 | 1 | [0. 1.] | 1 |
-| (1.0, 91) | 0.00126096 | 0.998261 | 0.997 | [0. 0. 0.003 0.997] | 0.000629455 | 0.999127 | 0.998498 | [0.003 0.997] | 0.997 |
-| (1.0, 92) | 0.0047099 | 0.99429 | 0.999 | [0. 0. 0.001 0.999] | 0.00236294 | 0.997137 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 93) | 0.00124108 | 0.997759 | 0.999 | [0. 0. 0.001 0.999] | 0.000621546 | 0.998878 | 0.9995 | [0.001 0.999] | 0.999 |
-| (1.0, 94) | 0.00111707 | 0.996883 | 0.998 | [0. 0. 0.002 0.998] | 0.00055997 | 0.998439 | 0.998999 | [0.002 0.998] | 0.998 |
-| (1.0, 95) | 2.16117e-05 | 0.999978 | 1 | [0. 0. 0. 1.] | 1.0806e-05 | 0.999989 | 1 | [0. 1.] | 1 |
-| (1.0, 96) | 0.00580863 | 0.994191 | 1 | [0. 0. 0. 1.] | 0.00291278 | 0.997087 | 1 | [0. 1.] | 1 |
-| (1.0, 97) | 0.00636452 | 0.993635 | 1 | [0. 0. 0. 1.] | 0.00319242 | 0.996808 | 1 | [0. 1.] | 1 |
-| (1.0, 98) | 0.00321332 | 0.996787 | 1 | [0. 0. 0. 1.] | 0.00160925 | 0.998391 | 1 | [0. 1.] | 1 |
+| | ('acc', 'mulmc_sld') | ('acc_score', 'mulmc_sld') | ('acc_score', 'ref') | ('eprevs', 'mulmc_sld') | ('f1', 'mulmc_sld') | ('f1_score', 'mulmc_sld') | ('f1_score', 'ref') | ('prevs', 'mulmc_sld') | ('ref', 'mulmc_sld') |
+|:-----------|-----------------------:|-----------------------------:|-----------------------:|:--------------------------|----------------------:|----------------------------:|----------------------:|:-------------------------|-----------------------:|
+| (0.0, 0) | 0.117723 | 0.0322767 | 0.15 | [0.15 0.85 0. 0. ] | 1.07331e-70 | 1.07331e-70 | 0 | [0.15 0.85] | 0.15 |
+| (0.0, 1) | 0.104077 | 0.0449229 | 0.149 | [0.149 0.851 0. 0. ] | 8.53968e-74 | 8.53968e-74 | 0 | [0.149 0.851] | 0.149 |
+| (0.0, 2) | 0.087328 | 0.046672 | 0.134 | [0.134 0.866 0. 0. ] | 1.42651e-85 | 1.42651e-85 | 0 | [0.134 0.866] | 0.134 |
+| (0.0, 3) | 0.111971 | 0.0340294 | 0.146 | [0.146 0.854 0. 0. ] | 6.79989e-84 | 6.79989e-84 | 0 | [0.146 0.854] | 0.146 |
+| (0.0, 4) | 0.114691 | 0.0233089 | 0.138 | [0.138 0.862 0. 0. ] | 1.46993e-84 | 1.46993e-84 | 0 | [0.138 0.862] | 0.138 |
+| (0.0, 5) | 0.103348 | 0.0556519 | 0.159 | [0.159 0.841 0. 0. ] | 3.0317e-73 | 3.0317e-73 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 6) | 0.0685699 | 0.0654301 | 0.134 | [0.134 0.866 0. 0. ] | 1.41915e-80 | 1.41915e-80 | 0 | [0.134 0.866] | 0.134 |
+| (0.0, 7) | 0.0672097 | 0.0867903 | 0.154 | [0.154 0.846 0. 0. ] | 1.58212e-72 | 1.58212e-72 | 0 | [0.154 0.846] | 0.154 |
+| (0.0, 8) | 0.0906741 | 0.0343259 | 0.125 | [0.125 0.875 0. 0. ] | 2.35037e-81 | 2.35037e-81 | 0 | [0.125 0.875] | 0.125 |
+| (0.0, 9) | 0.108344 | 0.0456563 | 0.154 | [0.154 0.846 0. 0. ] | 1.61876e-89 | 1.61876e-89 | 0 | [0.154 0.846] | 0.154 |
+| (0.0, 10) | 0.111637 | 0.0303634 | 0.142 | [0.142 0.858 0. 0. ] | 2.34042e-76 | 2.34042e-76 | 0 | [0.142 0.858] | 0.142 |
+| (0.0, 11) | 0.0818937 | 0.0631063 | 0.145 | [0.145 0.855 0. 0. ] | 8.88464e-76 | 8.88464e-76 | 0 | [0.145 0.855] | 0.145 |
+| (0.0, 12) | 0.080566 | 0.053434 | 0.134 | [0.134 0.866 0. 0. ] | 2.06441e-85 | 2.06441e-85 | 0 | [0.134 0.866] | 0.134 |
+| (0.0, 13) | 0.109082 | 0.0259184 | 0.135 | [0.135 0.865 0. 0. ] | 6.90501e-68 | 6.90501e-68 | 0 | [0.135 0.865] | 0.135 |
+| (0.0, 14) | 0.104661 | 0.0563386 | 0.161 | [0.161 0.839 0. 0. ] | 1.20084e-80 | 1.20084e-80 | 0 | [0.161 0.839] | 0.161 |
+| (0.0, 15) | 0.110168 | 0.0358321 | 0.146 | [0.146 0.854 0. 0. ] | 5.13457e-80 | 5.13457e-80 | 0 | [0.146 0.854] | 0.146 |
+| (0.0, 16) | 0.0821699 | 0.0548301 | 0.137 | [0.137 0.863 0. 0. ] | 1.23927e-107 | 1.23927e-107 | 0 | [0.137 0.863] | 0.137 |
+| (0.0, 17) | 0.152954 | 0.00104645 | 0.154 | [0.154 0.846 0. 0. ] | 7.76874e-67 | 7.76874e-67 | 0 | [0.154 0.846] | 0.154 |
+| (0.0, 18) | 0.101295 | 0.0507053 | 0.152 | [0.152 0.848 0. 0. ] | 5.41613e-70 | 5.41613e-70 | 0 | [0.152 0.848] | 0.152 |
+| (0.0, 19) | 0.101427 | 0.0475729 | 0.149 | [0.149 0.851 0. 0. ] | 7.82058e-75 | 7.82058e-75 | 0 | [0.149 0.851] | 0.149 |
+| (0.0, 20) | 0.0552487 | 0.111751 | 0.167 | [0.167 0.833 0. 0. ] | 1.48613e-85 | 1.48613e-85 | 0 | [0.167 0.833] | 0.167 |
+| (0.0, 21) | 0.105907 | 0.0250927 | 0.131 | [0.131 0.869 0. 0. ] | 4.52759e-74 | 4.52759e-74 | 0 | [0.131 0.869] | 0.131 |
+| (0.0, 22) | 0.0702368 | 0.0837632 | 0.154 | [0.154 0.846 0. 0. ] | 4.82942e-111 | 4.82942e-111 | 0 | [0.154 0.846] | 0.154 |
+| (0.0, 23) | 0.121287 | 0.0297134 | 0.151 | [0.151 0.849 0. 0. ] | 5.89441e-65 | 5.89441e-65 | 0 | [0.151 0.849] | 0.151 |
+| (0.0, 24) | 0.0834857 | 0.0645143 | 0.148 | [0.148 0.852 0. 0. ] | 3.59591e-72 | 3.59591e-72 | 0 | [0.148 0.852] | 0.148 |
+| (0.0, 25) | 0.0948862 | 0.0471138 | 0.142 | [0.142 0.858 0. 0. ] | 4.1855e-77 | 4.1855e-77 | 0 | [0.142 0.858] | 0.142 |
+| (0.0, 26) | 0.084485 | 0.066515 | 0.151 | [0.151 0.849 0. 0. ] | 3.53958e-93 | 3.53958e-93 | 0 | [0.151 0.849] | 0.151 |
+| (0.0, 27) | 0.0788194 | 0.0781806 | 0.157 | [0.157 0.843 0. 0. ] | 7.26205e-93 | 7.26205e-93 | 0 | [0.157 0.843] | 0.157 |
+| (0.0, 28) | 0.100112 | 0.0588884 | 0.159 | [0.159 0.841 0. 0. ] | 3.99054e-87 | 3.99054e-87 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 29) | 0.0964799 | 0.0535201 | 0.15 | [0.15 0.85 0. 0. ] | 6.532e-82 | 6.532e-82 | 0 | [0.15 0.85] | 0.15 |
+| (0.0, 30) | 0.119753 | 0.0272469 | 0.147 | [0.147 0.853 0. 0. ] | 4.10831e-75 | 4.10831e-75 | 0 | [0.147 0.853] | 0.147 |
+| (0.0, 31) | 0.0706346 | 0.0883654 | 0.159 | [0.159 0.841 0. 0. ] | 1.27863e-72 | 1.27863e-72 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 32) | 0.0988101 | 0.0491899 | 0.148 | [0.148 0.852 0. 0. ] | 2.07851e-74 | 2.07851e-74 | 0 | [0.148 0.852] | 0.148 |
+| (0.0, 33) | 0.0783135 | 0.0846865 | 0.163 | [0.163 0.837 0. 0. ] | 2.39408e-90 | 2.39408e-90 | 0 | [0.163 0.837] | 0.163 |
+| (0.0, 34) | 0.0902689 | 0.0557311 | 0.146 | [0.146 0.854 0. 0. ] | 6.57654e-81 | 6.57654e-81 | 0 | [0.146 0.854] | 0.146 |
+| (0.0, 35) | 0.0917235 | 0.0572765 | 0.149 | [0.149 0.851 0. 0. ] | 1.93739e-83 | 1.93739e-83 | 0 | [0.149 0.851] | 0.149 |
+| (0.0, 36) | 0.0600061 | 0.108994 | 0.169 | [0.169 0.831 0. 0. ] | 1.4334e-110 | 1.4334e-110 | 0 | [0.169 0.831] | 0.169 |
+| (0.0, 37) | 0.0939152 | 0.0700848 | 0.164 | [0.164 0.836 0. 0. ] | 3.97301e-77 | 3.97301e-77 | 0 | [0.164 0.836] | 0.164 |
+| (0.0, 38) | 0.0713029 | 0.0846971 | 0.156 | [0.156 0.844 0. 0. ] | 1.62578e-85 | 1.62578e-85 | 0 | [0.156 0.844] | 0.156 |
+| (0.0, 39) | 0.10238 | 0.0696199 | 0.172 | [0.172 0.828 0. 0. ] | 1.64608e-71 | 1.64608e-71 | 0 | [0.172 0.828] | 0.172 |
+| (0.0, 40) | 0.0808104 | 0.0661896 | 0.147 | [0.147 0.853 0. 0. ] | 7.03173e-76 | 7.03173e-76 | 0 | [0.147 0.853] | 0.147 |
+| (0.0, 41) | 0.0477844 | 0.105216 | 0.153 | [0.153 0.847 0. 0. ] | 1.94212e-97 | 1.94212e-97 | 0 | [0.153 0.847] | 0.153 |
+| (0.0, 42) | 0.0755388 | 0.0734612 | 0.149 | [0.149 0.851 0. 0. ] | 9.58123e-82 | 9.58123e-82 | 0 | [0.149 0.851] | 0.149 |
+| (0.0, 43) | 0.0541017 | 0.0788983 | 0.133 | [0.133 0.867 0. 0. ] | 3.21118e-74 | 3.21118e-74 | 0 | [0.133 0.867] | 0.133 |
+| (0.0, 44) | 0.0856808 | 0.0713192 | 0.157 | [0.157 0.843 0. 0. ] | 1.72404e-73 | 1.72404e-73 | 0 | [0.157 0.843] | 0.157 |
+| (0.0, 45) | 0.0736663 | 0.0893337 | 0.163 | [0.163 0.837 0. 0. ] | 5.94041e-97 | 5.94041e-97 | 0 | [0.163 0.837] | 0.163 |
+| (0.0, 46) | 0.118402 | 0.038598 | 0.157 | [0.157 0.843 0. 0. ] | 6.0959e-69 | 6.0959e-69 | 0 | [0.157 0.843] | 0.157 |
+| (0.0, 47) | 0.11078 | 0.0342197 | 0.145 | [0.145 0.855 0. 0. ] | 4.06314e-72 | 4.06314e-72 | 0 | [0.145 0.855] | 0.145 |
+| (0.0, 48) | 0.0831503 | 0.0478497 | 0.131 | [0.131 0.869 0. 0. ] | 5.42314e-85 | 5.42314e-85 | 0 | [0.131 0.869] | 0.131 |
+| (0.0, 49) | 0.0916819 | 0.0513181 | 0.143 | [0.143 0.857 0. 0. ] | 5.04478e-81 | 5.04478e-81 | 0 | [0.143 0.857] | 0.143 |
+| (0.0, 50) | 0.11094 | 0.03506 | 0.146 | [0.146 0.854 0. 0. ] | 2.9869e-75 | 2.9869e-75 | 0 | [0.146 0.854] | 0.146 |
+| (0.0, 51) | 0.0908154 | 0.0471846 | 0.138 | [0.138 0.862 0. 0. ] | 7.09617e-64 | 7.09617e-64 | 0 | [0.138 0.862] | 0.138 |
+| (0.0, 52) | 0.116686 | 0.0233143 | 0.14 | [0.14 0.86 0. 0. ] | 1.53735e-66 | 1.53735e-66 | 0 | [0.14 0.86] | 0.14 |
+| (0.0, 53) | 0.0621283 | 0.104872 | 0.167 | [0.167 0.833 0. 0. ] | 1.32848e-95 | 1.32848e-95 | 0 | [0.167 0.833] | 0.167 |
+| (0.0, 54) | 0.0971333 | 0.0688667 | 0.166 | [0.166 0.834 0. 0. ] | 1.60209e-77 | 1.60209e-77 | 0 | [0.166 0.834] | 0.166 |
+| (0.0, 55) | 0.0930373 | 0.0839627 | 0.177 | [0.177 0.823 0. 0. ] | 1.6235e-87 | 1.6235e-87 | 0 | [0.177 0.823] | 0.177 |
+| (0.0, 56) | 0.0757822 | 0.0812178 | 0.157 | [0.157 0.843 0. 0. ] | 4.25804e-75 | 4.25804e-75 | 0 | [0.157 0.843] | 0.157 |
+| (0.0, 57) | 0.0938824 | 0.0411176 | 0.135 | [0.135 0.865 0. 0. ] | 2.09063e-71 | 2.09063e-71 | 0 | [0.135 0.865] | 0.135 |
+| (0.0, 58) | 0.106571 | 0.0524287 | 0.159 | [0.159 0.841 0. 0. ] | 7.73697e-68 | 7.73697e-68 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 59) | 0.0897803 | 0.0692197 | 0.159 | [0.159 0.841 0. 0. ] | 9.83727e-73 | 9.83727e-73 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 60) | 0.111984 | 0.0160161 | 0.128 | [0.128 0.872 0. 0. ] | 3.54758e-79 | 3.54758e-79 | 0 | [0.128 0.872] | 0.128 |
+| (0.0, 61) | 0.101143 | 0.0308567 | 0.132 | [0.132 0.868 0. 0. ] | 1.72902e-77 | 1.72902e-77 | 0 | [0.132 0.868] | 0.132 |
+| (0.0, 62) | 0.115279 | 0.0377211 | 0.153 | [0.153 0.847 0. 0. ] | 7.03603e-77 | 7.03603e-77 | 0 | [0.153 0.847] | 0.153 |
+| (0.0, 63) | 0.0948507 | 0.0621493 | 0.157 | [0.157 0.843 0. 0. ] | 1.29883e-86 | 1.29883e-86 | 0 | [0.157 0.843] | 0.157 |
+| (0.0, 64) | 0.103509 | 0.0334913 | 0.137 | [0.137 0.863 0. 0. ] | 3.80986e-80 | 3.80986e-80 | 0 | [0.137 0.863] | 0.137 |
+| (0.0, 65) | 0.0781409 | 0.0808591 | 0.159 | [0.159 0.841 0. 0. ] | 1.80981e-71 | 1.80981e-71 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 66) | 0.0757231 | 0.0592769 | 0.135 | [0.135 0.865 0. 0. ] | 3.5588e-95 | 3.5588e-95 | 0 | [0.135 0.865] | 0.135 |
+| (0.0, 67) | 0.0728872 | 0.0881128 | 0.161 | [0.161 0.839 0. 0. ] | 5.99213e-89 | 5.99213e-89 | 0 | [0.161 0.839] | 0.161 |
+| (0.0, 68) | 0.0639539 | 0.0750461 | 0.139 | [0.139 0.861 0. 0. ] | 6.04828e-84 | 6.04828e-84 | 0 | [0.139 0.861] | 0.139 |
+| (0.0, 69) | 0.126742 | 0.0192578 | 0.146 | [0.146 0.854 0. 0. ] | 3.02779e-81 | 3.02779e-81 | 0 | [0.146 0.854] | 0.146 |
+| (0.0, 70) | 0.0826081 | 0.0673919 | 0.15 | [0.15 0.85 0. 0. ] | 1.46215e-89 | 1.46215e-89 | 0 | [0.15 0.85] | 0.15 |
+| (0.0, 71) | 0.0866534 | 0.0793466 | 0.166 | [0.166 0.834 0. 0. ] | 4.1842e-87 | 4.1842e-87 | 0 | [0.166 0.834] | 0.166 |
+| (0.0, 72) | 0.0756651 | 0.0873349 | 0.163 | [0.163 0.837 0. 0. ] | 4.15436e-100 | 4.15436e-100 | 0 | [0.163 0.837] | 0.163 |
+| (0.0, 73) | 0.0842012 | 0.0727988 | 0.157 | [0.157 0.843 0. 0. ] | 4.33554e-72 | 4.33554e-72 | 0 | [0.157 0.843] | 0.157 |
+| (0.0, 74) | 0.0732343 | 0.0537657 | 0.127 | [0.127 0.873 0. 0. ] | 5.78521e-65 | 5.78521e-65 | 0 | [0.127 0.873] | 0.127 |
+| (0.0, 75) | 0.0436204 | 0.10138 | 0.145 | [0.145 0.855 0. 0. ] | 5.99248e-08 | 5.99248e-08 | 0 | [0.145 0.855] | 0.145 |
+| (0.0, 76) | 0.073634 | 0.071366 | 0.145 | [0.145 0.855 0. 0. ] | 1.33422e-86 | 1.33422e-86 | 0 | [0.145 0.855] | 0.145 |
+| (0.0, 77) | 0.114722 | 0.0242778 | 0.139 | [0.139 0.861 0. 0. ] | 1.22296e-69 | 1.22296e-69 | 0 | [0.139 0.861] | 0.139 |
+| (0.0, 78) | 0.0910729 | 0.0529271 | 0.144 | [0.144 0.856 0. 0. ] | 3.20385e-81 | 3.20385e-81 | 0 | [0.144 0.856] | 0.144 |
+| (0.0, 79) | 0.1199 | 0.0391 | 0.159 | [0.159 0.841 0. 0. ] | 4.88611e-80 | 4.88611e-80 | 0 | [0.159 0.841] | 0.159 |
+| (0.0, 80) | 0.101953 | 0.0500466 | 0.152 | [0.152 0.848 0. 0. ] | 1.89129e-75 | 1.89129e-75 | 0 | [0.152 0.848] | 0.152 |
+| (0.0, 81) | 0.0889951 | 0.0510049 | 0.14 | [0.14 0.86 0. 0. ] | 1.37045e-70 | 1.37045e-70 | 0 | [0.14 0.86] | 0.14 |
+| (0.0, 82) | 0.0998662 | 0.0471338 | 0.147 | [0.147 0.853 0. 0. ] | 3.1581e-76 | 3.1581e-76 | 0 | [0.147 0.853] | 0.147 |
+| (0.0, 83) | 0.0831914 | 0.0558086 | 0.139 | [0.139 0.861 0. 0. ] | 1.71931e-86 | 1.71931e-86 | 0 | [0.139 0.861] | 0.139 |
+| (0.0, 84) | 0.120851 | 0.0331487 | 0.154 | [0.154 0.846 0. 0. ] | 7.23765e-74 | 7.23765e-74 | 0 | [0.154 0.846] | 0.154 |
+| (0.0, 85) | 0.100605 | 0.0433947 | 0.144 | [0.144 0.856 0. 0. ] | 2.67006e-82 | 2.67006e-82 | 0 | [0.144 0.856] | 0.144 |
+| (0.0, 86) | 0.0765061 | 0.0734939 | 0.15 | [0.15 0.85 0. 0. ] | 1.61559e-83 | 1.61559e-83 | 0 | [0.15 0.85] | 0.15 |
+| (0.0, 87) | 0.0705979 | 0.0724021 | 0.143 | [0.143 0.857 0. 0. ] | 6.80161e-90 | 6.80161e-90 | 0 | [0.143 0.857] | 0.143 |
+| (0.0, 88) | 0.133956 | 0.0270437 | 0.161 | [0.161 0.839 0. 0. ] | 4.02932e-85 | 4.02932e-85 | 0 | [0.161 0.839] | 0.161 |
+| (0.0, 89) | 0.0874214 | 0.0665786 | 0.154 | [0.154 0.846 0. 0. ] | 5.57476e-68 | 5.57476e-68 | 0 | [0.154 0.846] | 0.154 |
+| (0.0, 90) | 0.0715817 | 0.0634183 | 0.135 | [0.135 0.865 0. 0. ] | 4.40147e-76 | 4.40147e-76 | 0 | [0.135 0.865] | 0.135 |
+| (0.0, 91) | 0.0905213 | 0.0544787 | 0.145 | [0.145 0.855 0. 0. ] | 5.28556e-78 | 5.28556e-78 | 0 | [0.145 0.855] | 0.145 |
+| (0.0, 92) | 0.0795437 | 0.0964563 | 0.176 | [0.176 0.824 0. 0. ] | 1.1435e-87 | 1.1435e-87 | 0 | [0.176 0.824] | 0.176 |
+| (0.0, 93) | 0.118409 | 0.0365913 | 0.155 | [0.155 0.845 0. 0. ] | 3.5294e-95 | 3.5294e-95 | 0 | [0.155 0.845] | 0.155 |
+| (0.0, 94) | 0.109805 | 0.0591953 | 0.169 | [0.169 0.831 0. 0. ] | 1.80285e-76 | 1.80285e-76 | 0 | [0.169 0.831] | 0.169 |
+| (0.0, 95) | 0.098196 | 0.052804 | 0.151 | [0.151 0.849 0. 0. ] | 2.818e-84 | 2.818e-84 | 0 | [0.151 0.849] | 0.151 |
+| (0.0, 96) | 0.112439 | 0.0345615 | 0.147 | [0.147 0.853 0. 0. ] | 3.6936e-71 | 3.6936e-71 | 0 | [0.147 0.853] | 0.147 |
+| (0.0, 97) | 0.0904939 | 0.0645061 | 0.155 | [0.155 0.845 0. 0. ] | 8.14262e-94 | 8.14262e-94 | 0 | [0.155 0.845] | 0.155 |
+| (0.0, 98) | 0.107304 | 0.028696 | 0.136 | [0.136 0.864 0. 0. ] | 7.45097e-62 | 7.45097e-62 | 0 | [0.136 0.864] | 0.136 |
+| (0.0, 99) | 0.0726854 | 0.0783146 | 0.151 | [0.151 0.849 0. 0. ] | 1.27965e-92 | 1.27965e-92 | 0 | [0.151 0.849] | 0.151 |
+| (0.05, 0) | 0.139695 | 0.0533047 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 1.14176e-19 | 0.110254 | [0.143 0.857] | 0.193 |
+| (0.05, 1) | 0.135563 | 0.0344375 | 0.17 | [0.12 0.83 0. 0.05] | 0.107527 | 3.58656e-10 | 0.107527 | [0.12 0.88] | 0.17 |
+| (0.05, 2) | 0.140995 | 0.0510053 | 0.192 | [0.142 0.808 0. 0.05 ] | 0.110132 | 2.74753e-22 | 0.110132 | [0.142 0.858] | 0.192 |
+| (0.05, 3) | 0.137862 | 0.0681381 | 0.206 | [0.156 0.794 0. 0.05 ] | 0.111857 | 1.58351e-10 | 0.111857 | [0.156 0.844] | 0.206 |
+| (0.05, 4) | 0.106135 | 0.0828645 | 0.189 | [0.139 0.811 0. 0.05 ] | 0.109234 | 0.000535505 | 0.109769 | [0.139 0.861] | 0.189 |
+| (0.05, 5) | 0.122517 | 0.0634832 | 0.186 | [0.136 0.814 0. 0.05 ] | 0.109409 | 4.44136e-17 | 0.109409 | [0.136 0.864] | 0.186 |
+| (0.05, 6) | 0.156419 | 0.0255809 | 0.182 | [0.132 0.818 0. 0.05 ] | 0.108932 | 3.43807e-18 | 0.108932 | [0.132 0.868] | 0.182 |
+| (0.05, 7) | 0.145084 | 0.0439162 | 0.189 | [0.139 0.811 0. 0.05 ] | 0.109769 | 2.65993e-14 | 0.109769 | [0.139 0.861] | 0.189 |
+| (0.05, 8) | 0.155093 | 0.0359071 | 0.191 | [0.142 0.808 0.001 0.049] | 0.108049 | 4.59776e-11 | 0.108049 | [0.143 0.857] | 0.191 |
+| (0.05, 9) | 0.182126 | 0.00487421 | 0.187 | [0.137 0.813 0. 0.05 ] | 0.109529 | 1.84496e-14 | 0.109529 | [0.137 0.863] | 0.187 |
+| (0.05, 10) | 0.0998061 | 0.0921939 | 0.192 | [0.142 0.808 0. 0.05 ] | 0.110132 | 4.03461e-21 | 0.110132 | [0.142 0.858] | 0.192 |
+| (0.05, 11) | 0.135749 | 0.0592513 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 3.16984e-21 | 0.110497 | [0.145 0.855] | 0.195 |
+| (0.05, 12) | 0.115695 | 0.087305 | 0.203 | [0.153 0.797 0. 0.05 ] | 0.111483 | 1.33398e-15 | 0.111483 | [0.153 0.847] | 0.203 |
+| (0.05, 13) | 0.132882 | 0.0491177 | 0.182 | [0.132 0.818 0. 0.05 ] | 0.108932 | 3.836e-24 | 0.108932 | [0.132 0.868] | 0.182 |
+| (0.05, 14) | 0.10577 | 0.0692296 | 0.175 | [0.125 0.825 0. 0.05 ] | 0.108108 | 9.72476e-12 | 0.108108 | [0.125 0.875] | 0.175 |
+| (0.05, 15) | 0.156678 | 0.036322 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 2.07272e-23 | 0.110254 | [0.143 0.857] | 0.193 |
+| (0.05, 16) | 0.104347 | 0.0826534 | 0.187 | [0.137 0.813 0. 0.05 ] | 0.107933 | 0.00159586 | 0.109529 | [0.137 0.863] | 0.187 |
+| (0.05, 17) | 0.169004 | 0.00799577 | 0.177 | [0.127 0.823 0. 0.05 ] | 0.108342 | 7.79333e-11 | 0.108342 | [0.127 0.873] | 0.177 |
+| (0.05, 18) | 0.128698 | 0.0653016 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 1.77321e-22 | 0.110375 | [0.144 0.856] | 0.194 |
+| (0.05, 19) | 0.111877 | 0.0971234 | 0.209 | [0.159 0.791 0. 0.05 ] | 0.112233 | 2.68131e-19 | 0.112233 | [0.159 0.841] | 0.209 |
+| (0.05, 20) | 0.155026 | 0.0209742 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.108225 | 3.94502e-18 | 0.108225 | [0.126 0.874] | 0.176 |
+| (0.05, 21) | 0.124618 | 0.0773818 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111359 | 9.0121e-31 | 0.111359 | [0.152 0.848] | 0.202 |
+| (0.05, 22) | 0.130664 | 0.0603363 | 0.191 | [0.141 0.809 0. 0.05 ] | 0.110011 | 3.03675e-22 | 0.110011 | [0.141 0.859] | 0.191 |
+| (0.05, 23) | 0.154081 | 0.0469192 | 0.201 | [0.151 0.799 0. 0.05 ] | 0.111235 | 2.16643e-11 | 0.111235 | [0.151 0.849] | 0.201 |
+| (0.05, 24) | 0.122652 | 0.059348 | 0.182 | [0.132 0.818 0. 0.05 ] | 0.108932 | 1.6966e-14 | 0.108932 | [0.132 0.868] | 0.182 |
+| (0.05, 25) | 0.146311 | 0.055689 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111355 | 3.46681e-06 | 0.111359 | [0.152 0.848] | 0.202 |
+| (0.05, 26) | 0.140658 | 0.0373423 | 0.178 | [0.128 0.822 0. 0.05 ] | 0.10846 | 2.48311e-18 | 0.10846 | [0.128 0.872] | 0.178 |
+| (0.05, 27) | 0.134002 | 0.0429984 | 0.177 | [0.127 0.823 0. 0.05 ] | 0.108342 | 9.19174e-20 | 0.108342 | [0.127 0.873] | 0.177 |
+| (0.05, 28) | 0.157105 | 0.0368953 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 4.83413e-18 | 0.110375 | [0.144 0.856] | 0.194 |
+| (0.05, 29) | 0.149111 | 0.0308887 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 1.16102e-21 | 0.108696 | [0.13 0.87] | 0.18 |
+| (0.05, 30) | 0.104365 | 0.0786353 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 1.10507e-14 | 0.109051 | [0.133 0.867] | 0.183 |
+| (0.05, 31) | 0.158109 | 0.041891 | 0.2 | [0.151 0.799 0.001 0.049] | 0.109131 | 8.10113e-19 | 0.109131 | [0.152 0.848] | 0.2 |
+| (0.05, 32) | 0.14954 | 0.0294602 | 0.179 | [0.129 0.821 0. 0.05 ] | 0.108578 | 1.28469e-14 | 0.108578 | [0.129 0.871] | 0.179 |
+| (0.05, 33) | 0.157869 | 0.0161307 | 0.174 | [0.124 0.826 0. 0.05 ] | 0.107991 | 7.84528e-18 | 0.107991 | [0.124 0.876] | 0.174 |
+| (0.05, 34) | 0.157753 | 0.039247 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 2.2032e-17 | 0.110742 | [0.147 0.853] | 0.197 |
+| (0.05, 35) | 0.134724 | 0.0462759 | 0.181 | [0.131 0.819 0. 0.05 ] | 0.108814 | 1.46e-14 | 0.108814 | [0.131 0.869] | 0.181 |
+| (0.05, 36) | 0.14284 | 0.0331603 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.108225 | 3.56508e-16 | 0.108225 | [0.126 0.874] | 0.176 |
+| (0.05, 37) | 0.135851 | 0.0541488 | 0.19 | [0.14 0.81 0. 0.05] | 0.10989 | 1.37439e-14 | 0.10989 | [0.14 0.86] | 0.19 |
+| (0.05, 38) | 0.120848 | 0.0871521 | 0.208 | [0.158 0.792 0. 0.05 ] | 0.112108 | 3.07361e-10 | 0.112108 | [0.158 0.842] | 0.208 |
+| (0.05, 39) | 0.108411 | 0.071589 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 9.4529e-12 | 0.108696 | [0.13 0.87] | 0.18 |
+| (0.05, 40) | 0.138167 | 0.0358328 | 0.174 | [0.124 0.826 0. 0.05 ] | 0.107991 | 3.92459e-22 | 0.107991 | [0.124 0.876] | 0.174 |
+| (0.05, 41) | 0.134067 | 0.0729327 | 0.207 | [0.157 0.793 0. 0.05 ] | 0.111982 | 6.75036e-30 | 0.111982 | [0.157 0.843] | 0.207 |
+| (0.05, 42) | 0.172425 | 0.0235747 | 0.196 | [0.146 0.804 0. 0.05 ] | 0.110619 | 1.7918e-18 | 0.110619 | [0.146 0.854] | 0.196 |
+| (0.05, 43) | 0.137972 | 0.0540283 | 0.192 | [0.142 0.808 0. 0.05 ] | 0.110132 | 6.253e-19 | 0.110132 | [0.142 0.858] | 0.192 |
+| (0.05, 44) | 0.128741 | 0.0542591 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 1.05882e-23 | 0.109051 | [0.133 0.867] | 0.183 |
+| (0.05, 45) | 0.138375 | 0.0376248 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.108225 | 4.84466e-15 | 0.108225 | [0.126 0.874] | 0.176 |
+| (0.05, 46) | 0.162737 | 0.0232628 | 0.186 | [0.136 0.814 0. 0.05 ] | 0.109389 | 2.06901e-05 | 0.109409 | [0.136 0.864] | 0.186 |
+| (0.05, 47) | 0.145798 | 0.0382015 | 0.184 | [0.134 0.816 0. 0.05 ] | 0.10917 | 2.78441e-27 | 0.10917 | [0.134 0.866] | 0.184 |
+| (0.05, 48) | 0.137354 | 0.0726463 | 0.21 | [0.16 0.79 0. 0.05] | 0.11236 | 2.97923e-25 | 0.11236 | [0.16 0.84] | 0.21 |
+| (0.05, 49) | 0.155531 | 0.0394693 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 3.57224e-19 | 0.110497 | [0.145 0.855] | 0.195 |
+| (0.05, 50) | 0.165329 | 0.0146715 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 7.05554e-15 | 0.108696 | [0.13 0.87] | 0.18 |
+| (0.05, 51) | 0.107478 | 0.0715223 | 0.179 | [0.129 0.821 0. 0.05 ] | 0.108578 | 2.33682e-16 | 0.108578 | [0.129 0.871] | 0.179 |
+| (0.05, 52) | 0.0938284 | 0.0901716 | 0.184 | [0.134 0.816 0. 0.05 ] | 0.108422 | 0.000747907 | 0.10917 | [0.134 0.866] | 0.184 |
+| (0.05, 53) | 0.137715 | 0.0582849 | 0.196 | [0.146 0.804 0. 0.05 ] | 0.110619 | 9.415e-15 | 0.110619 | [0.146 0.854] | 0.196 |
+| (0.05, 54) | 0.152119 | 0.0308814 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 3.14673e-08 | 0.109051 | [0.133 0.867] | 0.183 |
+| (0.05, 55) | 0.17551 | 0.0224896 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 2.44773e-14 | 0.110865 | [0.148 0.852] | 0.198 |
+| (0.05, 56) | 0.180796 | 0.0172042 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 7.30979e-13 | 0.110865 | [0.148 0.852] | 0.198 |
+| (0.05, 57) | 0.129629 | 0.0533714 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 7.45796e-26 | 0.109051 | [0.133 0.867] | 0.183 |
+| (0.05, 58) | 0.163147 | 0.016853 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 2.66764e-19 | 0.108696 | [0.13 0.87] | 0.18 |
+| (0.05, 59) | 0.0869485 | 0.103052 | 0.19 | [0.14 0.81 0. 0.05] | 0.109035 | 0.000854853 | 0.10989 | [0.14 0.86] | 0.19 |
+| (0.05, 60) | 0.149196 | 0.0458035 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 1.89128e-15 | 0.110497 | [0.145 0.855] | 0.195 |
+| (0.05, 61) | 0.126469 | 0.0565306 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.109051 | 1.04909e-16 | 0.109051 | [0.133 0.867] | 0.183 |
+| (0.05, 62) | 0.172479 | 0.0155209 | 0.188 | [0.139 0.811 0.001 0.049] | 0.107692 | 3.99895e-09 | 0.107692 | [0.14 0.86] | 0.188 |
+| (0.05, 63) | 0.0976526 | 0.0803474 | 0.178 | [0.128 0.822 0. 0.05 ] | 0.10846 | 1.72691e-33 | 0.10846 | [0.128 0.872] | 0.178 |
+| (0.05, 64) | 0.118217 | 0.0667828 | 0.185 | [0.135 0.815 0. 0.05 ] | 0.10929 | 3.28193e-14 | 0.10929 | [0.135 0.865] | 0.185 |
+| (0.05, 65) | 0.0917532 | 0.0912468 | 0.183 | [0.133 0.817 0. 0.05 ] | 0.1084 | 0.000651129 | 0.109051 | [0.133 0.867] | 0.183 |
+| (0.05, 66) | 0.0971105 | 0.0788895 | 0.176 | [0.126 0.824 0. 0.05 ] | 0.107692 | 0.000532613 | 0.108225 | [0.126 0.874] | 0.176 |
+| (0.05, 67) | 0.107754 | 0.0802459 | 0.188 | [0.138 0.812 0. 0.05 ] | 0.109269 | 0.000379747 | 0.109649 | [0.138 0.862] | 0.188 |
+| (0.05, 68) | 0.153214 | 0.0267861 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 1.06491e-21 | 0.108696 | [0.13 0.87] | 0.18 |
+| (0.05, 69) | 0.140475 | 0.0495245 | 0.19 | [0.14 0.81 0. 0.05] | 0.10989 | 2.79207e-20 | 0.10989 | [0.14 0.86] | 0.19 |
+| (0.05, 70) | 0.145541 | 0.0454591 | 0.191 | [0.141 0.809 0. 0.05 ] | 0.110011 | 2.75263e-10 | 0.110011 | [0.141 0.859] | 0.191 |
+| (0.05, 71) | 0.155227 | 0.0187734 | 0.174 | [0.124 0.826 0. 0.05 ] | 0.107991 | 4.71961e-12 | 0.107991 | [0.124 0.876] | 0.174 |
+| (0.05, 72) | 0.154241 | 0.0667593 | 0.221 | [0.171 0.779 0. 0.05 ] | 0.113766 | 6.45733e-22 | 0.113766 | [0.171 0.829] | 0.221 |
+| (0.05, 73) | 0.149282 | 0.0537176 | 0.203 | [0.153 0.797 0. 0.05 ] | 0.111483 | 5.42307e-08 | 0.111483 | [0.153 0.847] | 0.203 |
+| (0.05, 74) | 0.112973 | 0.0600274 | 0.173 | [0.123 0.827 0. 0.05 ] | 0.107875 | 3.72521e-13 | 0.107875 | [0.123 0.877] | 0.173 |
+| (0.05, 75) | 0.118677 | 0.0783229 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 2.40661e-16 | 0.110742 | [0.147 0.853] | 0.197 |
+| (0.05, 76) | 0.118952 | 0.0800475 | 0.199 | [0.149 0.801 0. 0.05 ] | 0.110988 | 6.3083e-23 | 0.110988 | [0.149 0.851] | 0.199 |
+| (0.05, 77) | 0.147543 | 0.0464572 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 1.67292e-16 | 0.110375 | [0.144 0.856] | 0.194 |
+| (0.05, 78) | 0.157932 | 0.0350678 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 1.80691e-27 | 0.110254 | [0.143 0.857] | 0.193 |
+| (0.05, 79) | 0.10977 | 0.0872304 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 4.64983e-19 | 0.110742 | [0.147 0.853] | 0.197 |
+| (0.05, 80) | 0.110754 | 0.0802464 | 0.191 | [0.141 0.809 0. 0.05 ] | 0.110011 | 6.39424e-18 | 0.110011 | [0.141 0.859] | 0.191 |
+| (0.05, 81) | 0.156431 | 0.041569 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 7.35924e-18 | 0.110865 | [0.148 0.852] | 0.198 |
+| (0.05, 82) | 0.154779 | 0.0442212 | 0.199 | [0.149 0.801 0. 0.05 ] | 0.110988 | 6.42816e-10 | 0.110988 | [0.149 0.851] | 0.199 |
+| (0.05, 83) | 0.126509 | 0.0814906 | 0.208 | [0.158 0.792 0. 0.05 ] | 0.112108 | 1.30576e-17 | 0.112108 | [0.158 0.842] | 0.208 |
+| (0.05, 84) | 0.136929 | 0.0700712 | 0.207 | [0.158 0.792 0.001 0.049] | 0.109989 | 1.45571e-22 | 0.109989 | [0.159 0.841] | 0.207 |
+| (0.05, 85) | 0.150736 | 0.0462638 | 0.197 | [0.147 0.803 0. 0.05 ] | 0.110742 | 1.26775e-15 | 0.110742 | [0.147 0.853] | 0.197 |
+| (0.05, 86) | 0.13535 | 0.0666503 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111359 | 1.52258e-16 | 0.111359 | [0.152 0.848] | 0.202 |
+| (0.05, 87) | 0.154934 | 0.0240656 | 0.179 | [0.129 0.821 0. 0.05 ] | 0.108578 | 7.65988e-15 | 0.108578 | [0.129 0.871] | 0.179 |
+| (0.05, 88) | 0.107502 | 0.0654985 | 0.173 | [0.123 0.827 0. 0.05 ] | 0.107875 | 1.44443e-19 | 0.107875 | [0.123 0.877] | 0.173 |
+| (0.05, 89) | 0.148545 | 0.0474553 | 0.196 | [0.146 0.804 0. 0.05 ] | 0.110619 | 1.7763e-27 | 0.110619 | [0.146 0.854] | 0.196 |
+| (0.05, 90) | 0.118629 | 0.0533714 | 0.172 | [0.122 0.828 0. 0.05 ] | 0.107759 | 1.68968e-12 | 0.107759 | [0.122 0.878] | 0.172 |
+| (0.05, 91) | 0.120002 | 0.0739985 | 0.194 | [0.144 0.806 0. 0.05 ] | 0.110375 | 2.31969e-15 | 0.110375 | [0.144 0.856] | 0.194 |
+| (0.05, 92) | 0.11476 | 0.0782402 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 3.75623e-20 | 0.110254 | [0.143 0.857] | 0.193 |
+| (0.05, 93) | 0.128018 | 0.0719818 | 0.2 | [0.15 0.8 0. 0.05] | 0.111111 | 3.18359e-20 | 0.111111 | [0.15 0.85] | 0.2 |
+| (0.05, 94) | 0.104735 | 0.0972647 | 0.202 | [0.152 0.798 0. 0.05 ] | 0.111359 | 4.15272e-22 | 0.111359 | [0.152 0.848] | 0.202 |
+| (0.05, 95) | 0.14863 | 0.0313704 | 0.18 | [0.13 0.82 0. 0.05] | 0.108696 | 5.0643e-17 | 0.108696 | [0.13 0.87] | 0.18 |
+| (0.05, 96) | 0.155999 | 0.0390008 | 0.195 | [0.145 0.805 0. 0.05 ] | 0.110497 | 3.38826e-17 | 0.110497 | [0.145 0.855] | 0.195 |
+| (0.05, 97) | 0.121559 | 0.0774405 | 0.199 | [0.149 0.801 0. 0.05 ] | 0.110988 | 8.6301e-15 | 0.110988 | [0.149 0.851] | 0.199 |
+| (0.05, 98) | 0.107171 | 0.0908294 | 0.198 | [0.148 0.802 0. 0.05 ] | 0.110865 | 2.90772e-18 | 0.110865 | [0.148 0.852] | 0.198 |
+| (0.05, 99) | 0.155625 | 0.0373746 | 0.193 | [0.143 0.807 0. 0.05 ] | 0.110254 | 2.24989e-10 | 0.110254 | [0.143 0.857] | 0.193 |
+| (0.1, 0) | 0.178993 | 0.0430075 | 0.222 | [0.122 0.778 0. 0.1 ] | 0.144324 | 0.0601746 | 0.204499 | [0.122 0.878] | 0.222 |
+| (0.1, 1) | 0.152454 | 0.0715457 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.143947 | 0.0609715 | 0.204918 | [0.124 0.876] | 0.224 |
+| (0.1, 2) | 0.157962 | 0.0720383 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.189546 | 0.0166395 | 0.206186 | [0.13 0.87] | 0.23 |
+| (0.1, 3) | 0.140091 | 0.103909 | 0.244 | [0.144 0.756 0. 0.1 ] | 0.16705 | 0.042155 | 0.209205 | [0.144 0.856] | 0.244 |
+| (0.1, 4) | 0.146193 | 0.0908066 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.144253 | 0.063431 | 0.207684 | [0.137 0.863] | 0.237 |
+| (0.1, 5) | 0.149072 | 0.0789285 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.166733 | 0.0390282 | 0.205761 | [0.128 0.872] | 0.228 |
+| (0.1, 6) | 0.138868 | 0.0971322 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.146507 | 0.0609615 | 0.207469 | [0.136 0.864] | 0.236 |
+| (0.1, 7) | 0.155198 | 0.0728022 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.166977 | 0.0387839 | 0.205761 | [0.128 0.872] | 0.228 |
+| (0.1, 8) | 0.155993 | 0.0650068 | 0.221 | [0.121 0.779 0. 0.1 ] | 0.142876 | 0.0614141 | 0.20429 | [0.121 0.879] | 0.221 |
+| (0.1, 9) | 0.142102 | 0.0838979 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.161065 | 0.0442743 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 10) | 0.173001 | 0.0689987 | 0.242 | [0.142 0.758 0. 0.1 ] | 0.158182 | 0.0505862 | 0.208768 | [0.142 0.858] | 0.242 |
+| (0.1, 11) | 0.137157 | 0.114843 | 0.252 | [0.152 0.748 0. 0.1 ] | 0.17158 | 0.0393908 | 0.21097 | [0.152 0.848] | 0.252 |
+| (0.1, 12) | 0.139662 | 0.103338 | 0.243 | [0.143 0.757 0. 0.1 ] | 0.138507 | 0.0704791 | 0.208986 | [0.143 0.857] | 0.243 |
+| (0.1, 13) | 0.158423 | 0.0895769 | 0.248 | [0.149 0.751 0.001 0.099] | 0.190184 | 0.0182375 | 0.208421 | [0.15 0.85] | 0.248 |
+| (0.1, 14) | 0.12466 | 0.10934 | 0.234 | [0.134 0.766 0. 0.1 ] | 0.139225 | 0.0678139 | 0.207039 | [0.134 0.866] | 0.234 |
+| (0.1, 15) | 0.159436 | 0.0755636 | 0.235 | [0.135 0.765 0. 0.1 ] | 0.136966 | 0.0702877 | 0.207254 | [0.135 0.865] | 0.235 |
+| (0.1, 16) | 0.140571 | 0.0874287 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.1321 | 0.073661 | 0.205761 | [0.128 0.872] | 0.228 |
+| (0.1, 17) | 0.133351 | 0.0936495 | 0.227 | [0.127 0.773 0. 0.1 ] | 0.145652 | 0.0598978 | 0.20555 | [0.127 0.873] | 0.227 |
+| (0.1, 18) | 0.153178 | 0.074822 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.15928 | 0.0464809 | 0.205761 | [0.128 0.872] | 0.228 |
+| (0.1, 19) | 0.16243 | 0.0635701 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.14073 | 0.0646092 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 20) | 0.162509 | 0.0814913 | 0.244 | [0.144 0.756 0. 0.1 ] | 0.160787 | 0.0484177 | 0.209205 | [0.144 0.856] | 0.244 |
+| (0.1, 21) | 0.122019 | 0.109981 | 0.232 | [0.133 0.767 0.001 0.099] | 0.146363 | 0.058606 | 0.204969 | [0.134 0.866] | 0.232 |
+| (0.1, 22) | 0.164098 | 0.0729024 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.142794 | 0.0648901 | 0.207684 | [0.137 0.863] | 0.237 |
+| (0.1, 23) | 0.13655 | 0.10945 | 0.246 | [0.146 0.754 0. 0.1 ] | 0.133593 | 0.0760508 | 0.209644 | [0.146 0.854] | 0.246 |
+| (0.1, 24) | 0.156787 | 0.0702127 | 0.227 | [0.127 0.773 0. 0.1 ] | 0.162406 | 0.0431439 | 0.20555 | [0.127 0.873] | 0.227 |
+| (0.1, 25) | 0.142566 | 0.103434 | 0.246 | [0.146 0.754 0. 0.1 ] | 0.161656 | 0.0479876 | 0.209644 | [0.146 0.854] | 0.246 |
+| (0.1, 26) | 0.16276 | 0.0772395 | 0.24 | [0.14 0.76 0. 0.1 ] | 0.128966 | 0.0793677 | 0.208333 | [0.14 0.86] | 0.24 |
+| (0.1, 27) | 0.125019 | 0.0889812 | 0.214 | [0.114 0.786 0. 0.1 ] | 0.169924 | 0.0329159 | 0.20284 | [0.114 0.886] | 0.214 |
+| (0.1, 28) | 0.141623 | 0.101377 | 0.243 | [0.143 0.757 0. 0.1 ] | 0.131695 | 0.077291 | 0.208986 | [0.143 0.857] | 0.243 |
+| (0.1, 29) | 0.196429 | 0.0525706 | 0.249 | [0.149 0.751 0. 0.1 ] | 0.155012 | 0.0552926 | 0.210305 | [0.149 0.851] | 0.249 |
+| (0.1, 30) | 0.14666 | 0.10034 | 0.247 | [0.147 0.753 0. 0.1 ] | 0.134494 | 0.0753696 | 0.209864 | [0.147 0.853] | 0.247 |
+| (0.1, 31) | 0.138889 | 0.111111 | 0.25 | [0.151 0.749 0.001 0.099] | 0.122134 | 0.0867272 | 0.208861 | [0.152 0.848] | 0.25 |
+| (0.1, 32) | 0.14235 | 0.10065 | 0.243 | [0.144 0.756 0.001 0.099] | 0.125462 | 0.0818674 | 0.20733 | [0.145 0.855] | 0.243 |
+| (0.1, 33) | 0.149198 | 0.0748024 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.138851 | 0.0660671 | 0.204918 | [0.124 0.876] | 0.224 |
+| (0.1, 34) | 0.183632 | 0.0423683 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.165968 | 0.0393708 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 35) | 0.109742 | 0.131258 | 0.241 | [0.141 0.759 0. 0.1 ] | 0.124891 | 0.0836592 | 0.208551 | [0.141 0.859] | 0.241 |
+| (0.1, 36) | 0.119279 | 0.103721 | 0.223 | [0.123 0.777 0. 0.1 ] | 0.158427 | 0.0462817 | 0.204708 | [0.123 0.877] | 0.223 |
+| (0.1, 37) | 0.176492 | 0.0365084 | 0.213 | [0.113 0.787 0. 0.1 ] | 0.158593 | 0.0440417 | 0.202634 | [0.113 0.887] | 0.213 |
+| (0.1, 38) | 0.13036 | 0.09864 | 0.229 | [0.129 0.771 0. 0.1 ] | 0.151765 | 0.0542087 | 0.205973 | [0.129 0.871] | 0.229 |
+| (0.1, 39) | 0.143694 | 0.0773055 | 0.221 | [0.121 0.779 0. 0.1 ] | 0.152654 | 0.0516359 | 0.20429 | [0.121 0.879] | 0.221 |
+| (0.1, 40) | 0.176925 | 0.0620751 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.173127 | 0.0349899 | 0.208117 | [0.139 0.861] | 0.239 |
+| (0.1, 41) | 0.161501 | 0.0714994 | 0.233 | [0.133 0.767 0. 0.1 ] | 0.141467 | 0.0653583 | 0.206825 | [0.133 0.867] | 0.233 |
+| (0.1, 42) | 0.174647 | 0.0573527 | 0.232 | [0.133 0.767 0.001 0.099] | 0.163408 | 0.0415608 | 0.204969 | [0.134 0.866] | 0.232 |
+| (0.1, 43) | 0.167175 | 0.0718247 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.144039 | 0.0640772 | 0.208117 | [0.139 0.861] | 0.239 |
+| (0.1, 44) | 0.178495 | 0.0705051 | 0.249 | [0.149 0.751 0. 0.1 ] | 0.167393 | 0.0429116 | 0.210305 | [0.149 0.851] | 0.249 |
+| (0.1, 45) | 0.136153 | 0.0988467 | 0.235 | [0.135 0.765 0. 0.1 ] | 0.143173 | 0.0640808 | 0.207254 | [0.135 0.865] | 0.235 |
+| (0.1, 46) | 0.160061 | 0.0699394 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.160817 | 0.045369 | 0.206186 | [0.13 0.87] | 0.23 |
+| (0.1, 47) | 0.14961 | 0.0743897 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.125738 | 0.07918 | 0.204918 | [0.124 0.876] | 0.224 |
+| (0.1, 48) | 0.151283 | 0.0817166 | 0.233 | [0.133 0.767 0. 0.1 ] | 0.15867 | 0.0481552 | 0.206825 | [0.133 0.867] | 0.233 |
+| (0.1, 49) | 0.104849 | 0.132151 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.145601 | 0.062083 | 0.207684 | [0.137 0.863] | 0.237 |
+| (0.1, 50) | 0.137846 | 0.0781539 | 0.216 | [0.116 0.784 0. 0.1 ] | 0.159667 | 0.0435852 | 0.203252 | [0.116 0.884] | 0.216 |
+| (0.1, 51) | 0.165942 | 0.066058 | 0.232 | [0.132 0.768 0. 0.1 ] | 0.172122 | 0.0344898 | 0.206612 | [0.132 0.868] | 0.232 |
+| (0.1, 52) | 0.171149 | 0.042851 | 0.214 | [0.114 0.786 0. 0.1 ] | 0.162734 | 0.0401054 | 0.20284 | [0.114 0.886] | 0.214 |
+| (0.1, 53) | 0.154402 | 0.0895978 | 0.244 | [0.144 0.756 0. 0.1 ] | 0.145084 | 0.0641207 | 0.209205 | [0.144 0.856] | 0.244 |
+| (0.1, 54) | 0.142341 | 0.0896587 | 0.232 | [0.132 0.768 0. 0.1 ] | 0.15741 | 0.0492015 | 0.206612 | [0.132 0.868] | 0.232 |
+| (0.1, 55) | 0.125124 | 0.120876 | 0.246 | [0.146 0.754 0. 0.1 ] | 0.152008 | 0.0576355 | 0.209644 | [0.146 0.854] | 0.246 |
+| (0.1, 56) | 0.123448 | 0.106552 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.142112 | 0.0640739 | 0.206186 | [0.13 0.87] | 0.23 |
+| (0.1, 57) | 0.142486 | 0.0985143 | 0.241 | [0.142 0.758 0.001 0.099] | 0.172454 | 0.0344422 | 0.206897 | [0.143 0.857] | 0.241 |
+| (0.1, 58) | 0.1401 | 0.0999001 | 0.24 | [0.14 0.76 0. 0.1 ] | 0.162622 | 0.0457112 | 0.208333 | [0.14 0.86] | 0.24 |
+| (0.1, 59) | 0.136005 | 0.0989948 | 0.235 | [0.135 0.765 0. 0.1 ] | 0.113088 | 0.0941657 | 0.207254 | [0.135 0.865] | 0.235 |
+| (0.1, 60) | 0.164363 | 0.0656372 | 0.23 | [0.132 0.768 0.002 0.098] | 0.144721 | 0.0581779 | 0.202899 | [0.134 0.866] | 0.23 |
+| (0.1, 61) | 0.147789 | 0.102211 | 0.25 | [0.15 0.75 0. 0.1 ] | 0.120903 | 0.0896233 | 0.210526 | [0.15 0.85] | 0.25 |
+| (0.1, 62) | 0.171044 | 0.0549561 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.178233 | 0.0271061 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 63) | 0.163507 | 0.0704927 | 0.234 | [0.134 0.766 0. 0.1 ] | 0.158086 | 0.048953 | 0.207039 | [0.134 0.866] | 0.234 |
+| (0.1, 64) | 0.110106 | 0.136894 | 0.247 | [0.147 0.753 0. 0.1 ] | 0.131224 | 0.07864 | 0.209864 | [0.147 0.853] | 0.247 |
+| (0.1, 65) | 0.116124 | 0.113876 | 0.23 | [0.132 0.768 0.002 0.098] | 0.160052 | 0.0428462 | 0.202899 | [0.134 0.866] | 0.23 |
+| (0.1, 66) | 0.148545 | 0.0964552 | 0.245 | [0.145 0.755 0. 0.1 ] | 0.153694 | 0.0557301 | 0.209424 | [0.145 0.855] | 0.245 |
+| (0.1, 67) | 0.147949 | 0.0880511 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.120853 | 0.086616 | 0.207469 | [0.136 0.864] | 0.236 |
+| (0.1, 68) | 0.159105 | 0.066895 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.166105 | 0.0392333 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 69) | 0.133635 | 0.0993651 | 0.233 | [0.133 0.767 0. 0.1 ] | 0.13905 | 0.0677752 | 0.206825 | [0.133 0.867] | 0.233 |
+| (0.1, 70) | 0.136221 | 0.0947786 | 0.231 | [0.131 0.769 0. 0.1 ] | 0.158557 | 0.0478413 | 0.206398 | [0.131 0.869] | 0.231 |
+| (0.1, 71) | 0.173515 | 0.0564854 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.154365 | 0.0518201 | 0.206186 | [0.13 0.87] | 0.23 |
+| (0.1, 72) | 0.16392 | 0.0540796 | 0.218 | [0.118 0.782 0. 0.1 ] | 0.145843 | 0.0578235 | 0.203666 | [0.118 0.882] | 0.218 |
+| (0.1, 73) | 0.15042 | 0.0985805 | 0.249 | [0.149 0.751 0. 0.1 ] | 0.160302 | 0.0500027 | 0.210305 | [0.149 0.851] | 0.249 |
+| (0.1, 74) | 0.162813 | 0.0761868 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.158843 | 0.0492734 | 0.208117 | [0.139 0.861] | 0.239 |
+| (0.1, 75) | 0.13747 | 0.10053 | 0.238 | [0.138 0.762 0. 0.1 ] | 0.161175 | 0.046725 | 0.2079 | [0.138 0.862] | 0.238 |
+| (0.1, 76) | 0.145291 | 0.0577093 | 0.203 | [0.103 0.797 0. 0.1 ] | 0.149275 | 0.0513268 | 0.200602 | [0.103 0.897] | 0.203 |
+| (0.1, 77) | 0.162521 | 0.0464792 | 0.209 | [0.109 0.791 0. 0.1 ] | 0.160017 | 0.041799 | 0.201816 | [0.109 0.891] | 0.209 |
+| (0.1, 78) | 0.173875 | 0.0691247 | 0.243 | [0.143 0.757 0. 0.1 ] | 0.172443 | 0.0365437 | 0.208986 | [0.143 0.857] | 0.243 |
+| (0.1, 79) | 0.167891 | 0.0681092 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.164834 | 0.0426348 | 0.207469 | [0.136 0.864] | 0.236 |
+| (0.1, 80) | 0.105674 | 0.122326 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.141365 | 0.0643962 | 0.205761 | [0.128 0.872] | 0.228 |
+| (0.1, 81) | 0.146952 | 0.0890479 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.146061 | 0.0614083 | 0.207469 | [0.136 0.864] | 0.236 |
+| (0.1, 82) | 0.161609 | 0.0743909 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.157538 | 0.0499308 | 0.207469 | [0.136 0.864] | 0.236 |
+| (0.1, 83) | 0.133117 | 0.103883 | 0.237 | [0.137 0.763 0. 0.1 ] | 0.140087 | 0.0675969 | 0.207684 | [0.137 0.863] | 0.237 |
+| (0.1, 84) | 0.105845 | 0.133155 | 0.239 | [0.139 0.761 0. 0.1 ] | 0.134486 | 0.0736308 | 0.208117 | [0.139 0.861] | 0.239 |
+| (0.1, 85) | 0.149457 | 0.0795428 | 0.229 | [0.129 0.771 0. 0.1 ] | 0.152163 | 0.05381 | 0.205973 | [0.129 0.871] | 0.229 |
+| (0.1, 86) | 0.155383 | 0.075617 | 0.231 | [0.131 0.769 0. 0.1 ] | 0.142288 | 0.0641102 | 0.206398 | [0.131 0.869] | 0.231 |
+| (0.1, 87) | 0.152283 | 0.0677166 | 0.22 | [0.12 0.78 0. 0.1 ] | 0.136019 | 0.0680626 | 0.204082 | [0.12 0.88] | 0.22 |
+| (0.1, 88) | 0.155228 | 0.0857723 | 0.241 | [0.141 0.759 0. 0.1 ] | 0.159894 | 0.0486562 | 0.208551 | [0.141 0.859] | 0.241 |
+| (0.1, 89) | 0.173025 | 0.0519748 | 0.225 | [0.125 0.775 0. 0.1 ] | 0.149647 | 0.0554812 | 0.205128 | [0.125 0.875] | 0.225 |
+| (0.1, 90) | 0.161536 | 0.0644643 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.164452 | 0.0408866 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 91) | 0.19674 | 0.0392595 | 0.236 | [0.136 0.764 0. 0.1 ] | 0.152299 | 0.0551697 | 0.207469 | [0.136 0.864] | 0.236 |
+| (0.1, 92) | 0.1473 | 0.0766998 | 0.224 | [0.124 0.776 0. 0.1 ] | 0.125015 | 0.0799031 | 0.204918 | [0.124 0.876] | 0.224 |
+| (0.1, 93) | 0.157492 | 0.0725084 | 0.23 | [0.13 0.77 0. 0.1 ] | 0.161964 | 0.0442218 | 0.206186 | [0.13 0.87] | 0.23 |
+| (0.1, 94) | 0.166779 | 0.0672206 | 0.234 | [0.134 0.766 0. 0.1 ] | 0.168283 | 0.0387559 | 0.207039 | [0.134 0.866] | 0.234 |
+| (0.1, 95) | 0.170211 | 0.0797889 | 0.25 | [0.15 0.75 0. 0.1 ] | 0.151857 | 0.0586692 | 0.210526 | [0.15 0.85] | 0.25 |
+| (0.1, 96) | 0.137124 | 0.0808765 | 0.218 | [0.118 0.782 0. 0.1 ] | 0.154015 | 0.0496513 | 0.203666 | [0.118 0.882] | 0.218 |
+| (0.1, 97) | 0.153298 | 0.0727017 | 0.226 | [0.126 0.774 0. 0.1 ] | 0.165413 | 0.0399255 | 0.205339 | [0.126 0.874] | 0.226 |
+| (0.1, 98) | 0.141298 | 0.120702 | 0.262 | [0.162 0.738 0. 0.1 ] | 0.135892 | 0.0773272 | 0.21322 | [0.162 0.838] | 0.262 |
+| (0.1, 99) | 0.175225 | 0.0527751 | 0.228 | [0.128 0.772 0. 0.1 ] | 0.16037 | 0.045391 | 0.205761 | [0.128 0.872] | 0.228 |
+| (0.15, 0) | 0.1203 | 0.1657 | 0.286 | [0.137 0.713 0.001 0.149] | 0.127121 | 0.167346 | 0.294466 | [0.138 0.862] | 0.286 |
+| (0.15, 1) | 0.119526 | 0.167474 | 0.287 | [0.137 0.713 0. 0.15 ] | 0.135734 | 0.160416 | 0.29615 | [0.137 0.863] | 0.287 |
+| (0.15, 2) | 0.137288 | 0.133712 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.123291 | 0.168254 | 0.291545 | [0.121 0.879] | 0.271 |
+| (0.15, 3) | 0.142731 | 0.113269 | 0.256 | [0.106 0.744 0. 0.15 ] | 0.13131 | 0.156047 | 0.287356 | [0.106 0.894] | 0.256 |
+| (0.15, 4) | 0.166618 | 0.105382 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.161107 | 0.130722 | 0.291829 | [0.122 0.878] | 0.272 |
+| (0.15, 5) | 0.139421 | 0.139579 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.176782 | 0.117048 | 0.29383 | [0.129 0.871] | 0.279 |
+| (0.15, 6) | 0.170222 | 0.099778 | 0.27 | [0.12 0.73 0. 0.15] | 0.148121 | 0.143141 | 0.291262 | [0.12 0.88] | 0.27 |
+| (0.15, 7) | 0.158061 | 0.114939 | 0.273 | [0.123 0.727 0. 0.15 ] | 0.176748 | 0.115365 | 0.292113 | [0.123 0.877] | 0.273 |
+| (0.15, 8) | 0.17871 | 0.11629 | 0.295 | [0.145 0.705 0. 0.15 ] | 0.132824 | 0.165683 | 0.298507 | [0.145 0.855] | 0.295 |
+| (0.15, 9) | 0.151538 | 0.119462 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.149422 | 0.142123 | 0.291545 | [0.121 0.879] | 0.271 |
+| (0.15, 10) | 0.139049 | 0.130951 | 0.27 | [0.121 0.729 0.001 0.149] | 0.13676 | 0.153123 | 0.289883 | [0.122 0.878] | 0.27 |
+| (0.15, 11) | 0.116244 | 0.156756 | 0.273 | [0.124 0.726 0.001 0.149] | 0.141815 | 0.148916 | 0.290732 | [0.125 0.875] | 0.273 |
+| (0.15, 12) | 0.162998 | 0.126002 | 0.289 | [0.139 0.711 0. 0.15 ] | 0.156127 | 0.140609 | 0.296736 | [0.139 0.861] | 0.289 |
+| (0.15, 13) | 0.128238 | 0.150762 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.134349 | 0.159481 | 0.29383 | [0.129 0.871] | 0.279 |
+| (0.15, 14) | 0.117776 | 0.132224 | 0.25 | [0.1 0.75 0. 0.15] | 0.139297 | 0.146418 | 0.285714 | [0.1 0.9] | 0.25 |
+| (0.15, 15) | 0.104416 | 0.179584 | 0.284 | [0.134 0.716 0. 0.15 ] | 0.131122 | 0.164154 | 0.295276 | [0.134 0.866] | 0.284 |
+| (0.15, 16) | 0.137068 | 0.134932 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.166223 | 0.125605 | 0.291829 | [0.122 0.878] | 0.272 |
+| (0.15, 17) | 0.158429 | 0.111571 | 0.27 | [0.12 0.73 0. 0.15] | 0.17491 | 0.116352 | 0.291262 | [0.12 0.88] | 0.27 |
+| (0.15, 18) | 0.168285 | 0.0947153 | 0.263 | [0.113 0.737 0. 0.15 ] | 0.173726 | 0.11557 | 0.289296 | [0.113 0.887] | 0.263 |
+| (0.15, 19) | 0.171027 | 0.120973 | 0.292 | [0.142 0.708 0. 0.15 ] | 0.142831 | 0.154788 | 0.297619 | [0.142 0.858] | 0.292 |
+| (0.15, 20) | 0.148659 | 0.131341 | 0.28 | [0.13 0.72 0. 0.15] | 0.155957 | 0.138161 | 0.294118 | [0.13 0.87] | 0.28 |
+| (0.15, 21) | 0.110694 | 0.147306 | 0.258 | [0.108 0.742 0. 0.15 ] | 0.132425 | 0.155482 | 0.287908 | [0.108 0.892] | 0.258 |
+| (0.15, 22) | 0.13145 | 0.14855 | 0.28 | [0.13 0.72 0. 0.15] | 0.134374 | 0.159744 | 0.294118 | [0.13 0.87] | 0.28 |
+| (0.15, 23) | 0.146038 | 0.126962 | 0.273 | [0.123 0.727 0. 0.15 ] | 0.130698 | 0.161415 | 0.292113 | [0.123 0.877] | 0.273 |
+| (0.15, 24) | 0.181347 | 0.108653 | 0.29 | [0.141 0.709 0.001 0.149] | 0.149705 | 0.14593 | 0.295635 | [0.142 0.858] | 0.29 |
+| (0.15, 25) | 0.146943 | 0.144057 | 0.291 | [0.141 0.709 0. 0.15 ] | 0.136203 | 0.161121 | 0.297324 | [0.141 0.859] | 0.291 |
+| (0.15, 26) | 0.147795 | 0.116205 | 0.264 | [0.114 0.736 0. 0.15 ] | 0.157537 | 0.132038 | 0.289575 | [0.114 0.886] | 0.264 |
+| (0.15, 27) | 0.128014 | 0.138986 | 0.267 | [0.117 0.733 0. 0.15 ] | 0.148528 | 0.141888 | 0.290416 | [0.117 0.883] | 0.267 |
+| (0.15, 28) | 0.143207 | 0.128793 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.138262 | 0.153567 | 0.291829 | [0.122 0.878] | 0.272 |
+| (0.15, 29) | 0.148872 | 0.145128 | 0.294 | [0.144 0.706 0. 0.15 ] | 0.135484 | 0.162727 | 0.298211 | [0.144 0.856] | 0.294 |
+| (0.15, 30) | 0.144965 | 0.113035 | 0.258 | [0.108 0.742 0. 0.15 ] | 0.147562 | 0.140346 | 0.287908 | [0.108 0.892] | 0.258 |
+| (0.15, 31) | 0.145971 | 0.119029 | 0.265 | [0.115 0.735 0. 0.15 ] | 0.161121 | 0.128734 | 0.289855 | [0.115 0.885] | 0.265 |
+| (0.15, 32) | 0.137751 | 0.124249 | 0.262 | [0.113 0.737 0.001 0.149] | 0.145534 | 0.142111 | 0.287645 | [0.114 0.886] | 0.262 |
+| (0.15, 33) | 0.11238 | 0.15762 | 0.27 | [0.12 0.73 0. 0.15] | 0.130286 | 0.160976 | 0.291262 | [0.12 0.88] | 0.27 |
+| (0.15, 34) | 0.0966508 | 0.179349 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.117277 | 0.175692 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 35) | 0.157902 | 0.113098 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.152535 | 0.13901 | 0.291545 | [0.121 0.879] | 0.271 |
+| (0.15, 36) | 0.125849 | 0.166151 | 0.292 | [0.142 0.708 0. 0.15 ] | 0.15111 | 0.146509 | 0.297619 | [0.142 0.858] | 0.292 |
+| (0.15, 37) | 0.167764 | 0.137236 | 0.305 | [0.155 0.695 0. 0.15 ] | 0.179681 | 0.121826 | 0.301508 | [0.155 0.845] | 0.305 |
+| (0.15, 38) | 0.154211 | 0.128789 | 0.283 | [0.133 0.717 0. 0.15 ] | 0.166432 | 0.128554 | 0.294985 | [0.133 0.867] | 0.283 |
+| (0.15, 39) | 0.132705 | 0.143295 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.14616 | 0.146809 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 40) | 0.152512 | 0.123488 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.141054 | 0.151915 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 41) | 0.135058 | 0.127942 | 0.263 | [0.113 0.737 0. 0.15 ] | 0.16119 | 0.128106 | 0.289296 | [0.113 0.887] | 0.263 |
+| (0.15, 42) | 0.123784 | 0.152216 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.142844 | 0.150125 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 43) | 0.171101 | 0.0878989 | 0.259 | [0.109 0.741 0. 0.15 ] | 0.164715 | 0.123469 | 0.288184 | [0.109 0.891] | 0.259 |
+| (0.15, 44) | 0.16704 | 0.0949603 | 0.262 | [0.114 0.736 0.002 0.148] | 0.142699 | 0.143568 | 0.286267 | [0.116 0.884] | 0.262 |
+| (0.15, 45) | 0.116311 | 0.171689 | 0.288 | [0.138 0.712 0. 0.15 ] | 0.141653 | 0.15479 | 0.296443 | [0.138 0.862] | 0.288 |
+| (0.15, 46) | 0.154616 | 0.104384 | 0.259 | [0.109 0.741 0. 0.15 ] | 0.138548 | 0.149637 | 0.288184 | [0.109 0.891] | 0.259 |
+| (0.15, 47) | 0.144754 | 0.133246 | 0.278 | [0.128 0.722 0. 0.15 ] | 0.12734 | 0.166202 | 0.293542 | [0.128 0.872] | 0.278 |
+| (0.15, 48) | 0.175836 | 0.110164 | 0.286 | [0.136 0.714 0. 0.15 ] | 0.153911 | 0.141947 | 0.295858 | [0.136 0.864] | 0.286 |
+| (0.15, 49) | 0.162022 | 0.111978 | 0.274 | [0.124 0.726 0. 0.15 ] | 0.150176 | 0.142221 | 0.292398 | [0.124 0.876] | 0.274 |
+| (0.15, 50) | 0.177202 | 0.0937983 | 0.271 | [0.121 0.729 0. 0.15 ] | 0.158743 | 0.132803 | 0.291545 | [0.121 0.879] | 0.271 |
+| (0.15, 51) | 0.153076 | 0.111924 | 0.265 | [0.115 0.735 0. 0.15 ] | 0.134545 | 0.15531 | 0.289855 | [0.115 0.885] | 0.265 |
+| (0.15, 52) | 0.138063 | 0.151937 | 0.29 | [0.14 0.71 0. 0.15] | 0.137941 | 0.159089 | 0.29703 | [0.14 0.86] | 0.29 |
+| (0.15, 53) | 0.153557 | 0.122443 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.132467 | 0.160502 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 54) | 0.151345 | 0.114655 | 0.266 | [0.116 0.734 0. 0.15 ] | 0.138179 | 0.151956 | 0.290135 | [0.116 0.884] | 0.266 |
+| (0.15, 55) | 0.13427 | 0.14873 | 0.283 | [0.133 0.717 0. 0.15 ] | 0.157275 | 0.137711 | 0.294985 | [0.133 0.867] | 0.283 |
+| (0.15, 56) | 0.137219 | 0.134781 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.158478 | 0.133351 | 0.291829 | [0.122 0.878] | 0.272 |
+| (0.15, 57) | 0.160927 | 0.140073 | 0.301 | [0.151 0.699 0. 0.15 ] | 0.146971 | 0.153329 | 0.3003 | [0.151 0.849] | 0.301 |
+| (0.15, 58) | 0.120219 | 0.163781 | 0.284 | [0.134 0.716 0. 0.15 ] | 0.145434 | 0.149842 | 0.295276 | [0.134 0.866] | 0.284 |
+| (0.15, 59) | 0.154083 | 0.126917 | 0.281 | [0.131 0.719 0. 0.15 ] | 0.154977 | 0.139429 | 0.294406 | [0.131 0.869] | 0.281 |
+| (0.15, 60) | 0.157883 | 0.111117 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.172352 | 0.118627 | 0.29098 | [0.119 0.881] | 0.269 |
+| (0.15, 61) | 0.136203 | 0.143797 | 0.28 | [0.13 0.72 0. 0.15] | 0.156749 | 0.137369 | 0.294118 | [0.13 0.87] | 0.28 |
+| (0.15, 62) | 0.121822 | 0.177178 | 0.299 | [0.149 0.701 0. 0.15 ] | 0.158284 | 0.141416 | 0.2997 | [0.149 0.851] | 0.299 |
+| (0.15, 63) | 0.134564 | 0.151436 | 0.286 | [0.136 0.714 0. 0.15 ] | 0.122765 | 0.173093 | 0.295858 | [0.136 0.864] | 0.286 |
+| (0.15, 64) | 0.138566 | 0.136434 | 0.275 | [0.125 0.725 0. 0.15 ] | 0.164812 | 0.127871 | 0.292683 | [0.125 0.875] | 0.275 |
+| (0.15, 65) | 0.141594 | 0.132406 | 0.274 | [0.125 0.725 0.001 0.149] | 0.130073 | 0.160943 | 0.291016 | [0.126 0.874] | 0.274 |
+| (0.15, 66) | 0.144607 | 0.135393 | 0.28 | [0.13 0.72 0. 0.15] | 0.119498 | 0.174619 | 0.294118 | [0.13 0.87] | 0.28 |
+| (0.15, 67) | 0.178893 | 0.090107 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.171713 | 0.119267 | 0.29098 | [0.119 0.881] | 0.269 |
+| (0.15, 68) | 0.139628 | 0.145372 | 0.285 | [0.135 0.715 0. 0.15 ] | 0.135852 | 0.159714 | 0.295567 | [0.135 0.865] | 0.285 |
+| (0.15, 69) | 0.1838 | 0.0922 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.172546 | 0.120423 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 70) | 0.125644 | 0.138356 | 0.264 | [0.114 0.736 0. 0.15 ] | 0.160992 | 0.128583 | 0.289575 | [0.114 0.886] | 0.264 |
+| (0.15, 71) | 0.160764 | 0.101236 | 0.262 | [0.112 0.738 0. 0.15 ] | 0.161154 | 0.127864 | 0.289017 | [0.112 0.888] | 0.262 |
+| (0.15, 72) | 0.161464 | 0.107536 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.159812 | 0.131167 | 0.29098 | [0.119 0.881] | 0.269 |
+| (0.15, 73) | 0.121342 | 0.153658 | 0.275 | [0.125 0.725 0. 0.15 ] | 0.107444 | 0.185239 | 0.292683 | [0.125 0.875] | 0.275 |
+| (0.15, 74) | 0.145367 | 0.133633 | 0.279 | [0.13 0.72 0.001 0.149] | 0.129848 | 0.162596 | 0.292444 | [0.131 0.869] | 0.279 |
+| (0.15, 75) | 0.155114 | 0.117886 | 0.273 | [0.124 0.726 0.001 0.149] | 0.15948 | 0.131252 | 0.290732 | [0.125 0.875] | 0.273 |
+| (0.15, 76) | 0.1274 | 0.1606 | 0.288 | [0.138 0.712 0. 0.15 ] | 0.14193 | 0.154513 | 0.296443 | [0.138 0.862] | 0.288 |
+| (0.15, 77) | 0.152264 | 0.143736 | 0.296 | [0.146 0.704 0. 0.15 ] | 0.155979 | 0.142826 | 0.298805 | [0.146 0.854] | 0.296 |
+| (0.15, 78) | 0.10929 | 0.17271 | 0.282 | [0.132 0.718 0. 0.15 ] | 0.129038 | 0.165657 | 0.294695 | [0.132 0.868] | 0.282 |
+| (0.15, 79) | 0.1422 | 0.1328 | 0.275 | [0.125 0.725 0. 0.15 ] | 0.150535 | 0.142148 | 0.292683 | [0.125 0.875] | 0.275 |
+| (0.15, 80) | 0.168582 | 0.0974178 | 0.266 | [0.117 0.733 0.001 0.149] | 0.161824 | 0.126936 | 0.28876 | [0.118 0.882] | 0.266 |
+| (0.15, 81) | 0.148811 | 0.130189 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.118403 | 0.175427 | 0.29383 | [0.129 0.871] | 0.279 |
+| (0.15, 82) | 0.133344 | 0.134656 | 0.268 | [0.118 0.732 0. 0.15 ] | 0.151254 | 0.139444 | 0.290698 | [0.118 0.882] | 0.268 |
+| (0.15, 83) | 0.124459 | 0.126541 | 0.251 | [0.101 0.749 0. 0.15 ] | 0.13409 | 0.151896 | 0.285987 | [0.101 0.899] | 0.251 |
+| (0.15, 84) | 0.141318 | 0.137682 | 0.279 | [0.129 0.721 0. 0.15 ] | 0.154315 | 0.139515 | 0.29383 | [0.129 0.871] | 0.279 |
+| (0.15, 85) | 0.163049 | 0.117951 | 0.281 | [0.131 0.719 0. 0.15 ] | 0.140319 | 0.154088 | 0.294406 | [0.131 0.869] | 0.281 |
+| (0.15, 86) | 0.152419 | 0.133581 | 0.286 | [0.136 0.714 0. 0.15 ] | 0.137388 | 0.15847 | 0.295858 | [0.136 0.864] | 0.286 |
+| (0.15, 87) | 0.106809 | 0.176191 | 0.283 | [0.133 0.717 0. 0.15 ] | 0.102393 | 0.192592 | 0.294985 | [0.133 0.867] | 0.283 |
+| (0.15, 88) | 0.160406 | 0.104594 | 0.265 | [0.115 0.735 0. 0.15 ] | 0.15609 | 0.133765 | 0.289855 | [0.115 0.885] | 0.265 |
+| (0.15, 89) | 0.123011 | 0.149989 | 0.273 | [0.123 0.727 0. 0.15 ] | 0.145604 | 0.146509 | 0.292113 | [0.123 0.877] | 0.273 |
+| (0.15, 90) | 0.159302 | 0.112698 | 0.272 | [0.122 0.728 0. 0.15 ] | 0.139501 | 0.152328 | 0.291829 | [0.122 0.878] | 0.272 |
+| (0.15, 91) | 0.146535 | 0.147465 | 0.294 | [0.144 0.706 0. 0.15 ] | 0.160389 | 0.137822 | 0.298211 | [0.144 0.856] | 0.294 |
+| (0.15, 92) | 0.174056 | 0.089944 | 0.264 | [0.114 0.736 0. 0.15 ] | 0.154888 | 0.134687 | 0.289575 | [0.114 0.886] | 0.264 |
+| (0.15, 93) | 0.132952 | 0.145048 | 0.278 | [0.128 0.722 0. 0.15 ] | 0.153029 | 0.140513 | 0.293542 | [0.128 0.872] | 0.278 |
+| (0.15, 94) | 0.148742 | 0.131258 | 0.28 | [0.131 0.719 0.001 0.149] | 0.15407 | 0.138661 | 0.292731 | [0.132 0.868] | 0.28 |
+| (0.15, 95) | 0.160161 | 0.102839 | 0.263 | [0.114 0.736 0.001 0.149] | 0.135026 | 0.152896 | 0.287923 | [0.115 0.885] | 0.263 |
+| (0.15, 96) | 0.123638 | 0.160362 | 0.284 | [0.134 0.716 0. 0.15 ] | 0.138609 | 0.156667 | 0.295276 | [0.134 0.866] | 0.284 |
+| (0.15, 97) | 0.161662 | 0.105338 | 0.267 | [0.117 0.733 0. 0.15 ] | 0.146184 | 0.144233 | 0.290416 | [0.117 0.883] | 0.267 |
+| (0.15, 98) | 0.147239 | 0.128761 | 0.276 | [0.126 0.724 0. 0.15 ] | 0.165486 | 0.127483 | 0.292969 | [0.126 0.874] | 0.276 |
+| (0.15, 99) | 0.127231 | 0.141769 | 0.269 | [0.119 0.731 0. 0.15 ] | 0.137447 | 0.153533 | 0.29098 | [0.119 0.881] | 0.269 |
+| (0.2, 0) | 0.0932749 | 0.232725 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.107742 | 0.264698 | 0.372439 | [0.126 0.874] | 0.326 |
+| (0.2, 1) | 0.103595 | 0.225405 | 0.329 | [0.129 0.671 0. 0.2 ] | 0.11693 | 0.256553 | 0.373483 | [0.129 0.871] | 0.329 |
+| (0.2, 2) | 0.146266 | 0.174734 | 0.321 | [0.121 0.679 0. 0.2 ] | 0.13068 | 0.240034 | 0.370714 | [0.121 0.879] | 0.321 |
+| (0.2, 3) | 0.158612 | 0.158388 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.140197 | 0.229147 | 0.369344 | [0.117 0.883] | 0.317 |
+| (0.2, 4) | 0.13548 | 0.18852 | 0.324 | [0.125 0.675 0.001 0.199] | 0.123131 | 0.247446 | 0.370577 | [0.126 0.874] | 0.324 |
+| (0.2, 5) | 0.184383 | 0.139617 | 0.324 | [0.124 0.676 0. 0.2 ] | 0.16367 | 0.208077 | 0.371747 | [0.124 0.876] | 0.324 |
+| (0.2, 6) | 0.119201 | 0.191799 | 0.311 | [0.111 0.689 0. 0.2 ] | 0.12538 | 0.24193 | 0.367309 | [0.111 0.889] | 0.311 |
+| (0.2, 7) | 0.13074 | 0.18826 | 0.319 | [0.12 0.68 0.001 0.199] | 0.1483 | 0.22056 | 0.36886 | [0.121 0.879] | 0.319 |
+| (0.2, 8) | 0.158339 | 0.154661 | 0.313 | [0.113 0.687 0. 0.2 ] | 0.141924 | 0.226061 | 0.367985 | [0.113 0.887] | 0.313 |
+| (0.2, 9) | 0.133184 | 0.171816 | 0.305 | [0.107 0.693 0.002 0.198] | 0.155369 | 0.207601 | 0.36297 | [0.109 0.891] | 0.305 |
+| (0.2, 10) | 0.152238 | 0.170762 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.141301 | 0.230101 | 0.371402 | [0.123 0.877] | 0.323 |
+| (0.2, 11) | 0.147096 | 0.187904 | 0.335 | [0.135 0.665 0. 0.2 ] | 0.126492 | 0.249094 | 0.375587 | [0.135 0.865] | 0.335 |
+| (0.2, 12) | 0.139379 | 0.187621 | 0.327 | [0.127 0.673 0. 0.2 ] | 0.140083 | 0.232704 | 0.372787 | [0.127 0.873] | 0.327 |
+| (0.2, 13) | 0.157408 | 0.164592 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.128326 | 0.242732 | 0.371058 | [0.122 0.878] | 0.322 |
+| (0.2, 14) | 0.165325 | 0.154675 | 0.32 | [0.12 0.68 0. 0.2 ] | 0.141291 | 0.229079 | 0.37037 | [0.12 0.88] | 0.32 |
+| (0.2, 15) | 0.155916 | 0.162084 | 0.318 | [0.119 0.681 0.001 0.199] | 0.136168 | 0.232351 | 0.368519 | [0.12 0.88] | 0.318 |
+| (0.2, 16) | 0.126583 | 0.190417 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.0939205 | 0.275424 | 0.369344 | [0.117 0.883] | 0.317 |
+| (0.2, 17) | 0.132189 | 0.202811 | 0.335 | [0.135 0.665 0. 0.2 ] | 0.109183 | 0.266403 | 0.375587 | [0.135 0.865] | 0.335 |
+| (0.2, 18) | 0.129466 | 0.189534 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.115286 | 0.254741 | 0.370028 | [0.119 0.881] | 0.319 |
+| (0.2, 19) | 0.128175 | 0.177825 | 0.306 | [0.106 0.694 0. 0.2 ] | 0.133787 | 0.231843 | 0.365631 | [0.106 0.894] | 0.306 |
+| (0.2, 20) | 0.145426 | 0.187574 | 0.333 | [0.133 0.667 0. 0.2 ] | 0.151205 | 0.223677 | 0.374883 | [0.133 0.867] | 0.333 |
+| (0.2, 21) | 0.163454 | 0.154546 | 0.318 | [0.119 0.681 0.001 0.199] | 0.139559 | 0.228959 | 0.368519 | [0.12 0.88] | 0.318 |
+| (0.2, 22) | 0.114168 | 0.215832 | 0.33 | [0.131 0.669 0.001 0.199] | 0.114659 | 0.258001 | 0.372659 | [0.132 0.868] | 0.33 |
+| (0.2, 23) | 0.156559 | 0.173441 | 0.33 | [0.13 0.67 0. 0.2 ] | 0.150894 | 0.222937 | 0.373832 | [0.13 0.87] | 0.33 |
+| (0.2, 24) | 0.110103 | 0.206897 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.109295 | 0.260049 | 0.369344 | [0.117 0.883] | 0.317 |
+| (0.2, 25) | 0.153082 | 0.174918 | 0.328 | [0.128 0.672 0. 0.2 ] | 0.159335 | 0.213799 | 0.373134 | [0.128 0.872] | 0.328 |
+| (0.2, 26) | 0.126215 | 0.187785 | 0.314 | [0.114 0.686 0. 0.2 ] | 0.114362 | 0.253962 | 0.368324 | [0.114 0.886] | 0.314 |
+| (0.2, 27) | 0.145636 | 0.172364 | 0.318 | [0.118 0.682 0. 0.2 ] | 0.154729 | 0.214956 | 0.369686 | [0.118 0.882] | 0.318 |
+| (0.2, 28) | 0.113045 | 0.191955 | 0.305 | [0.105 0.695 0. 0.2 ] | 0.103814 | 0.261482 | 0.365297 | [0.105 0.895] | 0.305 |
+| (0.2, 29) | 0.151512 | 0.171488 | 0.323 | [0.124 0.676 0.001 0.199] | 0.134941 | 0.235291 | 0.370233 | [0.125 0.875] | 0.323 |
+| (0.2, 30) | 0.124049 | 0.206951 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.130243 | 0.243939 | 0.374181 | [0.131 0.869] | 0.331 |
+| (0.2, 31) | 0.14276 | 0.17924 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.147474 | 0.223583 | 0.371058 | [0.122 0.878] | 0.322 |
+| (0.2, 32) | 0.184874 | 0.137126 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.162763 | 0.208295 | 0.371058 | [0.122 0.878] | 0.322 |
+| (0.2, 33) | 0.113052 | 0.205948 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.125327 | 0.2447 | 0.370028 | [0.119 0.881] | 0.319 |
+| (0.2, 34) | 0.11022 | 0.20578 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.134172 | 0.234831 | 0.369004 | [0.116 0.884] | 0.316 |
+| (0.2, 35) | 0.15689 | 0.16811 | 0.325 | [0.125 0.675 0. 0.2 ] | 0.139515 | 0.232578 | 0.372093 | [0.125 0.875] | 0.325 |
+| (0.2, 36) | 0.12372 | 0.19828 | 0.322 | [0.123 0.677 0.001 0.199] | 0.144416 | 0.225473 | 0.369888 | [0.124 0.876] | 0.322 |
+| (0.2, 37) | 0.156173 | 0.149827 | 0.306 | [0.106 0.694 0. 0.2 ] | 0.140543 | 0.225087 | 0.365631 | [0.106 0.894] | 0.306 |
+| (0.2, 38) | 0.123178 | 0.191822 | 0.315 | [0.115 0.685 0. 0.2 ] | 0.124918 | 0.243745 | 0.368664 | [0.115 0.885] | 0.315 |
+| (0.2, 39) | 0.149818 | 0.155182 | 0.305 | [0.105 0.695 0. 0.2 ] | 0.153473 | 0.211824 | 0.365297 | [0.105 0.895] | 0.305 |
+| (0.2, 40) | 0.146996 | 0.151004 | 0.298 | [0.098 0.702 0. 0.2 ] | 0.136716 | 0.226261 | 0.362976 | [0.098 0.902] | 0.298 |
+| (0.2, 41) | 0.134983 | 0.174017 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.130812 | 0.235824 | 0.366636 | [0.109 0.891] | 0.309 |
+| (0.2, 42) | 0.130339 | 0.204661 | 0.335 | [0.135 0.665 0. 0.2 ] | 0.132934 | 0.242653 | 0.375587 | [0.135 0.865] | 0.335 |
+| (0.2, 43) | 0.131752 | 0.197248 | 0.329 | [0.129 0.671 0. 0.2 ] | 0.122563 | 0.25092 | 0.373483 | [0.129 0.871] | 0.329 |
+| (0.2, 44) | 0.104892 | 0.213108 | 0.318 | [0.118 0.682 0. 0.2 ] | 0.101844 | 0.267842 | 0.369686 | [0.118 0.882] | 0.318 |
+| (0.2, 45) | 0.108924 | 0.208076 | 0.317 | [0.118 0.682 0.001 0.199] | 0.112634 | 0.255543 | 0.368178 | [0.119 0.881] | 0.317 |
+| (0.2, 46) | 0.158723 | 0.146277 | 0.305 | [0.106 0.694 0.001 0.199] | 0.14642 | 0.217715 | 0.364135 | [0.107 0.893] | 0.305 |
+| (0.2, 47) | 0.181864 | 0.130136 | 0.312 | [0.113 0.687 0.001 0.199] | 0.162233 | 0.204249 | 0.366483 | [0.114 0.886] | 0.312 |
+| (0.2, 48) | 0.139857 | 0.177143 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.130469 | 0.238875 | 0.369344 | [0.117 0.883] | 0.317 |
+| (0.2, 49) | 0.130555 | 0.185445 | 0.316 | [0.117 0.683 0.001 0.199] | 0.129553 | 0.238285 | 0.367837 | [0.118 0.882] | 0.316 |
+| (0.2, 50) | 0.126112 | 0.184888 | 0.311 | [0.111 0.689 0. 0.2 ] | 0.116336 | 0.250973 | 0.367309 | [0.111 0.889] | 0.311 |
+| (0.2, 51) | 0.126804 | 0.189196 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.134586 | 0.234417 | 0.369004 | [0.116 0.884] | 0.316 |
+| (0.2, 52) | 0.1149 | 0.1861 | 0.301 | [0.101 0.699 0. 0.2 ] | 0.131898 | 0.232069 | 0.363967 | [0.101 0.899] | 0.301 |
+| (0.2, 53) | 0.147138 | 0.163862 | 0.311 | [0.112 0.688 0.001 0.199] | 0.130518 | 0.235628 | 0.366145 | [0.113 0.887] | 0.311 |
+| (0.2, 54) | 0.126953 | 0.204047 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.103391 | 0.270791 | 0.374181 | [0.131 0.869] | 0.331 |
+| (0.2, 55) | 0.154759 | 0.161241 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.143336 | 0.225668 | 0.369004 | [0.116 0.884] | 0.316 |
+| (0.2, 56) | 0.148069 | 0.154931 | 0.303 | [0.103 0.697 0. 0.2 ] | 0.13299 | 0.23164 | 0.364631 | [0.103 0.897] | 0.303 |
+| (0.2, 57) | 0.14951 | 0.17349 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.124754 | 0.246648 | 0.371402 | [0.123 0.877] | 0.323 |
+| (0.2, 58) | 0.124588 | 0.182412 | 0.307 | [0.107 0.693 0. 0.2 ] | 0.135337 | 0.230628 | 0.365965 | [0.107 0.893] | 0.307 |
+| (0.2, 59) | 0.106309 | 0.219691 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.124609 | 0.247831 | 0.372439 | [0.126 0.874] | 0.326 |
+| (0.2, 60) | 0.163061 | 0.148939 | 0.312 | [0.112 0.688 0. 0.2 ] | 0.125001 | 0.242646 | 0.367647 | [0.112 0.888] | 0.312 |
+| (0.2, 61) | 0.098016 | 0.220984 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.111374 | 0.258654 | 0.370028 | [0.119 0.881] | 0.319 |
+| (0.2, 62) | 0.133823 | 0.192177 | 0.326 | [0.127 0.673 0.001 0.199] | 0.138711 | 0.232558 | 0.371269 | [0.128 0.872] | 0.326 |
+| (0.2, 63) | 0.132592 | 0.193408 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.168652 | 0.203787 | 0.372439 | [0.126 0.874] | 0.326 |
+| (0.2, 64) | 0.146847 | 0.167153 | 0.314 | [0.114 0.686 0. 0.2 ] | 0.134352 | 0.233973 | 0.368324 | [0.114 0.886] | 0.314 |
+| (0.2, 65) | 0.123678 | 0.209322 | 0.333 | [0.134 0.666 0.001 0.199] | 0.139748 | 0.233961 | 0.373709 | [0.135 0.865] | 0.333 |
+| (0.2, 66) | 0.153441 | 0.166559 | 0.32 | [0.12 0.68 0. 0.2 ] | 0.168793 | 0.201578 | 0.37037 | [0.12 0.88] | 0.32 |
+| (0.2, 67) | 0.102558 | 0.206442 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.129257 | 0.237379 | 0.366636 | [0.109 0.891] | 0.309 |
+| (0.2, 68) | 0.113796 | 0.181204 | 0.295 | [0.095 0.705 0. 0.2 ] | 0.125855 | 0.236136 | 0.361991 | [0.095 0.905] | 0.295 |
+| (0.2, 69) | 0.130216 | 0.186784 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.154798 | 0.214547 | 0.369344 | [0.117 0.883] | 0.317 |
+| (0.2, 70) | 0.140137 | 0.173863 | 0.314 | [0.114 0.686 0. 0.2 ] | 0.133952 | 0.234372 | 0.368324 | [0.114 0.886] | 0.314 |
+| (0.2, 71) | 0.118374 | 0.173626 | 0.292 | [0.093 0.707 0.001 0.199] | 0.102911 | 0.256944 | 0.359855 | [0.094 0.906] | 0.292 |
+| (0.2, 72) | 0.142998 | 0.173002 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.13498 | 0.234024 | 0.369004 | [0.116 0.884] | 0.316 |
+| (0.2, 73) | 0.11727 | 0.20573 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.100748 | 0.270654 | 0.371402 | [0.123 0.877] | 0.323 |
+| (0.2, 74) | 0.13782 | 0.17518 | 0.313 | [0.114 0.686 0.001 0.199] | 0.113838 | 0.252982 | 0.36682 | [0.115 0.885] | 0.313 |
+| (0.2, 75) | 0.127086 | 0.203914 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.124813 | 0.249369 | 0.374181 | [0.131 0.869] | 0.331 |
+| (0.2, 76) | 0.110385 | 0.192615 | 0.303 | [0.104 0.696 0.001 0.199] | 0.117311 | 0.246159 | 0.36347 | [0.105 0.895] | 0.303 |
+| (0.2, 77) | 0.169946 | 0.156054 | 0.326 | [0.126 0.674 0. 0.2 ] | 0.154318 | 0.218121 | 0.372439 | [0.126 0.874] | 0.326 |
+| (0.2, 78) | 0.125895 | 0.184105 | 0.31 | [0.11 0.69 0. 0.2 ] | 0.137846 | 0.229127 | 0.366972 | [0.11 0.89] | 0.31 |
+| (0.2, 79) | 0.106497 | 0.195503 | 0.302 | [0.102 0.698 0. 0.2 ] | 0.108174 | 0.256124 | 0.364299 | [0.102 0.898] | 0.302 |
+| (0.2, 80) | 0.153481 | 0.163519 | 0.317 | [0.117 0.683 0. 0.2 ] | 0.136076 | 0.233269 | 0.369344 | [0.117 0.883] | 0.317 |
+| (0.2, 81) | 0.139622 | 0.180378 | 0.32 | [0.121 0.679 0.001 0.199] | 0.126998 | 0.242204 | 0.369202 | [0.122 0.878] | 0.32 |
+| (0.2, 82) | 0.131272 | 0.188728 | 0.32 | [0.121 0.679 0.001 0.199] | 0.125249 | 0.243954 | 0.369202 | [0.122 0.878] | 0.32 |
+| (0.2, 83) | 0.150497 | 0.172503 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.154524 | 0.216878 | 0.371402 | [0.123 0.877] | 0.323 |
+| (0.2, 84) | 0.138086 | 0.180914 | 0.319 | [0.119 0.681 0. 0.2 ] | 0.125401 | 0.244626 | 0.370028 | [0.119 0.881] | 0.319 |
+| (0.2, 85) | 0.139788 | 0.187212 | 0.327 | [0.127 0.673 0. 0.2 ] | 0.157005 | 0.215781 | 0.372787 | [0.127 0.873] | 0.327 |
+| (0.2, 86) | 0.0908716 | 0.216128 | 0.307 | [0.107 0.693 0. 0.2 ] | 0.0962838 | 0.269681 | 0.365965 | [0.107 0.893] | 0.307 |
+| (0.2, 87) | 0.147758 | 0.161242 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.129789 | 0.236848 | 0.366636 | [0.109 0.891] | 0.309 |
+| (0.2, 88) | 0.137745 | 0.187255 | 0.325 | [0.125 0.675 0. 0.2 ] | 0.16326 | 0.208833 | 0.372093 | [0.125 0.875] | 0.325 |
+| (0.2, 89) | 0.147468 | 0.161532 | 0.309 | [0.109 0.691 0. 0.2 ] | 0.132114 | 0.234522 | 0.366636 | [0.109 0.891] | 0.309 |
+| (0.2, 90) | 0.0964468 | 0.224553 | 0.321 | [0.121 0.679 0. 0.2 ] | 0.102582 | 0.268131 | 0.370714 | [0.121 0.879] | 0.321 |
+| (0.2, 91) | 0.101547 | 0.214453 | 0.316 | [0.116 0.684 0. 0.2 ] | 0.112843 | 0.25616 | 0.369004 | [0.116 0.884] | 0.316 |
+| (0.2, 92) | 0.162379 | 0.157621 | 0.32 | [0.12 0.68 0. 0.2 ] | 0.132839 | 0.237531 | 0.37037 | [0.12 0.88] | 0.32 |
+| (0.2, 93) | 0.141758 | 0.189242 | 0.331 | [0.132 0.668 0.001 0.199] | 0.144896 | 0.228113 | 0.373008 | [0.133 0.867] | 0.331 |
+| (0.2, 94) | 0.169261 | 0.152739 | 0.322 | [0.122 0.678 0. 0.2 ] | 0.166465 | 0.204593 | 0.371058 | [0.122 0.878] | 0.322 |
+| (0.2, 95) | 0.122537 | 0.200463 | 0.323 | [0.123 0.677 0. 0.2 ] | 0.111265 | 0.260137 | 0.371402 | [0.123 0.877] | 0.323 |
+| (0.2, 96) | 0.126137 | 0.193863 | 0.32 | [0.121 0.679 0.001 0.199] | 0.130176 | 0.239026 | 0.369202 | [0.122 0.878] | 0.32 |
+| (0.2, 97) | 0.0939801 | 0.23702 | 0.331 | [0.131 0.669 0. 0.2 ] | 0.103706 | 0.270476 | 0.374181 | [0.131 0.869] | 0.331 |
+| (0.2, 98) | 0.105674 | 0.208326 | 0.314 | [0.115 0.685 0.001 0.199] | 0.115848 | 0.251311 | 0.367159 | [0.116 0.884] | 0.314 |
+| (0.2, 99) | 0.107548 | 0.207452 | 0.315 | [0.115 0.685 0. 0.2 ] | 0.118836 | 0.249828 | 0.368664 | [0.115 0.885] | 0.315 |
+| (0.25, 0) | 0.124355 | 0.219645 | 0.344 | [0.094 0.656 0. 0.25 ] | 0.128487 | 0.304039 | 0.432526 | [0.094 0.906] | 0.344 |
+| (0.25, 1) | 0.123549 | 0.242451 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.123781 | 0.317136 | 0.440917 | [0.116 0.884] | 0.366 |
+| (0.25, 2) | 0.11547 | 0.24653 | 0.362 | [0.113 0.637 0.001 0.249] | 0.108391 | 0.32999 | 0.43838 | [0.114 0.886] | 0.362 |
+| (0.25, 3) | 0.14217 | 0.23583 | 0.378 | [0.128 0.622 0. 0.25 ] | 0.13991 | 0.305723 | 0.445633 | [0.128 0.872] | 0.378 |
+| (0.25, 4) | 0.115606 | 0.240394 | 0.356 | [0.106 0.644 0. 0.25 ] | 0.10033 | 0.336733 | 0.437063 | [0.106 0.894] | 0.356 |
+| (0.25, 5) | 0.168544 | 0.212456 | 0.381 | [0.131 0.619 0. 0.25 ] | 0.144145 | 0.302683 | 0.446828 | [0.131 0.869] | 0.381 |
+| (0.25, 6) | 0.0947743 | 0.273226 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.095146 | 0.34655 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 7) | 0.113473 | 0.251527 | 0.365 | [0.115 0.635 0. 0.25 ] | 0.111097 | 0.329432 | 0.440529 | [0.115 0.885] | 0.365 |
+| (0.25, 8) | 0.155793 | 0.217207 | 0.373 | [0.123 0.627 0. 0.25 ] | 0.136486 | 0.30717 | 0.443656 | [0.123 0.877] | 0.373 |
+| (0.25, 9) | 0.129944 | 0.218056 | 0.348 | [0.098 0.652 0. 0.25 ] | 0.124308 | 0.30972 | 0.434028 | [0.098 0.902] | 0.348 |
+| (0.25, 10) | 0.137385 | 0.225615 | 0.363 | [0.113 0.637 0. 0.25 ] | 0.134428 | 0.305325 | 0.439754 | [0.113 0.887] | 0.363 |
+| (0.25, 11) | 0.129083 | 0.242917 | 0.372 | [0.122 0.628 0. 0.25 ] | 0.136549 | 0.306714 | 0.443262 | [0.122 0.878] | 0.372 |
+| (0.25, 12) | 0.116791 | 0.239209 | 0.356 | [0.106 0.644 0. 0.25 ] | 0.130234 | 0.306828 | 0.437063 | [0.106 0.894] | 0.356 |
+| (0.25, 13) | 0.126751 | 0.222249 | 0.349 | [0.099 0.651 0. 0.25 ] | 0.113015 | 0.32139 | 0.434405 | [0.099 0.901] | 0.349 |
+| (0.25, 14) | 0.128282 | 0.226718 | 0.355 | [0.105 0.645 0. 0.25 ] | 0.120019 | 0.316662 | 0.436681 | [0.105 0.895] | 0.355 |
+| (0.25, 15) | 0.143813 | 0.218187 | 0.362 | [0.113 0.637 0.001 0.249] | 0.126338 | 0.312042 | 0.43838 | [0.114 0.886] | 0.362 |
+| (0.25, 16) | 0.135428 | 0.238572 | 0.374 | [0.124 0.626 0. 0.25 ] | 0.130811 | 0.313239 | 0.44405 | [0.124 0.876] | 0.374 |
+| (0.25, 17) | 0.112018 | 0.241982 | 0.354 | [0.105 0.645 0.001 0.249] | 0.120587 | 0.314728 | 0.435315 | [0.106 0.894] | 0.354 |
+| (0.25, 18) | 0.159659 | 0.202341 | 0.362 | [0.112 0.638 0. 0.25 ] | 0.14518 | 0.294188 | 0.439367 | [0.112 0.888] | 0.362 |
+| (0.25, 19) | 0.125726 | 0.242274 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.116861 | 0.324835 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 20) | 0.156058 | 0.193942 | 0.35 | [0.1 0.65 0. 0.25] | 0.112552 | 0.32223 | 0.434783 | [0.1 0.9] | 0.35 |
+| (0.25, 21) | 0.115433 | 0.259567 | 0.375 | [0.125 0.625 0. 0.25 ] | 0.0991129 | 0.345332 | 0.444444 | [0.125 0.875] | 0.375 |
+| (0.25, 22) | 0.127289 | 0.232711 | 0.36 | [0.11 0.64 0. 0.25] | 0.115265 | 0.323332 | 0.438596 | [0.11 0.89] | 0.36 |
+| (0.25, 23) | 0.124531 | 0.233469 | 0.358 | [0.109 0.641 0.001 0.249] | 0.0982565 | 0.338586 | 0.436842 | [0.11 0.89] | 0.358 |
+| (0.25, 24) | 0.169186 | 0.195814 | 0.365 | [0.115 0.635 0. 0.25 ] | 0.138074 | 0.302455 | 0.440529 | [0.115 0.885] | 0.365 |
+| (0.25, 25) | 0.128267 | 0.227733 | 0.356 | [0.107 0.643 0.001 0.249] | 0.148625 | 0.287452 | 0.436077 | [0.108 0.892] | 0.356 |
+| (0.25, 26) | 0.126575 | 0.236425 | 0.363 | [0.113 0.637 0. 0.25 ] | 0.133828 | 0.305925 | 0.439754 | [0.113 0.887] | 0.363 |
+| (0.25, 27) | 0.129839 | 0.252161 | 0.382 | [0.132 0.618 0. 0.25 ] | 0.115004 | 0.332224 | 0.447227 | [0.132 0.868] | 0.382 |
+| (0.25, 28) | 0.10892 | 0.24408 | 0.353 | [0.103 0.647 0. 0.25 ] | 0.112931 | 0.322988 | 0.43592 | [0.103 0.897] | 0.353 |
+| (0.25, 29) | 0.121689 | 0.228311 | 0.35 | [0.1 0.65 0. 0.25] | 0.124501 | 0.310282 | 0.434783 | [0.1 0.9] | 0.35 |
+| (0.25, 30) | 0.130389 | 0.216611 | 0.347 | [0.098 0.652 0.001 0.249] | 0.137773 | 0.294895 | 0.432667 | [0.099 0.901] | 0.347 |
+| (0.25, 31) | 0.109612 | 0.257388 | 0.367 | [0.117 0.633 0. 0.25 ] | 0.100272 | 0.341035 | 0.441306 | [0.117 0.883] | 0.367 |
+| (0.25, 32) | 0.123587 | 0.245413 | 0.369 | [0.119 0.631 0. 0.25 ] | 0.133389 | 0.308697 | 0.442087 | [0.119 0.881] | 0.369 |
+| (0.25, 33) | 0.162584 | 0.194416 | 0.357 | [0.107 0.643 0. 0.25 ] | 0.134293 | 0.303153 | 0.437445 | [0.107 0.893] | 0.357 |
+| (0.25, 34) | 0.148317 | 0.213683 | 0.362 | [0.112 0.638 0. 0.25 ] | 0.110308 | 0.329059 | 0.439367 | [0.112 0.888] | 0.362 |
+| (0.25, 35) | 0.11158 | 0.25342 | 0.365 | [0.115 0.635 0. 0.25 ] | 0.110128 | 0.330401 | 0.440529 | [0.115 0.885] | 0.365 |
+| (0.25, 36) | 0.154516 | 0.207484 | 0.362 | [0.113 0.637 0.001 0.249] | 0.125018 | 0.313362 | 0.43838 | [0.114 0.886] | 0.362 |
+| (0.25, 37) | 0.120364 | 0.245636 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.116338 | 0.32458 | 0.440917 | [0.116 0.884] | 0.366 |
+| (0.25, 38) | 0.166437 | 0.190563 | 0.357 | [0.108 0.642 0.001 0.249] | 0.140817 | 0.295642 | 0.436459 | [0.109 0.891] | 0.357 |
+| (0.25, 39) | 0.117464 | 0.243536 | 0.361 | [0.111 0.639 0. 0.25 ] | 0.11287 | 0.326111 | 0.438982 | [0.111 0.889] | 0.361 |
+| (0.25, 40) | 0.139079 | 0.196921 | 0.336 | [0.087 0.663 0.001 0.249] | 0.132232 | 0.296339 | 0.428571 | [0.088 0.912] | 0.336 |
+| (0.25, 41) | 0.106429 | 0.239571 | 0.346 | [0.096 0.654 0. 0.25 ] | 0.113467 | 0.319809 | 0.433276 | [0.096 0.904] | 0.346 |
+| (0.25, 42) | 0.130296 | 0.252704 | 0.383 | [0.133 0.617 0. 0.25 ] | 0.0936963 | 0.353931 | 0.447628 | [0.133 0.867] | 0.383 |
+| (0.25, 43) | 0.143415 | 0.201585 | 0.345 | [0.095 0.655 0. 0.25 ] | 0.143536 | 0.289364 | 0.4329 | [0.095 0.905] | 0.345 |
+| (0.25, 44) | 0.114779 | 0.257221 | 0.372 | [0.123 0.627 0.001 0.249] | 0.103723 | 0.338551 | 0.442274 | [0.124 0.876] | 0.372 |
+| (0.25, 45) | 0.16507 | 0.19593 | 0.361 | [0.111 0.639 0. 0.25 ] | 0.149673 | 0.289309 | 0.438982 | [0.111 0.889] | 0.361 |
+| (0.25, 46) | 0.158965 | 0.201035 | 0.36 | [0.11 0.64 0. 0.25] | 0.135501 | 0.303095 | 0.438596 | [0.11 0.89] | 0.36 |
+| (0.25, 47) | 0.12667 | 0.24133 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.120737 | 0.320959 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 48) | 0.142702 | 0.240298 | 0.383 | [0.133 0.617 0. 0.25 ] | 0.126929 | 0.320699 | 0.447628 | [0.133 0.867] | 0.383 |
+| (0.25, 49) | 0.139296 | 0.228704 | 0.368 | [0.12 0.63 0.002 0.248] | 0.116949 | 0.322768 | 0.439716 | [0.122 0.878] | 0.368 |
+| (0.25, 50) | 0.130214 | 0.218786 | 0.349 | [0.099 0.651 0. 0.25 ] | 0.139032 | 0.295373 | 0.434405 | [0.099 0.901] | 0.349 |
+| (0.25, 51) | 0.126645 | 0.221355 | 0.348 | [0.098 0.652 0. 0.25 ] | 0.111247 | 0.322781 | 0.434028 | [0.098 0.902] | 0.348 |
+| (0.25, 52) | 0.162073 | 0.197927 | 0.36 | [0.111 0.639 0.001 0.249] | 0.145148 | 0.292462 | 0.43761 | [0.112 0.888] | 0.36 |
+| (0.25, 53) | 0.125951 | 0.237049 | 0.363 | [0.115 0.635 0.002 0.248] | 0.121835 | 0.315941 | 0.437776 | [0.117 0.883] | 0.363 |
+| (0.25, 54) | 0.137738 | 0.233262 | 0.371 | [0.121 0.629 0. 0.25 ] | 0.149517 | 0.293353 | 0.44287 | [0.121 0.879] | 0.371 |
+| (0.25, 55) | 0.120461 | 0.226539 | 0.347 | [0.098 0.652 0.001 0.249] | 0.126996 | 0.305672 | 0.432667 | [0.099 0.901] | 0.347 |
+| (0.25, 56) | 0.083097 | 0.271903 | 0.355 | [0.106 0.644 0.001 0.249] | 0.0829992 | 0.352696 | 0.435696 | [0.107 0.893] | 0.355 |
+| (0.25, 57) | 0.152516 | 0.206484 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.156152 | 0.28206 | 0.438212 | [0.109 0.891] | 0.359 |
+| (0.25, 58) | 0.15842 | 0.19158 | 0.35 | [0.101 0.649 0.001 0.249] | 0.140964 | 0.292834 | 0.433798 | [0.102 0.898] | 0.35 |
+| (0.25, 59) | 0.120642 | 0.251358 | 0.372 | [0.122 0.628 0. 0.25 ] | 0.121374 | 0.321889 | 0.443262 | [0.122 0.878] | 0.372 |
+| (0.25, 60) | 0.125145 | 0.231855 | 0.357 | [0.107 0.643 0. 0.25 ] | 0.111299 | 0.326146 | 0.437445 | [0.107 0.893] | 0.357 |
+| (0.25, 61) | 0.141589 | 0.228411 | 0.37 | [0.12 0.63 0. 0.25] | 0.146554 | 0.295924 | 0.442478 | [0.12 0.88] | 0.37 |
+| (0.25, 62) | 0.129288 | 0.210712 | 0.34 | [0.09 0.66 0. 0.25] | 0.123316 | 0.307719 | 0.431034 | [0.09 0.91] | 0.34 |
+| (0.25, 63) | 0.167968 | 0.200032 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.14112 | 0.300576 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 64) | 0.126202 | 0.241798 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.107658 | 0.334039 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 65) | 0.139649 | 0.205351 | 0.345 | [0.095 0.655 0. 0.25 ] | 0.132912 | 0.299989 | 0.4329 | [0.095 0.905] | 0.345 |
+| (0.25, 66) | 0.13461 | 0.22139 | 0.356 | [0.107 0.643 0.001 0.249] | 0.120895 | 0.315182 | 0.436077 | [0.108 0.892] | 0.356 |
+| (0.25, 67) | 0.112746 | 0.246254 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.108761 | 0.329451 | 0.438212 | [0.109 0.891] | 0.359 |
+| (0.25, 68) | 0.125963 | 0.240037 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.12457 | 0.316347 | 0.440917 | [0.116 0.884] | 0.366 |
+| (0.25, 69) | 0.117978 | 0.225022 | 0.343 | [0.094 0.656 0.001 0.249] | 0.122437 | 0.308731 | 0.431169 | [0.095 0.905] | 0.343 |
+| (0.25, 70) | 0.0978247 | 0.271175 | 0.369 | [0.119 0.631 0. 0.25 ] | 0.10638 | 0.335707 | 0.442087 | [0.119 0.881] | 0.369 |
+| (0.25, 71) | 0.122178 | 0.228822 | 0.351 | [0.101 0.649 0. 0.25 ] | 0.112982 | 0.322179 | 0.435161 | [0.101 0.899] | 0.351 |
+| (0.25, 72) | 0.116694 | 0.261306 | 0.378 | [0.128 0.622 0. 0.25 ] | 0.129308 | 0.316324 | 0.445633 | [0.128 0.872] | 0.378 |
+| (0.25, 73) | 0.142151 | 0.206849 | 0.349 | [0.099 0.651 0. 0.25 ] | 0.127291 | 0.307114 | 0.434405 | [0.099 0.901] | 0.349 |
+| (0.25, 74) | 0.119932 | 0.223068 | 0.343 | [0.093 0.657 0. 0.25 ] | 0.118733 | 0.313419 | 0.432152 | [0.093 0.907] | 0.343 |
+| (0.25, 75) | 0.161339 | 0.193661 | 0.355 | [0.105 0.645 0. 0.25 ] | 0.13814 | 0.298541 | 0.436681 | [0.105 0.895] | 0.355 |
+| (0.25, 76) | 0.102897 | 0.251103 | 0.354 | [0.105 0.645 0.001 0.249] | 0.113351 | 0.321964 | 0.435315 | [0.106 0.894] | 0.354 |
+| (0.25, 77) | 0.13454 | 0.22646 | 0.361 | [0.111 0.639 0. 0.25 ] | 0.118977 | 0.320005 | 0.438982 | [0.111 0.889] | 0.361 |
+| (0.25, 78) | 0.139003 | 0.228997 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.124439 | 0.317258 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 79) | 0.128929 | 0.230071 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.109666 | 0.328546 | 0.438212 | [0.109 0.891] | 0.359 |
+| (0.25, 80) | 0.153328 | 0.220672 | 0.374 | [0.124 0.626 0. 0.25 ] | 0.148008 | 0.296042 | 0.44405 | [0.124 0.876] | 0.374 |
+| (0.25, 81) | 0.123484 | 0.247516 | 0.371 | [0.121 0.629 0. 0.25 ] | 0.105126 | 0.337743 | 0.44287 | [0.121 0.879] | 0.371 |
+| (0.25, 82) | 0.12095 | 0.23105 | 0.352 | [0.102 0.648 0. 0.25 ] | 0.102409 | 0.333131 | 0.43554 | [0.102 0.898] | 0.352 |
+| (0.25, 83) | 0.123315 | 0.239685 | 0.363 | [0.113 0.637 0. 0.25 ] | 0.113052 | 0.326702 | 0.439754 | [0.113 0.887] | 0.363 |
+| (0.25, 84) | 0.114865 | 0.244135 | 0.359 | [0.11 0.64 0.001 0.249] | 0.0973808 | 0.339845 | 0.437226 | [0.111 0.889] | 0.359 |
+| (0.25, 85) | 0.141829 | 0.225171 | 0.367 | [0.118 0.632 0.001 0.249] | 0.123299 | 0.317019 | 0.440318 | [0.119 0.881] | 0.367 |
+| (0.25, 86) | 0.136209 | 0.229791 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.123135 | 0.317782 | 0.440917 | [0.116 0.884] | 0.366 |
+| (0.25, 87) | 0.170616 | 0.183384 | 0.354 | [0.104 0.646 0. 0.25 ] | 0.145532 | 0.290768 | 0.4363 | [0.104 0.896] | 0.354 |
+| (0.25, 88) | 0.143335 | 0.223665 | 0.367 | [0.117 0.633 0. 0.25 ] | 0.127911 | 0.313396 | 0.441306 | [0.117 0.883] | 0.367 |
+| (0.25, 89) | 0.137073 | 0.216927 | 0.354 | [0.104 0.646 0. 0.25 ] | 0.154553 | 0.281747 | 0.4363 | [0.104 0.896] | 0.354 |
+| (0.25, 90) | 0.140224 | 0.216776 | 0.357 | [0.107 0.643 0. 0.25 ] | 0.152714 | 0.284731 | 0.437445 | [0.107 0.893] | 0.357 |
+| (0.25, 91) | 0.117738 | 0.253262 | 0.371 | [0.121 0.629 0. 0.25 ] | 0.0959792 | 0.346891 | 0.44287 | [0.121 0.879] | 0.371 |
+| (0.25, 92) | 0.123906 | 0.252094 | 0.376 | [0.126 0.624 0. 0.25 ] | 0.126874 | 0.317966 | 0.44484 | [0.126 0.874] | 0.376 |
+| (0.25, 93) | 0.0661894 | 0.301811 | 0.368 | [0.118 0.632 0. 0.25 ] | 0.0814921 | 0.360204 | 0.441696 | [0.118 0.882] | 0.368 |
+| (0.25, 94) | 0.153841 | 0.208159 | 0.362 | [0.112 0.638 0. 0.25 ] | 0.129741 | 0.309626 | 0.439367 | [0.112 0.888] | 0.362 |
+| (0.25, 95) | 0.144879 | 0.200121 | 0.345 | [0.096 0.654 0.001 0.249] | 0.139426 | 0.29249 | 0.431917 | [0.097 0.903] | 0.345 |
+| (0.25, 96) | 0.151496 | 0.214504 | 0.366 | [0.116 0.634 0. 0.25 ] | 0.112522 | 0.328395 | 0.440917 | [0.116 0.884] | 0.366 |
+| (0.25, 97) | 0.135256 | 0.219744 | 0.355 | [0.105 0.645 0. 0.25 ] | 0.126896 | 0.309785 | 0.436681 | [0.105 0.895] | 0.355 |
+| (0.25, 98) | 0.148867 | 0.194133 | 0.343 | [0.093 0.657 0. 0.25 ] | 0.128798 | 0.303354 | 0.432152 | [0.093 0.907] | 0.343 |
+| (0.25, 99) | 0.137454 | 0.221546 | 0.359 | [0.109 0.641 0. 0.25 ] | 0.108894 | 0.329318 | 0.438212 | [0.109 0.891] | 0.359 |
+| (0.3, 0) | 0.115385 | 0.311615 | 0.427 | [0.127 0.573 0. 0.3 ] | 0.103546 | 0.407963 | 0.511509 | [0.127 0.873] | 0.427 |
+| (0.3, 1) | 0.115234 | 0.275766 | 0.391 | [0.092 0.608 0.001 0.299] | 0.105087 | 0.390356 | 0.495443 | [0.093 0.907] | 0.391 |
+| (0.3, 2) | 0.107756 | 0.296244 | 0.404 | [0.105 0.595 0.001 0.299] | 0.105065 | 0.395773 | 0.500838 | [0.106 0.894] | 0.404 |
+| (0.3, 3) | 0.0940979 | 0.301902 | 0.396 | [0.096 0.604 0. 0.3 ] | 0.0939231 | 0.404416 | 0.498339 | [0.096 0.904] | 0.396 |
+| (0.3, 4) | 0.129976 | 0.268024 | 0.398 | [0.098 0.602 0. 0.3 ] | 0.104953 | 0.394215 | 0.499168 | [0.098 0.902] | 0.398 |
+| (0.3, 5) | 0.128381 | 0.250619 | 0.379 | [0.079 0.621 0. 0.3 ] | 0.101842 | 0.389559 | 0.4914 | [0.079 0.921] | 0.379 |
+| (0.3, 6) | 0.131556 | 0.270444 | 0.402 | [0.102 0.598 0. 0.3 ] | 0.117514 | 0.383321 | 0.500835 | [0.102 0.898] | 0.402 |
+| (0.3, 7) | 0.112026 | 0.284974 | 0.397 | [0.099 0.601 0.002 0.298] | 0.124003 | 0.373078 | 0.497081 | [0.101 0.899] | 0.397 |
+| (0.3, 8) | 0.126207 | 0.290793 | 0.417 | [0.117 0.583 0. 0.3 ] | 0.117671 | 0.389514 | 0.507185 | [0.117 0.883] | 0.417 |
+| (0.3, 9) | 0.139192 | 0.253808 | 0.393 | [0.094 0.606 0.001 0.299] | 0.0999559 | 0.39631 | 0.496266 | [0.095 0.905] | 0.393 |
+| (0.3, 10) | 0.120012 | 0.281988 | 0.402 | [0.102 0.598 0. 0.3 ] | 0.119377 | 0.381458 | 0.500835 | [0.102 0.898] | 0.402 |
+| (0.3, 11) | 0.139279 | 0.260721 | 0.4 | [0.1 0.6 0. 0.3] | 0.117324 | 0.382676 | 0.5 | [0.1 0.9] | 0.4 |
+| (0.3, 12) | 0.116443 | 0.276557 | 0.393 | [0.095 0.605 0.002 0.298] | 0.111133 | 0.384295 | 0.495428 | [0.097 0.903] | 0.393 |
+| (0.3, 13) | 0.124193 | 0.273807 | 0.398 | [0.099 0.601 0.001 0.299] | 0.108405 | 0.389929 | 0.498333 | [0.1 0.9] | 0.398 |
+| (0.3, 14) | 0.12208 | 0.26692 | 0.389 | [0.089 0.611 0. 0.3 ] | 0.127327 | 0.368132 | 0.495458 | [0.089 0.911] | 0.389 |
+| (0.3, 15) | 0.103448 | 0.292552 | 0.396 | [0.096 0.604 0. 0.3 ] | 0.100266 | 0.398073 | 0.498339 | [0.096 0.904] | 0.396 |
+| (0.3, 16) | 0.14551 | 0.24649 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.120372 | 0.376316 | 0.496689 | [0.092 0.908] | 0.392 |
+| (0.3, 17) | 0.141222 | 0.269778 | 0.411 | [0.111 0.589 0. 0.3 ] | 0.118556 | 0.38607 | 0.504626 | [0.111 0.889] | 0.411 |
+| (0.3, 18) | 0.142631 | 0.262369 | 0.405 | [0.105 0.595 0. 0.3 ] | 0.0938785 | 0.408214 | 0.502092 | [0.105 0.895] | 0.405 |
+| (0.3, 19) | 0.14518 | 0.26782 | 0.413 | [0.114 0.586 0.001 0.299] | 0.125934 | 0.378707 | 0.504641 | [0.115 0.885] | 0.413 |
+| (0.3, 20) | 0.117111 | 0.292889 | 0.41 | [0.11 0.59 0. 0.3 ] | 0.100578 | 0.403624 | 0.504202 | [0.11 0.89] | 0.41 |
+| (0.3, 21) | 0.147531 | 0.264469 | 0.412 | [0.113 0.587 0.001 0.299] | 0.116326 | 0.387889 | 0.504216 | [0.114 0.886] | 0.412 |
+| (0.3, 22) | 0.106063 | 0.292937 | 0.399 | [0.099 0.601 0. 0.3 ] | 0.106593 | 0.39299 | 0.499584 | [0.099 0.901] | 0.399 |
+| (0.3, 23) | 0.148613 | 0.250387 | 0.399 | [0.099 0.601 0. 0.3 ] | 0.127635 | 0.371949 | 0.499584 | [0.099 0.901] | 0.399 |
+| (0.3, 24) | 0.154573 | 0.248427 | 0.403 | [0.103 0.597 0. 0.3 ] | 0.114545 | 0.386709 | 0.501253 | [0.103 0.897] | 0.403 |
+| (0.3, 25) | 0.126976 | 0.267024 | 0.394 | [0.094 0.606 0. 0.3 ] | 0.107205 | 0.390308 | 0.497512 | [0.094 0.906] | 0.394 |
+| (0.3, 26) | 0.0936366 | 0.315363 | 0.409 | [0.109 0.591 0. 0.3 ] | 0.0963521 | 0.407426 | 0.503778 | [0.109 0.891] | 0.409 |
+| (0.3, 27) | 0.112656 | 0.269344 | 0.382 | [0.083 0.617 0.001 0.299] | 0.104119 | 0.387657 | 0.491776 | [0.084 0.916] | 0.382 |
+| (0.3, 28) | 0.162282 | 0.249718 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.125725 | 0.379325 | 0.505051 | [0.112 0.888] | 0.412 |
+| (0.3, 29) | 0.144141 | 0.254859 | 0.399 | [0.1 0.6 0.001 0.299] | 0.10784 | 0.390909 | 0.498749 | [0.101 0.899] | 0.399 |
+| (0.3, 30) | 0.148497 | 0.254503 | 0.403 | [0.103 0.597 0. 0.3 ] | 0.114328 | 0.386925 | 0.501253 | [0.103 0.897] | 0.403 |
+| (0.3, 31) | 0.132418 | 0.280582 | 0.413 | [0.113 0.587 0. 0.3 ] | 0.110571 | 0.394905 | 0.505476 | [0.113 0.887] | 0.413 |
+| (0.3, 32) | 0.112737 | 0.277263 | 0.39 | [0.091 0.609 0.001 0.299] | 0.105898 | 0.389135 | 0.495033 | [0.092 0.908] | 0.39 |
+| (0.3, 33) | 0.141008 | 0.265992 | 0.407 | [0.107 0.593 0. 0.3 ] | 0.124772 | 0.378162 | 0.502934 | [0.107 0.893] | 0.407 |
+| (0.3, 34) | 0.138324 | 0.254676 | 0.393 | [0.093 0.607 0. 0.3 ] | 0.132808 | 0.364293 | 0.4971 | [0.093 0.907] | 0.393 |
+| (0.3, 35) | 0.142124 | 0.270876 | 0.413 | [0.113 0.587 0. 0.3 ] | 0.114159 | 0.391317 | 0.505476 | [0.113 0.887] | 0.413 |
+| (0.3, 36) | 0.122152 | 0.278848 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.0982835 | 0.402133 | 0.500417 | [0.101 0.899] | 0.401 |
+| (0.3, 37) | 0.131292 | 0.261708 | 0.393 | [0.093 0.607 0. 0.3 ] | 0.123554 | 0.373546 | 0.4971 | [0.093 0.907] | 0.393 |
+| (0.3, 38) | 0.128837 | 0.288163 | 0.417 | [0.118 0.582 0.001 0.299] | 0.108684 | 0.397666 | 0.506351 | [0.119 0.881] | 0.417 |
+| (0.3, 39) | 0.129308 | 0.262692 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.106602 | 0.390086 | 0.496689 | [0.092 0.908] | 0.392 |
+| (0.3, 40) | 0.140918 | 0.253082 | 0.394 | [0.095 0.605 0.001 0.299] | 0.112835 | 0.383843 | 0.496678 | [0.096 0.904] | 0.394 |
+| (0.3, 41) | 0.116026 | 0.291974 | 0.408 | [0.108 0.592 0. 0.3 ] | 0.0894206 | 0.413935 | 0.503356 | [0.108 0.892] | 0.408 |
+| (0.3, 42) | 0.126607 | 0.266393 | 0.393 | [0.095 0.605 0.002 0.298] | 0.112307 | 0.383122 | 0.495428 | [0.097 0.903] | 0.393 |
+| (0.3, 43) | 0.100563 | 0.307437 | 0.408 | [0.109 0.591 0.001 0.299] | 0.099999 | 0.402522 | 0.502521 | [0.11 0.89] | 0.408 |
+| (0.3, 44) | 0.129683 | 0.262317 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.10938 | 0.387309 | 0.496689 | [0.092 0.908] | 0.392 |
+| (0.3, 45) | 0.113322 | 0.281678 | 0.395 | [0.095 0.605 0. 0.3 ] | 0.102612 | 0.395314 | 0.497925 | [0.095 0.905] | 0.395 |
+| (0.3, 46) | 0.121586 | 0.283414 | 0.405 | [0.105 0.595 0. 0.3 ] | 0.111687 | 0.390405 | 0.502092 | [0.105 0.895] | 0.405 |
+| (0.3, 47) | 0.117878 | 0.303122 | 0.421 | [0.121 0.579 0. 0.3 ] | 0.101569 | 0.407336 | 0.508906 | [0.121 0.879] | 0.421 |
+| (0.3, 48) | 0.114245 | 0.286755 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.105145 | 0.395272 | 0.500417 | [0.101 0.899] | 0.401 |
+| (0.3, 49) | 0.138991 | 0.244009 | 0.383 | [0.083 0.617 0. 0.3 ] | 0.126666 | 0.366349 | 0.493016 | [0.083 0.917] | 0.383 |
+| (0.3, 50) | 0.120115 | 0.271885 | 0.392 | [0.092 0.608 0. 0.3 ] | 0.121823 | 0.374866 | 0.496689 | [0.092 0.908] | 0.392 |
+| (0.3, 51) | 0.11579 | 0.26921 | 0.385 | [0.085 0.615 0. 0.3 ] | 0.110148 | 0.383679 | 0.493827 | [0.085 0.915] | 0.385 |
+| (0.3, 52) | 0.134915 | 0.275085 | 0.41 | [0.111 0.589 0.001 0.299] | 0.0925126 | 0.410854 | 0.503367 | [0.112 0.888] | 0.41 |
+| (0.3, 53) | 0.142717 | 0.261283 | 0.404 | [0.106 0.594 0.002 0.298] | 0.118655 | 0.381345 | 0.5 | [0.108 0.892] | 0.404 |
+| (0.3, 54) | 0.154873 | 0.236127 | 0.391 | [0.091 0.609 0. 0.3 ] | 0.115805 | 0.380473 | 0.496278 | [0.091 0.909] | 0.391 |
+| (0.3, 55) | 0.117916 | 0.297084 | 0.415 | [0.115 0.585 0. 0.3 ] | 0.113195 | 0.393134 | 0.506329 | [0.115 0.885] | 0.415 |
+| (0.3, 56) | 0.119119 | 0.291881 | 0.411 | [0.111 0.589 0. 0.3 ] | 0.0887019 | 0.415924 | 0.504626 | [0.111 0.889] | 0.411 |
+| (0.3, 57) | 0.136571 | 0.269429 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.121916 | 0.380597 | 0.502513 | [0.106 0.894] | 0.406 |
+| (0.3, 58) | 0.149654 | 0.235346 | 0.385 | [0.086 0.614 0.001 0.299] | 0.118077 | 0.374916 | 0.492993 | [0.087 0.913] | 0.385 |
+| (0.3, 59) | 0.110281 | 0.305719 | 0.416 | [0.116 0.584 0. 0.3 ] | 0.113127 | 0.39363 | 0.506757 | [0.116 0.884] | 0.416 |
+| (0.3, 60) | 0.105847 | 0.288153 | 0.394 | [0.094 0.606 0. 0.3 ] | 0.108523 | 0.388989 | 0.497512 | [0.094 0.906] | 0.394 |
+| (0.3, 61) | 0.118659 | 0.288341 | 0.407 | [0.107 0.593 0. 0.3 ] | 0.085541 | 0.417393 | 0.502934 | [0.107 0.893] | 0.407 |
+| (0.3, 62) | 0.129623 | 0.283377 | 0.413 | [0.115 0.585 0.002 0.298] | 0.112032 | 0.391772 | 0.503804 | [0.117 0.883] | 0.413 |
+| (0.3, 63) | 0.126394 | 0.269606 | 0.396 | [0.096 0.604 0. 0.3 ] | 0.112563 | 0.385776 | 0.498339 | [0.096 0.904] | 0.396 |
+| (0.3, 64) | 0.139585 | 0.264415 | 0.404 | [0.104 0.596 0. 0.3 ] | 0.111884 | 0.389788 | 0.501672 | [0.104 0.896] | 0.404 |
+| (0.3, 65) | 0.0951434 | 0.310857 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.0848641 | 0.417648 | 0.502513 | [0.106 0.894] | 0.406 |
+| (0.3, 66) | 0.111057 | 0.277943 | 0.389 | [0.089 0.611 0. 0.3 ] | 0.10445 | 0.391009 | 0.495458 | [0.089 0.911] | 0.389 |
+| (0.3, 67) | 0.0656081 | 0.346392 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.0574239 | 0.447627 | 0.505051 | [0.112 0.888] | 0.412 |
+| (0.3, 68) | 0.115383 | 0.293617 | 0.409 | [0.109 0.591 0. 0.3 ] | 0.0971393 | 0.406639 | 0.503778 | [0.109 0.891] | 0.409 |
+| (0.3, 69) | 0.11694 | 0.28806 | 0.405 | [0.105 0.595 0. 0.3 ] | 0.118732 | 0.38336 | 0.502092 | [0.105 0.895] | 0.405 |
+| (0.3, 70) | 0.129901 | 0.276099 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.11687 | 0.385643 | 0.502513 | [0.106 0.894] | 0.406 |
+| (0.3, 71) | 0.12312 | 0.29188 | 0.415 | [0.115 0.585 0. 0.3 ] | 0.0975558 | 0.408773 | 0.506329 | [0.115 0.885] | 0.415 |
+| (0.3, 72) | 0.119927 | 0.294073 | 0.414 | [0.114 0.586 0. 0.3 ] | 0.096911 | 0.408991 | 0.505902 | [0.114 0.886] | 0.414 |
+| (0.3, 73) | 0.133123 | 0.253877 | 0.387 | [0.087 0.613 0. 0.3 ] | 0.110938 | 0.383703 | 0.494641 | [0.087 0.913] | 0.387 |
+| (0.3, 74) | 0.0891778 | 0.333822 | 0.423 | [0.123 0.577 0. 0.3 ] | 0.0806618 | 0.429109 | 0.509771 | [0.123 0.877] | 0.423 |
+| (0.3, 75) | 0.0964315 | 0.321569 | 0.418 | [0.118 0.582 0. 0.3 ] | 0.0962955 | 0.411319 | 0.507614 | [0.118 0.882] | 0.418 |
+| (0.3, 76) | 0.152005 | 0.253995 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.118398 | 0.384115 | 0.502513 | [0.106 0.894] | 0.406 |
+| (0.3, 77) | 0.139943 | 0.259057 | 0.399 | [0.099 0.601 0. 0.3 ] | 0.116276 | 0.383307 | 0.499584 | [0.099 0.901] | 0.399 |
+| (0.3, 78) | 0.13643 | 0.26457 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.112532 | 0.387885 | 0.500417 | [0.101 0.899] | 0.401 |
+| (0.3, 79) | 0.113834 | 0.290166 | 0.404 | [0.104 0.596 0. 0.3 ] | 0.103453 | 0.398219 | 0.501672 | [0.104 0.896] | 0.404 |
+| (0.3, 80) | 0.162074 | 0.225926 | 0.388 | [0.089 0.611 0.001 0.299] | 0.127037 | 0.367178 | 0.494215 | [0.09 0.91] | 0.388 |
+| (0.3, 81) | 0.112507 | 0.294493 | 0.407 | [0.107 0.593 0. 0.3 ] | 0.112868 | 0.390066 | 0.502934 | [0.107 0.893] | 0.407 |
+| (0.3, 82) | 0.137672 | 0.250328 | 0.388 | [0.088 0.612 0. 0.3 ] | 0.107459 | 0.38759 | 0.49505 | [0.088 0.912] | 0.388 |
+| (0.3, 83) | 0.11512 | 0.29688 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.0942575 | 0.410793 | 0.505051 | [0.112 0.888] | 0.412 |
+| (0.3, 84) | 0.103276 | 0.290724 | 0.394 | [0.096 0.604 0.002 0.298] | 0.0984201 | 0.39742 | 0.49584 | [0.098 0.902] | 0.394 |
+| (0.3, 85) | 0.128535 | 0.269465 | 0.398 | [0.099 0.601 0.001 0.299] | 0.102733 | 0.3956 | 0.498333 | [0.1 0.9] | 0.398 |
+| (0.3, 86) | 0.117567 | 0.290433 | 0.408 | [0.108 0.592 0. 0.3 ] | 0.11328 | 0.390076 | 0.503356 | [0.108 0.892] | 0.408 |
+| (0.3, 87) | 0.141018 | 0.252982 | 0.394 | [0.096 0.604 0.002 0.298] | 0.108792 | 0.387049 | 0.49584 | [0.098 0.902] | 0.394 |
+| (0.3, 88) | 0.114183 | 0.286817 | 0.401 | [0.101 0.599 0. 0.3 ] | 0.092482 | 0.407935 | 0.500417 | [0.101 0.899] | 0.401 |
+| (0.3, 89) | 0.110207 | 0.302793 | 0.413 | [0.114 0.586 0.001 0.299] | 0.117155 | 0.387487 | 0.504641 | [0.115 0.885] | 0.413 |
+| (0.3, 90) | 0.129401 | 0.284599 | 0.414 | [0.114 0.586 0. 0.3 ] | 0.10979 | 0.396113 | 0.505902 | [0.114 0.886] | 0.414 |
+| (0.3, 91) | 0.12667 | 0.28733 | 0.414 | [0.115 0.585 0.001 0.299] | 0.109093 | 0.395974 | 0.505068 | [0.116 0.884] | 0.414 |
+| (0.3, 92) | 0.0895823 | 0.309418 | 0.399 | [0.1 0.6 0.001 0.299] | 0.0919172 | 0.406832 | 0.498749 | [0.101 0.899] | 0.399 |
+| (0.3, 93) | 0.13851 | 0.26349 | 0.402 | [0.103 0.597 0.001 0.299] | 0.116828 | 0.383172 | 0.5 | [0.104 0.896] | 0.402 |
+| (0.3, 94) | 0.110087 | 0.308913 | 0.419 | [0.12 0.58 0.001 0.299] | 0.103164 | 0.404046 | 0.507209 | [0.121 0.879] | 0.419 |
+| (0.3, 95) | 0.120184 | 0.297816 | 0.418 | [0.118 0.582 0. 0.3 ] | 0.098135 | 0.409479 | 0.507614 | [0.118 0.882] | 0.418 |
+| (0.3, 96) | 0.133316 | 0.256684 | 0.39 | [0.09 0.61 0. 0.3 ] | 0.116543 | 0.379325 | 0.495868 | [0.09 0.91] | 0.39 |
+| (0.3, 97) | 0.0983323 | 0.313668 | 0.412 | [0.112 0.588 0. 0.3 ] | 0.0720765 | 0.432974 | 0.505051 | [0.112 0.888] | 0.412 |
+| (0.3, 98) | 0.136707 | 0.279293 | 0.416 | [0.116 0.584 0. 0.3 ] | 0.113834 | 0.392923 | 0.506757 | [0.116 0.884] | 0.416 |
+| (0.3, 99) | 0.128764 | 0.277236 | 0.406 | [0.106 0.594 0. 0.3 ] | 0.127621 | 0.374892 | 0.502513 | [0.106 0.894] | 0.406 |
+| (0.35, 0) | 0.127734 | 0.323266 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.106 | 0.454448 | 0.560448 | [0.101 0.899] | 0.451 |
+| (0.35, 1) | 0.126857 | 0.316143 | 0.443 | [0.093 0.557 0. 0.35 ] | 0.113086 | 0.443795 | 0.556881 | [0.093 0.907] | 0.443 |
+| (0.35, 2) | 0.0879283 | 0.358072 | 0.446 | [0.097 0.553 0.001 0.349] | 0.0770572 | 0.480451 | 0.557508 | [0.098 0.902] | 0.446 |
+| (0.35, 3) | 0.111434 | 0.340566 | 0.452 | [0.102 0.548 0. 0.35 ] | 0.107314 | 0.453583 | 0.560897 | [0.102 0.898] | 0.452 |
+| (0.35, 4) | 0.158193 | 0.295807 | 0.454 | [0.104 0.546 0. 0.35 ] | 0.132322 | 0.429476 | 0.561798 | [0.104 0.896] | 0.454 |
+| (0.35, 5) | 0.120109 | 0.325891 | 0.446 | [0.097 0.553 0.001 0.349] | 0.112725 | 0.444783 | 0.557508 | [0.098 0.902] | 0.446 |
+| (0.35, 6) | 0.0941796 | 0.35182 | 0.446 | [0.096 0.554 0. 0.35 ] | 0.0882179 | 0.469996 | 0.558214 | [0.096 0.904] | 0.446 |
+| (0.35, 7) | 0.103097 | 0.345903 | 0.449 | [0.099 0.551 0. 0.35 ] | 0.099472 | 0.46008 | 0.559552 | [0.099 0.901] | 0.449 |
+| (0.35, 8) | 0.138126 | 0.330874 | 0.469 | [0.119 0.531 0. 0.35 ] | 0.100208 | 0.468435 | 0.568643 | [0.119 0.881] | 0.469 |
+| (0.35, 9) | 0.107922 | 0.347078 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.0834859 | 0.478763 | 0.562249 | [0.105 0.895] | 0.455 |
+| (0.35, 10) | 0.0992061 | 0.337794 | 0.437 | [0.087 0.563 0. 0.35 ] | 0.091621 | 0.462615 | 0.554236 | [0.087 0.913] | 0.437 |
+| (0.35, 11) | 0.105041 | 0.344959 | 0.45 | [0.1 0.55 0. 0.35] | 0.0902889 | 0.469711 | 0.56 | [0.1 0.9] | 0.45 |
+| (0.35, 12) | 0.100877 | 0.350123 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.0870643 | 0.473384 | 0.560448 | [0.101 0.899] | 0.451 |
+| (0.35, 13) | 0.0960624 | 0.345938 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0724629 | 0.483976 | 0.556439 | [0.092 0.908] | 0.442 |
+| (0.35, 14) | 0.131091 | 0.299909 | 0.431 | [0.081 0.569 0. 0.35 ] | 0.112462 | 0.439153 | 0.551615 | [0.081 0.919] | 0.431 |
+| (0.35, 15) | 0.120561 | 0.325439 | 0.446 | [0.097 0.553 0.001 0.349] | 0.0972215 | 0.460286 | 0.557508 | [0.098 0.902] | 0.446 |
+| (0.35, 16) | 0.107446 | 0.339554 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.0781809 | 0.480478 | 0.558659 | [0.097 0.903] | 0.447 |
+| (0.35, 17) | 0.12172 | 0.33228 | 0.454 | [0.104 0.546 0. 0.35 ] | 0.0898545 | 0.471943 | 0.561798 | [0.104 0.896] | 0.454 |
+| (0.35, 18) | 0.110049 | 0.365951 | 0.476 | [0.126 0.524 0. 0.35 ] | 0.0858809 | 0.486014 | 0.571895 | [0.126 0.874] | 0.476 |
+| (0.35, 19) | 0.108301 | 0.329699 | 0.438 | [0.089 0.561 0.001 0.349] | 0.0928654 | 0.461103 | 0.553968 | [0.09 0.91] | 0.438 |
+| (0.35, 20) | 0.113459 | 0.319541 | 0.433 | [0.083 0.567 0. 0.35 ] | 0.087382 | 0.465104 | 0.552486 | [0.083 0.917] | 0.433 |
+| (0.35, 21) | 0.123105 | 0.329895 | 0.453 | [0.103 0.547 0. 0.35 ] | 0.105268 | 0.456079 | 0.561347 | [0.103 0.897] | 0.453 |
+| (0.35, 22) | 0.113375 | 0.345625 | 0.459 | [0.109 0.541 0. 0.35 ] | 0.0933376 | 0.470724 | 0.564061 | [0.109 0.891] | 0.459 |
+| (0.35, 23) | 0.118606 | 0.329394 | 0.448 | [0.098 0.552 0. 0.35 ] | 0.0897363 | 0.469369 | 0.559105 | [0.098 0.902] | 0.448 |
+| (0.35, 24) | 0.127113 | 0.306887 | 0.434 | [0.085 0.565 0.001 0.349] | 0.0946077 | 0.457607 | 0.552215 | [0.086 0.914] | 0.434 |
+| (0.35, 25) | 0.119535 | 0.320465 | 0.44 | [0.09 0.56 0. 0.35] | 0.115511 | 0.440044 | 0.555556 | [0.09 0.91] | 0.44 |
+| (0.35, 26) | 0.0883172 | 0.344683 | 0.433 | [0.084 0.566 0.001 0.349] | 0.0744312 | 0.477347 | 0.551779 | [0.085 0.915] | 0.433 |
+| (0.35, 27) | 0.166992 | 0.279008 | 0.446 | [0.096 0.554 0. 0.35 ] | 0.137423 | 0.42079 | 0.558214 | [0.096 0.904] | 0.446 |
+| (0.35, 28) | 0.0954868 | 0.340513 | 0.436 | [0.087 0.563 0.001 0.349] | 0.0830672 | 0.470023 | 0.55309 | [0.088 0.912] | 0.436 |
+| (0.35, 29) | 0.0778668 | 0.367133 | 0.445 | [0.096 0.554 0.001 0.349] | 0.0649534 | 0.49211 | 0.557063 | [0.097 0.903] | 0.445 |
+| (0.35, 30) | 0.107221 | 0.325779 | 0.433 | [0.083 0.567 0. 0.35 ] | 0.0822103 | 0.470276 | 0.552486 | [0.083 0.917] | 0.433 |
+| (0.35, 31) | 0.102419 | 0.339581 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0894659 | 0.466973 | 0.556439 | [0.092 0.908] | 0.442 |
+| (0.35, 32) | 0.119917 | 0.328083 | 0.448 | [0.098 0.552 0. 0.35 ] | 0.0886716 | 0.470434 | 0.559105 | [0.098 0.902] | 0.448 |
+| (0.35, 33) | 0.11129 | 0.34371 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.0841548 | 0.478094 | 0.562249 | [0.105 0.895] | 0.455 |
+| (0.35, 34) | 0.101306 | 0.349694 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.0869425 | 0.473506 | 0.560448 | [0.101 0.899] | 0.451 |
+| (0.35, 35) | 0.109456 | 0.333544 | 0.443 | [0.094 0.556 0.001 0.349] | 0.106623 | 0.449552 | 0.556175 | [0.095 0.905] | 0.443 |
+| (0.35, 36) | 0.0992197 | 0.34478 | 0.444 | [0.094 0.556 0. 0.35 ] | 0.0943453 | 0.46298 | 0.557325 | [0.094 0.906] | 0.444 |
+| (0.35, 37) | 0.150907 | 0.288093 | 0.439 | [0.09 0.56 0.001 0.349] | 0.119051 | 0.435357 | 0.554408 | [0.091 0.909] | 0.439 |
+| (0.35, 38) | 0.109748 | 0.325252 | 0.435 | [0.085 0.565 0. 0.35 ] | 0.0863649 | 0.466995 | 0.55336 | [0.085 0.915] | 0.435 |
+| (0.35, 39) | 0.145428 | 0.291572 | 0.437 | [0.088 0.562 0.001 0.349] | 0.128978 | 0.424551 | 0.553529 | [0.089 0.911] | 0.437 |
+| (0.35, 40) | 0.098426 | 0.360574 | 0.459 | [0.11 0.54 0.001 0.349] | 0.07388 | 0.489478 | 0.563358 | [0.111 0.889] | 0.459 |
+| (0.35, 41) | 0.13594 | 0.31106 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.116727 | 0.441932 | 0.558659 | [0.097 0.903] | 0.447 |
+| (0.35, 42) | 0.123184 | 0.312816 | 0.436 | [0.086 0.564 0. 0.35 ] | 0.114021 | 0.439777 | 0.553797 | [0.086 0.914] | 0.436 |
+| (0.35, 43) | 0.128692 | 0.318308 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.102665 | 0.455994 | 0.558659 | [0.097 0.903] | 0.447 |
+| (0.35, 44) | 0.136286 | 0.292714 | 0.429 | [0.08 0.57 0.001 0.349] | 0.104948 | 0.445091 | 0.550039 | [0.081 0.919] | 0.429 |
+| (0.35, 45) | 0.108885 | 0.336115 | 0.445 | [0.095 0.555 0. 0.35 ] | 0.0977137 | 0.460055 | 0.557769 | [0.095 0.905] | 0.445 |
+| (0.35, 46) | 0.112286 | 0.334714 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.102874 | 0.455785 | 0.558659 | [0.097 0.903] | 0.447 |
+| (0.35, 47) | 0.0906932 | 0.369307 | 0.46 | [0.11 0.54 0. 0.35] | 0.0778993 | 0.486617 | 0.564516 | [0.11 0.89] | 0.46 |
+| (0.35, 48) | 0.137978 | 0.315022 | 0.453 | [0.103 0.547 0. 0.35 ] | 0.102033 | 0.459314 | 0.561347 | [0.103 0.897] | 0.453 |
+| (0.35, 49) | 0.116168 | 0.334832 | 0.451 | [0.101 0.549 0. 0.35 ] | 0.0912107 | 0.469238 | 0.560448 | [0.101 0.899] | 0.451 |
+| (0.35, 50) | 0.104287 | 0.334713 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.0944456 | 0.460669 | 0.555115 | [0.089 0.911] | 0.439 |
+| (0.35, 51) | 0.128891 | 0.313109 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0930384 | 0.4634 | 0.556439 | [0.092 0.908] | 0.442 |
+| (0.35, 52) | 0.113322 | 0.357678 | 0.471 | [0.121 0.529 0. 0.35 ] | 0.100441 | 0.469128 | 0.569569 | [0.121 0.879] | 0.471 |
+| (0.35, 53) | 0.104489 | 0.331511 | 0.436 | [0.086 0.564 0. 0.35 ] | 0.0901448 | 0.463653 | 0.553797 | [0.086 0.914] | 0.436 |
+| (0.35, 54) | 0.0996681 | 0.346332 | 0.446 | [0.096 0.554 0. 0.35 ] | 0.0920318 | 0.466182 | 0.558214 | [0.096 0.904] | 0.446 |
+| (0.35, 55) | 0.119316 | 0.311684 | 0.431 | [0.081 0.569 0. 0.35 ] | 0.108829 | 0.442786 | 0.551615 | [0.081 0.919] | 0.431 |
+| (0.35, 56) | 0.133962 | 0.304038 | 0.438 | [0.089 0.561 0.001 0.349] | 0.106918 | 0.44705 | 0.553968 | [0.09 0.91] | 0.438 |
+| (0.35, 57) | 0.138717 | 0.316283 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.11544 | 0.446809 | 0.562249 | [0.105 0.895] | 0.455 |
+| (0.35, 58) | 0.139865 | 0.314135 | 0.454 | [0.105 0.545 0.001 0.349] | 0.0996406 | 0.461453 | 0.561093 | [0.106 0.894] | 0.454 |
+| (0.35, 59) | 0.117694 | 0.326306 | 0.444 | [0.094 0.556 0. 0.35 ] | 0.0946397 | 0.462685 | 0.557325 | [0.094 0.906] | 0.444 |
+| (0.35, 60) | 0.0823521 | 0.383648 | 0.466 | [0.116 0.534 0. 0.35 ] | 0.0751242 | 0.492137 | 0.567261 | [0.116 0.884] | 0.466 |
+| (0.35, 61) | 0.114932 | 0.324068 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.107789 | 0.447326 | 0.555115 | [0.089 0.911] | 0.439 |
+| (0.35, 62) | 0.0971008 | 0.341899 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.0794721 | 0.475643 | 0.555115 | [0.089 0.911] | 0.439 |
+| (0.35, 63) | 0.114859 | 0.339141 | 0.454 | [0.105 0.545 0.001 0.349] | 0.101821 | 0.459272 | 0.561093 | [0.106 0.894] | 0.454 |
+| (0.35, 64) | 0.105616 | 0.336384 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.0953635 | 0.461075 | 0.556439 | [0.092 0.908] | 0.442 |
+| (0.35, 65) | 0.109411 | 0.330589 | 0.44 | [0.09 0.56 0. 0.35] | 0.0857621 | 0.469794 | 0.555556 | [0.09 0.91] | 0.44 |
+| (0.35, 66) | 0.139524 | 0.314476 | 0.454 | [0.104 0.546 0. 0.35 ] | 0.113682 | 0.448115 | 0.561798 | [0.104 0.896] | 0.454 |
+| (0.35, 67) | 0.114339 | 0.340661 | 0.455 | [0.105 0.545 0. 0.35 ] | 0.106207 | 0.456042 | 0.562249 | [0.105 0.895] | 0.455 |
+| (0.35, 68) | 0.115384 | 0.316616 | 0.432 | [0.082 0.568 0. 0.35 ] | 0.104768 | 0.447283 | 0.55205 | [0.082 0.918] | 0.432 |
+| (0.35, 69) | 0.136346 | 0.305654 | 0.442 | [0.092 0.558 0. 0.35 ] | 0.111795 | 0.444644 | 0.556439 | [0.092 0.908] | 0.442 |
+| (0.35, 70) | 0.120153 | 0.319847 | 0.44 | [0.09 0.56 0. 0.35] | 0.109676 | 0.44588 | 0.555556 | [0.09 0.91] | 0.44 |
+| (0.35, 71) | 0.111197 | 0.350803 | 0.462 | [0.112 0.538 0. 0.35 ] | 0.081468 | 0.48396 | 0.565428 | [0.112 0.888] | 0.462 |
+| (0.35, 72) | 0.13692 | 0.30608 | 0.443 | [0.093 0.557 0. 0.35 ] | 0.117318 | 0.439564 | 0.556881 | [0.093 0.907] | 0.443 |
+| (0.35, 73) | 0.124503 | 0.328497 | 0.453 | [0.103 0.547 0. 0.35 ] | 0.0945593 | 0.466788 | 0.561347 | [0.103 0.897] | 0.453 |
+| (0.35, 74) | 0.136985 | 0.301015 | 0.438 | [0.088 0.562 0. 0.35 ] | 0.0994015 | 0.455274 | 0.554675 | [0.088 0.912] | 0.438 |
+| (0.35, 75) | 0.122077 | 0.331923 | 0.454 | [0.106 0.544 0.002 0.348] | 0.0941126 | 0.466274 | 0.560386 | [0.108 0.892] | 0.454 |
+| (0.35, 76) | 0.105174 | 0.352826 | 0.458 | [0.109 0.541 0.001 0.349] | 0.0934764 | 0.469427 | 0.562903 | [0.11 0.89] | 0.458 |
+| (0.35, 77) | 0.109797 | 0.325203 | 0.435 | [0.086 0.564 0.001 0.349] | 0.0970415 | 0.455611 | 0.552652 | [0.087 0.913] | 0.435 |
+| (0.35, 78) | 0.103501 | 0.344499 | 0.448 | [0.098 0.552 0. 0.35 ] | 0.0972722 | 0.461833 | 0.559105 | [0.098 0.902] | 0.448 |
+| (0.35, 79) | 0.0992824 | 0.347718 | 0.447 | [0.097 0.553 0. 0.35 ] | 0.0883709 | 0.470288 | 0.558659 | [0.097 0.903] | 0.447 |
+| (0.35, 80) | 0.0864577 | 0.359542 | 0.446 | [0.097 0.553 0.001 0.349] | 0.0811096 | 0.476398 | 0.557508 | [0.098 0.902] | 0.446 |
+| (0.35, 81) | 0.0944448 | 0.362555 | 0.457 | [0.107 0.543 0. 0.35 ] | 0.0824714 | 0.480682 | 0.563154 | [0.107 0.893] | 0.457 |
+| (0.35, 82) | 0.131583 | 0.318417 | 0.45 | [0.101 0.549 0.001 0.349] | 0.10794 | 0.451355 | 0.559295 | [0.102 0.898] | 0.45 |
+| (0.35, 83) | 0.120998 | 0.331002 | 0.452 | [0.102 0.548 0. 0.35 ] | 0.104399 | 0.456498 | 0.560897 | [0.102 0.898] | 0.452 |
+| (0.35, 84) | 0.106906 | 0.345094 | 0.452 | [0.103 0.547 0.001 0.349] | 0.0750503 | 0.485142 | 0.560193 | [0.104 0.896] | 0.452 |
+| (0.35, 85) | 0.120944 | 0.337056 | 0.458 | [0.108 0.542 0. 0.35 ] | 0.0885901 | 0.475017 | 0.563607 | [0.108 0.892] | 0.458 |
+| (0.35, 86) | 0.105667 | 0.339333 | 0.445 | [0.095 0.555 0. 0.35 ] | 0.0975882 | 0.460181 | 0.557769 | [0.095 0.905] | 0.445 |
+| (0.35, 87) | 0.14568 | 0.29532 | 0.441 | [0.091 0.559 0. 0.35 ] | 0.114812 | 0.441184 | 0.555997 | [0.091 0.909] | 0.441 |
+| (0.35, 88) | 0.113016 | 0.325984 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.106299 | 0.448816 | 0.555115 | [0.089 0.911] | 0.439 |
+| (0.35, 89) | 0.100033 | 0.342967 | 0.443 | [0.093 0.557 0. 0.35 ] | 0.0877762 | 0.469105 | 0.556881 | [0.093 0.907] | 0.443 |
+| (0.35, 90) | 0.130903 | 0.300097 | 0.431 | [0.081 0.569 0. 0.35 ] | 0.128361 | 0.423255 | 0.551615 | [0.081 0.919] | 0.431 |
+| (0.35, 91) | 0.124577 | 0.332423 | 0.457 | [0.107 0.543 0. 0.35 ] | 0.0952436 | 0.46791 | 0.563154 | [0.107 0.893] | 0.457 |
+| (0.35, 92) | 0.105592 | 0.333408 | 0.439 | [0.089 0.561 0. 0.35 ] | 0.098634 | 0.456481 | 0.555115 | [0.089 0.911] | 0.439 |
+| (0.35, 93) | 0.140823 | 0.304177 | 0.445 | [0.096 0.554 0.001 0.349] | 0.125783 | 0.43128 | 0.557063 | [0.097 0.903] | 0.445 |
+| (0.35, 94) | 0.121894 | 0.316106 | 0.438 | [0.089 0.561 0.001 0.349] | 0.0975567 | 0.456412 | 0.553968 | [0.09 0.91] | 0.438 |
+| (0.35, 95) | 0.111933 | 0.332067 | 0.444 | [0.094 0.556 0. 0.35 ] | 0.106763 | 0.450562 | 0.557325 | [0.094 0.906] | 0.444 |
+| (0.35, 96) | 0.116825 | 0.334175 | 0.451 | [0.102 0.548 0.001 0.349] | 0.098681 | 0.461062 | 0.559743 | [0.103 0.897] | 0.451 |
+| (0.35, 97) | 0.0768109 | 0.383189 | 0.46 | [0.11 0.54 0. 0.35] | 0.0613629 | 0.503153 | 0.564516 | [0.11 0.89] | 0.46 |
+| (0.35, 98) | 0.1058 | 0.3342 | 0.44 | [0.09 0.56 0. 0.35] | 0.0989152 | 0.45664 | 0.555556 | [0.09 0.91] | 0.44 |
+| (0.35, 99) | 0.117609 | 0.317391 | 0.435 | [0.085 0.565 0. 0.35 ] | 0.0861184 | 0.467241 | 0.55336 | [0.085 0.915] | 0.435 |
+| (0.4, 0) | 0.092345 | 0.401655 | 0.494 | [0.094 0.506 0. 0.4 ] | 0.0832232 | 0.529334 | 0.612557 | [0.094 0.906] | 0.494 |
+| (0.4, 1) | 0.110067 | 0.369933 | 0.48 | [0.081 0.519 0.001 0.399] | 0.0940139 | 0.511449 | 0.605463 | [0.082 0.918] | 0.48 |
+| (0.4, 2) | 0.10932 | 0.38868 | 0.498 | [0.098 0.502 0. 0.4 ] | 0.0823125 | 0.532127 | 0.614439 | [0.098 0.902] | 0.498 |
+| (0.4, 3) | 0.140325 | 0.344675 | 0.485 | [0.085 0.515 0. 0.4 ] | 0.109529 | 0.498836 | 0.608365 | [0.085 0.915] | 0.485 |
+| (0.4, 4) | 0.113004 | 0.369996 | 0.483 | [0.085 0.515 0.002 0.398] | 0.100758 | 0.505487 | 0.606245 | [0.087 0.913] | 0.483 |
+| (0.4, 5) | 0.102619 | 0.402381 | 0.505 | [0.106 0.494 0.001 0.399] | 0.0800786 | 0.537091 | 0.617169 | [0.107 0.893] | 0.505 |
+| (0.4, 6) | 0.121988 | 0.385012 | 0.507 | [0.107 0.493 0. 0.4 ] | 0.0934156 | 0.525301 | 0.618716 | [0.107 0.893] | 0.507 |
+| (0.4, 7) | 0.111719 | 0.373281 | 0.485 | [0.085 0.515 0. 0.4 ] | 0.0860944 | 0.522271 | 0.608365 | [0.085 0.915] | 0.485 |
+| (0.4, 8) | 0.103077 | 0.391923 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0934454 | 0.519581 | 0.613027 | [0.095 0.905] | 0.495 |
+| (0.4, 9) | 0.09463 | 0.39437 | 0.489 | [0.089 0.511 0. 0.4 ] | 0.0841998 | 0.526021 | 0.610221 | [0.089 0.911] | 0.489 |
+| (0.4, 10) | 0.114552 | 0.377448 | 0.492 | [0.092 0.508 0. 0.4 ] | 0.0829579 | 0.528663 | 0.611621 | [0.092 0.908] | 0.492 |
+| (0.4, 11) | 0.0881744 | 0.402826 | 0.491 | [0.091 0.509 0. 0.4 ] | 0.080588 | 0.530566 | 0.611154 | [0.091 0.909] | 0.491 |
+| (0.4, 12) | 0.116386 | 0.369614 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0788718 | 0.529956 | 0.608828 | [0.086 0.914] | 0.486 |
+| (0.4, 13) | 0.082174 | 0.422826 | 0.505 | [0.106 0.494 0.001 0.399] | 0.0696855 | 0.547484 | 0.617169 | [0.107 0.893] | 0.505 |
+| (0.4, 14) | 0.10176 | 0.38824 | 0.49 | [0.09 0.51 0. 0.4 ] | 0.0850318 | 0.525655 | 0.610687 | [0.09 0.91] | 0.49 |
+| (0.4, 15) | 0.0911766 | 0.404823 | 0.496 | [0.097 0.503 0.001 0.399] | 0.0791771 | 0.533726 | 0.612903 | [0.098 0.902] | 0.496 |
+| (0.4, 16) | 0.148433 | 0.335567 | 0.484 | [0.084 0.516 0. 0.4 ] | 0.105864 | 0.502038 | 0.607903 | [0.084 0.916] | 0.484 |
+| (0.4, 17) | 0.0972479 | 0.395752 | 0.493 | [0.093 0.507 0. 0.4 ] | 0.0776354 | 0.534453 | 0.612089 | [0.093 0.907] | 0.493 |
+| (0.4, 18) | 0.0899533 | 0.390047 | 0.48 | [0.08 0.52 0. 0.4 ] | 0.0751172 | 0.530943 | 0.606061 | [0.08 0.92] | 0.48 |
+| (0.4, 19) | 0.0985107 | 0.395489 | 0.494 | [0.094 0.506 0. 0.4 ] | 0.0900225 | 0.522535 | 0.612557 | [0.094 0.906] | 0.494 |
+| (0.4, 20) | 0.133984 | 0.358016 | 0.492 | [0.093 0.507 0.001 0.399] | 0.100027 | 0.510999 | 0.611026 | [0.094 0.906] | 0.492 |
+| (0.4, 21) | 0.107137 | 0.388863 | 0.496 | [0.096 0.504 0. 0.4 ] | 0.0792101 | 0.534287 | 0.613497 | [0.096 0.904] | 0.496 |
+| (0.4, 22) | 0.0939334 | 0.401067 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0811591 | 0.531868 | 0.613027 | [0.095 0.905] | 0.495 |
+| (0.4, 23) | 0.119607 | 0.363393 | 0.483 | [0.085 0.515 0.002 0.398] | 0.0741715 | 0.532074 | 0.606245 | [0.087 0.913] | 0.483 |
+| (0.4, 24) | 0.0886681 | 0.402332 | 0.491 | [0.092 0.508 0.001 0.399] | 0.0779011 | 0.532657 | 0.610559 | [0.093 0.907] | 0.491 |
+| (0.4, 25) | 0.120708 | 0.361292 | 0.482 | [0.083 0.517 0.001 0.399] | 0.0967001 | 0.509683 | 0.606383 | [0.084 0.916] | 0.482 |
+| (0.4, 26) | 0.115847 | 0.372153 | 0.488 | [0.088 0.512 0. 0.4 ] | 0.090602 | 0.519154 | 0.609756 | [0.088 0.912] | 0.488 |
+| (0.4, 27) | 0.0823224 | 0.418678 | 0.501 | [0.101 0.499 0. 0.4 ] | 0.0663761 | 0.549482 | 0.615858 | [0.101 0.899] | 0.501 |
+| (0.4, 28) | 0.126811 | 0.354189 | 0.481 | [0.081 0.519 0. 0.4 ] | 0.0952304 | 0.51129 | 0.60652 | [0.081 0.919] | 0.481 |
+| (0.4, 29) | 0.120102 | 0.370898 | 0.491 | [0.091 0.509 0. 0.4 ] | 0.0952146 | 0.515939 | 0.611154 | [0.091 0.909] | 0.491 |
+| (0.4, 30) | 0.1235 | 0.3405 | 0.464 | [0.064 0.536 0. 0.4 ] | 0.0918379 | 0.506964 | 0.598802 | [0.064 0.936] | 0.464 |
+| (0.4, 31) | 0.116506 | 0.369494 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0997973 | 0.509031 | 0.608828 | [0.086 0.914] | 0.486 |
+| (0.4, 32) | 0.129958 | 0.359042 | 0.489 | [0.089 0.511 0. 0.4 ] | 0.0956325 | 0.514589 | 0.610221 | [0.089 0.911] | 0.489 |
+| (0.4, 33) | 0.101764 | 0.388236 | 0.49 | [0.09 0.51 0. 0.4 ] | 0.0904647 | 0.520222 | 0.610687 | [0.09 0.91] | 0.49 |
+| (0.4, 34) | 0.111378 | 0.382622 | 0.494 | [0.094 0.506 0. 0.4 ] | 0.0774008 | 0.535157 | 0.612557 | [0.094 0.906] | 0.494 |
+| (0.4, 35) | 0.118964 | 0.369036 | 0.488 | [0.089 0.511 0.001 0.399] | 0.0925809 | 0.516579 | 0.60916 | [0.09 0.91] | 0.488 |
+| (0.4, 36) | 0.107617 | 0.379383 | 0.487 | [0.087 0.513 0. 0.4 ] | 0.0748225 | 0.534469 | 0.609292 | [0.087 0.913] | 0.487 |
+| (0.4, 37) | 0.104499 | 0.377501 | 0.482 | [0.083 0.517 0.001 0.399] | 0.0941583 | 0.512225 | 0.606383 | [0.084 0.916] | 0.482 |
+| (0.4, 38) | 0.0908303 | 0.38517 | 0.476 | [0.077 0.523 0.001 0.399] | 0.0805585 | 0.523072 | 0.603631 | [0.078 0.922] | 0.476 |
+| (0.4, 39) | 0.141925 | 0.327075 | 0.469 | [0.069 0.531 0. 0.4 ] | 0.109778 | 0.491274 | 0.601052 | [0.069 0.931] | 0.469 |
+| (0.4, 40) | 0.113013 | 0.380987 | 0.494 | [0.095 0.505 0.001 0.399] | 0.0873407 | 0.524622 | 0.611963 | [0.096 0.904] | 0.494 |
+| (0.4, 41) | 0.103835 | 0.397165 | 0.501 | [0.101 0.499 0. 0.4 ] | 0.0760962 | 0.539762 | 0.615858 | [0.101 0.899] | 0.501 |
+| (0.4, 42) | 0.117133 | 0.378867 | 0.496 | [0.097 0.503 0.001 0.399] | 0.0906409 | 0.522262 | 0.612903 | [0.098 0.902] | 0.496 |
+| (0.4, 43) | 0.0771431 | 0.416857 | 0.494 | [0.096 0.504 0.002 0.398] | 0.065077 | 0.54629 | 0.611367 | [0.098 0.902] | 0.494 |
+| (0.4, 44) | 0.0940821 | 0.384918 | 0.479 | [0.079 0.521 0. 0.4 ] | 0.083618 | 0.521984 | 0.605602 | [0.079 0.921] | 0.479 |
+| (0.4, 45) | 0.100887 | 0.379113 | 0.48 | [0.081 0.519 0.001 0.399] | 0.098478 | 0.506985 | 0.605463 | [0.082 0.918] | 0.48 |
+| (0.4, 46) | 0.0877998 | 0.4042 | 0.492 | [0.093 0.507 0.001 0.399] | 0.0742074 | 0.536819 | 0.611026 | [0.094 0.906] | 0.492 |
+| (0.4, 47) | 0.133793 | 0.343207 | 0.477 | [0.077 0.523 0. 0.4 ] | 0.111633 | 0.493053 | 0.604686 | [0.077 0.923] | 0.477 |
+| (0.4, 48) | 0.104751 | 0.391249 | 0.496 | [0.096 0.504 0. 0.4 ] | 0.0948151 | 0.518682 | 0.613497 | [0.096 0.904] | 0.496 |
+| (0.4, 49) | 0.111086 | 0.372914 | 0.484 | [0.085 0.515 0.001 0.399] | 0.0854655 | 0.52184 | 0.607306 | [0.086 0.914] | 0.484 |
+| (0.4, 50) | 0.115748 | 0.367252 | 0.483 | [0.084 0.516 0.001 0.399] | 0.0794044 | 0.52744 | 0.606844 | [0.085 0.915] | 0.483 |
+| (0.4, 51) | 0.111478 | 0.389522 | 0.501 | [0.101 0.499 0. 0.4 ] | 0.094504 | 0.521354 | 0.615858 | [0.101 0.899] | 0.501 |
+| (0.4, 52) | 0.116461 | 0.378539 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0778475 | 0.535179 | 0.613027 | [0.095 0.905] | 0.495 |
+| (0.4, 53) | 0.129073 | 0.340927 | 0.47 | [0.071 0.529 0.001 0.399] | 0.10103 | 0.499874 | 0.600904 | [0.072 0.928] | 0.47 |
+| (0.4, 54) | 0.070972 | 0.413028 | 0.484 | [0.085 0.515 0.001 0.399] | 0.0619927 | 0.545313 | 0.607306 | [0.086 0.914] | 0.484 |
+| (0.4, 55) | 0.117027 | 0.363973 | 0.481 | [0.081 0.519 0. 0.4 ] | 0.100197 | 0.506323 | 0.60652 | [0.081 0.919] | 0.481 |
+| (0.4, 56) | 0.116247 | 0.360753 | 0.477 | [0.077 0.523 0. 0.4 ] | 0.0981762 | 0.50651 | 0.604686 | [0.077 0.923] | 0.477 |
+| (0.4, 57) | 0.0605851 | 0.419415 | 0.48 | [0.08 0.52 0. 0.4 ] | 0.0531007 | 0.55296 | 0.606061 | [0.08 0.92] | 0.48 |
+| (0.4, 58) | 0.123128 | 0.349872 | 0.473 | [0.073 0.527 0. 0.4 ] | 0.0887936 | 0.51407 | 0.602864 | [0.073 0.927] | 0.473 |
+| (0.4, 59) | 0.118622 | 0.362378 | 0.481 | [0.081 0.519 0. 0.4 ] | 0.0999178 | 0.506602 | 0.60652 | [0.081 0.919] | 0.481 |
+| (0.4, 60) | 0.127352 | 0.347648 | 0.475 | [0.075 0.525 0. 0.4 ] | 0.0978482 | 0.505925 | 0.603774 | [0.075 0.925] | 0.475 |
+| (0.4, 61) | 0.106386 | 0.353614 | 0.46 | [0.061 0.539 0.001 0.399] | 0.0804344 | 0.515978 | 0.596413 | [0.062 0.938] | 0.46 |
+| (0.4, 62) | 0.0924329 | 0.395567 | 0.488 | [0.089 0.511 0.001 0.399] | 0.0820076 | 0.527153 | 0.60916 | [0.09 0.91] | 0.488 |
+| (0.4, 63) | 0.105464 | 0.381536 | 0.487 | [0.087 0.513 0. 0.4 ] | 0.0768776 | 0.532414 | 0.609292 | [0.087 0.913] | 0.487 |
+| (0.4, 64) | 0.103833 | 0.377167 | 0.481 | [0.082 0.518 0.001 0.399] | 0.0846173 | 0.521305 | 0.605923 | [0.083 0.917] | 0.481 |
+| (0.4, 65) | 0.099706 | 0.378294 | 0.478 | [0.079 0.521 0.001 0.399] | 0.0838127 | 0.520733 | 0.604545 | [0.08 0.92] | 0.478 |
+| (0.4, 66) | 0.138331 | 0.336669 | 0.475 | [0.076 0.524 0.001 0.399] | 0.103986 | 0.499188 | 0.603175 | [0.077 0.923] | 0.475 |
+| (0.4, 67) | 0.0768523 | 0.407148 | 0.484 | [0.084 0.516 0. 0.4 ] | 0.0699597 | 0.537943 | 0.607903 | [0.084 0.916] | 0.484 |
+| (0.4, 68) | 0.12711 | 0.35589 | 0.483 | [0.083 0.517 0. 0.4 ] | 0.106317 | 0.501125 | 0.607441 | [0.083 0.917] | 0.483 |
+| (0.4, 69) | 0.0883312 | 0.388669 | 0.477 | [0.077 0.523 0. 0.4 ] | 0.0754731 | 0.529213 | 0.604686 | [0.077 0.923] | 0.477 |
+| (0.4, 70) | 0.0730699 | 0.41593 | 0.489 | [0.089 0.511 0. 0.4 ] | 0.0616618 | 0.548559 | 0.610221 | [0.089 0.911] | 0.489 |
+| (0.4, 71) | 0.124959 | 0.375041 | 0.5 | [0.1 0.5 0. 0.4] | 0.0857221 | 0.529663 | 0.615385 | [0.1 0.9] | 0.5 |
+| (0.4, 72) | 0.113747 | 0.376253 | 0.49 | [0.091 0.509 0.001 0.399] | 0.0965721 | 0.51352 | 0.610092 | [0.092 0.908] | 0.49 |
+| (0.4, 73) | 0.133 | 0.358 | 0.491 | [0.092 0.508 0.001 0.399] | 0.0919066 | 0.518652 | 0.610559 | [0.093 0.907] | 0.491 |
+| (0.4, 74) | 0.105271 | 0.386729 | 0.492 | [0.092 0.508 0. 0.4 ] | 0.0828093 | 0.528812 | 0.611621 | [0.092 0.908] | 0.492 |
+| (0.4, 75) | 0.134828 | 0.358172 | 0.493 | [0.093 0.507 0. 0.4 ] | 0.110178 | 0.50191 | 0.612089 | [0.093 0.907] | 0.493 |
+| (0.4, 76) | 0.12011 | 0.37189 | 0.492 | [0.092 0.508 0. 0.4 ] | 0.091034 | 0.520587 | 0.611621 | [0.092 0.908] | 0.492 |
+| (0.4, 77) | 0.118663 | 0.359337 | 0.478 | [0.078 0.522 0. 0.4 ] | 0.0957442 | 0.5094 | 0.605144 | [0.078 0.922] | 0.478 |
+| (0.4, 78) | 0.0944783 | 0.405522 | 0.5 | [0.1 0.5 0. 0.4] | 0.0700838 | 0.545301 | 0.615385 | [0.1 0.9] | 0.5 |
+| (0.4, 79) | 0.116782 | 0.380218 | 0.497 | [0.097 0.503 0. 0.4 ] | 0.0970365 | 0.516931 | 0.613968 | [0.097 0.903] | 0.497 |
+| (0.4, 80) | 0.107796 | 0.369204 | 0.477 | [0.079 0.521 0.002 0.398] | 0.0821726 | 0.521315 | 0.603487 | [0.081 0.919] | 0.477 |
+| (0.4, 81) | 0.105714 | 0.380286 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0767872 | 0.532041 | 0.608828 | [0.086 0.914] | 0.486 |
+| (0.4, 82) | 0.114563 | 0.391437 | 0.506 | [0.106 0.494 0. 0.4 ] | 0.0992908 | 0.518947 | 0.618238 | [0.106 0.894] | 0.506 |
+| (0.4, 83) | 0.112762 | 0.366238 | 0.479 | [0.079 0.521 0. 0.4 ] | 0.0831437 | 0.522458 | 0.605602 | [0.079 0.921] | 0.479 |
+| (0.4, 84) | 0.118112 | 0.361888 | 0.48 | [0.081 0.519 0.001 0.399] | 0.0910492 | 0.514414 | 0.605463 | [0.082 0.918] | 0.48 |
+| (0.4, 85) | 0.109261 | 0.369739 | 0.479 | [0.079 0.521 0. 0.4 ] | 0.0871998 | 0.518402 | 0.605602 | [0.079 0.921] | 0.479 |
+| (0.4, 86) | 0.0915574 | 0.404443 | 0.496 | [0.096 0.504 0. 0.4 ] | 0.0691098 | 0.544387 | 0.613497 | [0.096 0.904] | 0.496 |
+| (0.4, 87) | 0.102728 | 0.399272 | 0.502 | [0.102 0.498 0. 0.4 ] | 0.0756223 | 0.540711 | 0.616333 | [0.102 0.898] | 0.502 |
+| (0.4, 88) | 0.073757 | 0.414243 | 0.488 | [0.088 0.512 0. 0.4 ] | 0.0647122 | 0.545044 | 0.609756 | [0.088 0.912] | 0.488 |
+| (0.4, 89) | 0.0796764 | 0.404324 | 0.484 | [0.084 0.516 0. 0.4 ] | 0.0650499 | 0.542853 | 0.607903 | [0.084 0.916] | 0.484 |
+| (0.4, 90) | 0.109032 | 0.383968 | 0.493 | [0.093 0.507 0. 0.4 ] | 0.0869838 | 0.525105 | 0.612089 | [0.093 0.907] | 0.493 |
+| (0.4, 91) | 0.0873812 | 0.403619 | 0.491 | [0.093 0.507 0.002 0.398] | 0.0752138 | 0.534748 | 0.609962 | [0.095 0.905] | 0.491 |
+| (0.4, 92) | 0.133381 | 0.342619 | 0.476 | [0.077 0.523 0.001 0.399] | 0.116146 | 0.487485 | 0.603631 | [0.078 0.922] | 0.476 |
+| (0.4, 93) | 0.0782402 | 0.39776 | 0.476 | [0.077 0.523 0.001 0.399] | 0.0717926 | 0.531838 | 0.603631 | [0.078 0.922] | 0.476 |
+| (0.4, 94) | 0.0698796 | 0.43712 | 0.507 | [0.107 0.493 0. 0.4 ] | 0.056667 | 0.562049 | 0.618716 | [0.107 0.893] | 0.507 |
+| (0.4, 95) | 0.0862284 | 0.399772 | 0.486 | [0.086 0.514 0. 0.4 ] | 0.0655856 | 0.543242 | 0.608828 | [0.086 0.914] | 0.486 |
+| (0.4, 96) | 0.082924 | 0.402076 | 0.485 | [0.086 0.514 0.001 0.399] | 0.0622894 | 0.545479 | 0.607768 | [0.087 0.913] | 0.485 |
+| (0.4, 97) | 0.106119 | 0.388881 | 0.495 | [0.095 0.505 0. 0.4 ] | 0.0793528 | 0.533674 | 0.613027 | [0.095 0.905] | 0.495 |
+| (0.4, 98) | 0.0803093 | 0.415691 | 0.496 | [0.097 0.503 0.001 0.399] | 0.0649711 | 0.547932 | 0.612903 | [0.098 0.902] | 0.496 |
+| (0.4, 99) | 0.130854 | 0.357146 | 0.488 | [0.088 0.512 0. 0.4 ] | 0.0929463 | 0.51681 | 0.609756 | [0.088 0.912] | 0.488 |
+| (0.45, 0) | 0.144135 | 0.390865 | 0.535 | [0.085 0.465 0. 0.45 ] | 0.0978465 | 0.561494 | 0.659341 | [0.085 0.915] | 0.535 |
+| (0.45, 1) | 0.0803529 | 0.446647 | 0.527 | [0.078 0.472 0.001 0.449] | 0.0665225 | 0.588474 | 0.654996 | [0.079 0.921] | 0.527 |
+| (0.45, 2) | 0.102685 | 0.434315 | 0.537 | [0.087 0.463 0. 0.45 ] | 0.0754333 | 0.584875 | 0.660308 | [0.087 0.913] | 0.537 |
+| (0.45, 3) | 0.0687572 | 0.470243 | 0.539 | [0.089 0.461 0. 0.45 ] | 0.0624005 | 0.598878 | 0.661278 | [0.089 0.911] | 0.539 |
+| (0.45, 4) | 0.125853 | 0.388147 | 0.514 | [0.064 0.486 0. 0.45 ] | 0.0917095 | 0.557641 | 0.649351 | [0.064 0.936] | 0.514 |
+| (0.45, 5) | 0.0746958 | 0.451304 | 0.526 | [0.076 0.474 0. 0.45 ] | 0.0637687 | 0.591253 | 0.655022 | [0.076 0.924] | 0.526 |
+| (0.45, 6) | 0.110722 | 0.424278 | 0.535 | [0.085 0.465 0. 0.45 ] | 0.0802848 | 0.579056 | 0.659341 | [0.085 0.915] | 0.535 |
+| (0.45, 7) | 0.0962457 | 0.436754 | 0.533 | [0.084 0.466 0.001 0.449] | 0.0746481 | 0.583227 | 0.657875 | [0.085 0.915] | 0.533 |
+| (0.45, 8) | 0.0899108 | 0.463089 | 0.553 | [0.103 0.447 0. 0.45 ] | 0.0678808 | 0.600271 | 0.668151 | [0.103 0.897] | 0.553 |
+| (0.45, 9) | 0.0804035 | 0.443597 | 0.524 | [0.074 0.476 0. 0.45 ] | 0.0667882 | 0.587282 | 0.65407 | [0.074 0.926] | 0.524 |
+| (0.45, 10) | 0.0723278 | 0.458672 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.056579 | 0.600835 | 0.657414 | [0.081 0.919] | 0.531 |
+| (0.45, 11) | 0.130674 | 0.398326 | 0.529 | [0.079 0.471 0. 0.45 ] | 0.0896737 | 0.566781 | 0.656455 | [0.079 0.921] | 0.529 |
+| (0.45, 12) | 0.0678408 | 0.468159 | 0.536 | [0.088 0.462 0.002 0.448] | 0.0504177 | 0.608406 | 0.658824 | [0.09 0.91] | 0.536 |
+| (0.45, 13) | 0.102707 | 0.424293 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0840882 | 0.571411 | 0.655499 | [0.077 0.923] | 0.527 |
+| (0.45, 14) | 0.123353 | 0.414647 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0904657 | 0.570327 | 0.660793 | [0.088 0.912] | 0.538 |
+| (0.45, 15) | 0.117961 | 0.416039 | 0.534 | [0.084 0.466 0. 0.45 ] | 0.0893819 | 0.569476 | 0.658858 | [0.084 0.916] | 0.534 |
+| (0.45, 16) | 0.0889066 | 0.440093 | 0.529 | [0.079 0.471 0. 0.45 ] | 0.06649 | 0.589965 | 0.656455 | [0.079 0.921] | 0.529 |
+| (0.45, 17) | 0.093381 | 0.428619 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0608659 | 0.592255 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 18) | 0.0845936 | 0.448406 | 0.533 | [0.083 0.467 0. 0.45 ] | 0.0663776 | 0.591998 | 0.658376 | [0.083 0.917] | 0.533 |
+| (0.45, 19) | 0.0937979 | 0.442202 | 0.536 | [0.086 0.464 0. 0.45 ] | 0.0702677 | 0.589556 | 0.659824 | [0.086 0.914] | 0.536 |
+| (0.45, 20) | 0.0977833 | 0.443217 | 0.541 | [0.091 0.459 0. 0.45 ] | 0.0747889 | 0.587463 | 0.662252 | [0.091 0.909] | 0.541 |
+| (0.45, 21) | 0.109247 | 0.412753 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0880567 | 0.565064 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 22) | 0.0977246 | 0.433275 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0722733 | 0.585141 | 0.657414 | [0.081 0.919] | 0.531 |
+| (0.45, 23) | 0.0845927 | 0.444407 | 0.529 | [0.08 0.47 0.001 0.449] | 0.063226 | 0.592727 | 0.655953 | [0.081 0.919] | 0.529 |
+| (0.45, 24) | 0.0863168 | 0.444683 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0612519 | 0.596162 | 0.657414 | [0.081 0.919] | 0.531 |
+| (0.45, 25) | 0.0951726 | 0.430827 | 0.526 | [0.076 0.474 0. 0.45 ] | 0.0676557 | 0.587366 | 0.655022 | [0.076 0.924] | 0.526 |
+| (0.45, 26) | 0.11682 | 0.41518 | 0.532 | [0.083 0.467 0.001 0.449] | 0.0886786 | 0.568715 | 0.657394 | [0.084 0.916] | 0.532 |
+| (0.45, 27) | 0.0810696 | 0.46393 | 0.545 | [0.095 0.455 0. 0.45 ] | 0.0680873 | 0.596119 | 0.664207 | [0.095 0.905] | 0.545 |
+| (0.45, 28) | 0.0983129 | 0.434687 | 0.533 | [0.084 0.466 0.001 0.449] | 0.0680319 | 0.589844 | 0.657875 | [0.085 0.915] | 0.533 |
+| (0.45, 29) | 0.113898 | 0.434102 | 0.548 | [0.098 0.452 0. 0.45 ] | 0.099043 | 0.566637 | 0.66568 | [0.098 0.902] | 0.548 |
+| (0.45, 30) | 0.107967 | 0.436033 | 0.544 | [0.094 0.456 0. 0.45 ] | 0.0797048 | 0.584012 | 0.663717 | [0.094 0.906] | 0.544 |
+| (0.45, 31) | 0.0910724 | 0.435928 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0792247 | 0.576274 | 0.655499 | [0.077 0.923] | 0.527 |
+| (0.45, 32) | 0.0998013 | 0.437199 | 0.537 | [0.088 0.462 0.001 0.449] | 0.0709575 | 0.588851 | 0.659809 | [0.089 0.911] | 0.537 |
+| (0.45, 33) | 0.128649 | 0.395351 | 0.524 | [0.075 0.475 0.001 0.449] | 0.0880365 | 0.56553 | 0.653566 | [0.076 0.924] | 0.524 |
+| (0.45, 34) | 0.11969 | 0.42331 | 0.543 | [0.093 0.457 0. 0.45 ] | 0.0735173 | 0.58971 | 0.663228 | [0.093 0.907] | 0.543 |
+| (0.45, 35) | 0.10032 | 0.43168 | 0.532 | [0.084 0.466 0.002 0.448] | 0.0863961 | 0.570495 | 0.656891 | [0.086 0.914] | 0.532 |
+| (0.45, 36) | 0.0874866 | 0.436513 | 0.524 | [0.074 0.476 0. 0.45 ] | 0.0645323 | 0.589537 | 0.65407 | [0.074 0.926] | 0.524 |
+| (0.45, 37) | 0.0794778 | 0.447522 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0575178 | 0.597981 | 0.655499 | [0.077 0.923] | 0.527 |
+| (0.45, 38) | 0.0371157 | 0.498884 | 0.536 | [0.086 0.464 0. 0.45 ] | 0.0320388 | 0.627785 | 0.659824 | [0.086 0.914] | 0.536 |
+| (0.45, 39) | 0.0757443 | 0.446256 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0608502 | 0.59227 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 40) | 0.125924 | 0.399076 | 0.525 | [0.077 0.473 0.002 0.448] | 0.0963192 | 0.557218 | 0.653538 | [0.079 0.921] | 0.525 |
+| (0.45, 41) | 0.0878115 | 0.450189 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0617661 | 0.599027 | 0.660793 | [0.088 0.912] | 0.538 |
+| (0.45, 42) | 0.0975696 | 0.44243 | 0.54 | [0.091 0.459 0.001 0.449] | 0.0706756 | 0.590591 | 0.661267 | [0.092 0.908] | 0.54 |
+| (0.45, 43) | 0.0907168 | 0.447283 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0714498 | 0.589343 | 0.660793 | [0.088 0.912] | 0.538 |
+| (0.45, 44) | 0.069606 | 0.452394 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0567298 | 0.596391 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 45) | 0.0775188 | 0.460481 | 0.538 | [0.088 0.462 0. 0.45 ] | 0.0631226 | 0.59767 | 0.660793 | [0.088 0.912] | 0.538 |
+| (0.45, 46) | 0.107153 | 0.428847 | 0.536 | [0.087 0.463 0.001 0.449] | 0.0851788 | 0.574146 | 0.659325 | [0.088 0.912] | 0.536 |
+| (0.45, 47) | 0.110526 | 0.409474 | 0.52 | [0.07 0.48 0. 0.45] | 0.0791248 | 0.573049 | 0.652174 | [0.07 0.93] | 0.52 |
+| (0.45, 48) | 0.105262 | 0.422738 | 0.528 | [0.078 0.472 0. 0.45 ] | 0.0851603 | 0.570816 | 0.655977 | [0.078 0.922] | 0.528 |
+| (0.45, 49) | 0.0977202 | 0.44528 | 0.543 | [0.093 0.457 0. 0.45 ] | 0.0667705 | 0.596457 | 0.663228 | [0.093 0.907] | 0.543 |
+| (0.45, 50) | 0.110384 | 0.406616 | 0.517 | [0.067 0.483 0. 0.45 ] | 0.0739936 | 0.576766 | 0.650759 | [0.067 0.933] | 0.517 |
+| (0.45, 51) | 0.10361 | 0.42639 | 0.53 | [0.08 0.47 0. 0.45] | 0.0716481 | 0.585286 | 0.656934 | [0.08 0.92] | 0.53 |
+| (0.45, 52) | 0.0978246 | 0.433175 | 0.531 | [0.082 0.468 0.001 0.449] | 0.0701777 | 0.586735 | 0.656913 | [0.083 0.917] | 0.531 |
+| (0.45, 53) | 0.0900391 | 0.431961 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0735003 | 0.57962 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 54) | 0.0896197 | 0.44938 | 0.539 | [0.09 0.46 0.001 0.449] | 0.0574227 | 0.603357 | 0.66078 | [0.091 0.909] | 0.539 |
+| (0.45, 55) | 0.0844244 | 0.429576 | 0.514 | [0.064 0.486 0. 0.45 ] | 0.0684914 | 0.580859 | 0.649351 | [0.064 0.936] | 0.514 |
+| (0.45, 56) | 0.0762635 | 0.447736 | 0.524 | [0.074 0.476 0. 0.45 ] | 0.0546346 | 0.599435 | 0.65407 | [0.074 0.926] | 0.524 |
+| (0.45, 57) | 0.0873352 | 0.442665 | 0.53 | [0.08 0.47 0. 0.45] | 0.0714978 | 0.585436 | 0.656934 | [0.08 0.92] | 0.53 |
+| (0.45, 58) | 0.0981975 | 0.432803 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0694249 | 0.587989 | 0.657414 | [0.081 0.919] | 0.531 |
+| (0.45, 59) | 0.0862462 | 0.438754 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0721937 | 0.582352 | 0.654545 | [0.075 0.925] | 0.525 |
+| (0.45, 60) | 0.0910102 | 0.42499 | 0.516 | [0.066 0.484 0. 0.45 ] | 0.0711453 | 0.579144 | 0.650289 | [0.066 0.934] | 0.516 |
+| (0.45, 61) | 0.108033 | 0.420967 | 0.529 | [0.079 0.471 0. 0.45 ] | 0.0712548 | 0.5852 | 0.656455 | [0.079 0.921] | 0.529 |
+| (0.45, 62) | 0.0915517 | 0.437448 | 0.529 | [0.08 0.47 0.001 0.449] | 0.0657728 | 0.59018 | 0.655953 | [0.081 0.919] | 0.529 |
+| (0.45, 63) | 0.10221 | 0.42779 | 0.53 | [0.08 0.47 0. 0.45] | 0.071132 | 0.585802 | 0.656934 | [0.08 0.92] | 0.53 |
+| (0.45, 64) | 0.0737738 | 0.451226 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0595941 | 0.594951 | 0.654545 | [0.075 0.925] | 0.525 |
+| (0.45, 65) | 0.108378 | 0.413622 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0710203 | 0.5821 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 66) | 0.0985459 | 0.432454 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0684595 | 0.588955 | 0.657414 | [0.081 0.919] | 0.531 |
+| (0.45, 67) | 0.0782579 | 0.460742 | 0.539 | [0.09 0.46 0.001 0.449] | 0.0622707 | 0.598509 | 0.66078 | [0.091 0.909] | 0.539 |
+| (0.45, 68) | 0.0895337 | 0.436466 | 0.526 | [0.077 0.473 0.001 0.449] | 0.0572073 | 0.597312 | 0.654519 | [0.078 0.922] | 0.526 |
+| (0.45, 69) | 0.116034 | 0.410966 | 0.527 | [0.077 0.473 0. 0.45 ] | 0.0800237 | 0.575475 | 0.655499 | [0.077 0.923] | 0.527 |
+| (0.45, 70) | 0.0733139 | 0.451686 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0563668 | 0.598179 | 0.654545 | [0.075 0.925] | 0.525 |
+| (0.45, 71) | 0.0764108 | 0.454589 | 0.531 | [0.081 0.469 0. 0.45 ] | 0.0568153 | 0.600599 | 0.657414 | [0.081 0.919] | 0.531 |
+| (0.45, 72) | 0.101457 | 0.421543 | 0.523 | [0.074 0.476 0.001 0.449] | 0.0660446 | 0.587046 | 0.653091 | [0.075 0.925] | 0.523 |
+| (0.45, 73) | 0.074457 | 0.445543 | 0.52 | [0.07 0.48 0. 0.45] | 0.0427993 | 0.609375 | 0.652174 | [0.07 0.93] | 0.52 |
+| (0.45, 74) | 0.114778 | 0.416222 | 0.531 | [0.082 0.468 0.001 0.449] | 0.0877855 | 0.569127 | 0.656913 | [0.083 0.917] | 0.531 |
+| (0.45, 75) | 0.0871245 | 0.453876 | 0.541 | [0.091 0.459 0. 0.45 ] | 0.0578167 | 0.604435 | 0.662252 | [0.091 0.909] | 0.541 |
+| (0.45, 76) | 0.0804687 | 0.448531 | 0.529 | [0.08 0.47 0.001 0.449] | 0.0565621 | 0.599391 | 0.655953 | [0.081 0.919] | 0.529 |
+| (0.45, 77) | 0.0759259 | 0.472074 | 0.548 | [0.098 0.452 0. 0.45 ] | 0.0714512 | 0.594229 | 0.66568 | [0.098 0.902] | 0.548 |
+| (0.45, 78) | 0.0901168 | 0.436883 | 0.527 | [0.078 0.472 0.001 0.449] | 0.0652689 | 0.589727 | 0.654996 | [0.079 0.921] | 0.527 |
+| (0.45, 79) | 0.117665 | 0.398335 | 0.516 | [0.066 0.484 0. 0.45 ] | 0.0850179 | 0.565271 | 0.650289 | [0.066 0.934] | 0.516 |
+| (0.45, 80) | 0.0838263 | 0.450174 | 0.534 | [0.086 0.464 0.002 0.448] | 0.0586789 | 0.599177 | 0.657856 | [0.088 0.912] | 0.534 |
+| (0.45, 81) | 0.117966 | 0.407034 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0916233 | 0.562922 | 0.654545 | [0.075 0.925] | 0.525 |
+| (0.45, 82) | 0.0783591 | 0.465641 | 0.544 | [0.094 0.456 0. 0.45 ] | 0.0563563 | 0.607361 | 0.663717 | [0.094 0.906] | 0.544 |
+| (0.45, 83) | 0.107869 | 0.426131 | 0.534 | [0.084 0.466 0. 0.45 ] | 0.079874 | 0.578984 | 0.658858 | [0.084 0.916] | 0.534 |
+| (0.45, 84) | 0.0742541 | 0.457746 | 0.532 | [0.083 0.467 0.001 0.449] | 0.0582135 | 0.59918 | 0.657394 | [0.084 0.916] | 0.532 |
+| (0.45, 85) | 0.0889582 | 0.436042 | 0.525 | [0.075 0.475 0. 0.45 ] | 0.0641647 | 0.590381 | 0.654545 | [0.075 0.925] | 0.525 |
+| (0.45, 86) | 0.105018 | 0.429982 | 0.535 | [0.086 0.464 0.001 0.449] | 0.075934 | 0.582907 | 0.658841 | [0.087 0.913] | 0.535 |
+| (0.45, 87) | 0.0880208 | 0.437979 | 0.526 | [0.077 0.473 0.001 0.449] | 0.0573692 | 0.59715 | 0.654519 | [0.078 0.922] | 0.526 |
+| (0.45, 88) | 0.0817681 | 0.456232 | 0.538 | [0.09 0.46 0.002 0.448] | 0.056134 | 0.60366 | 0.659794 | [0.092 0.908] | 0.538 |
+| (0.45, 89) | 0.113433 | 0.420567 | 0.534 | [0.085 0.465 0.001 0.449] | 0.085868 | 0.57249 | 0.658358 | [0.086 0.914] | 0.534 |
+| (0.45, 90) | 0.0828514 | 0.446149 | 0.529 | [0.081 0.469 0.002 0.448] | 0.0623557 | 0.593094 | 0.65545 | [0.083 0.917] | 0.529 |
+| (0.45, 91) | 0.0816244 | 0.451376 | 0.533 | [0.083 0.467 0. 0.45 ] | 0.0671052 | 0.591271 | 0.658376 | [0.083 0.917] | 0.533 |
+| (0.45, 92) | 0.0661671 | 0.459833 | 0.526 | [0.076 0.474 0. 0.45 ] | 0.0487002 | 0.606322 | 0.655022 | [0.076 0.924] | 0.526 |
+| (0.45, 93) | 0.111753 | 0.412247 | 0.524 | [0.075 0.475 0.001 0.449] | 0.0867837 | 0.566783 | 0.653566 | [0.076 0.924] | 0.524 |
+| (0.45, 94) | 0.120017 | 0.414983 | 0.535 | [0.085 0.465 0. 0.45 ] | 0.0876596 | 0.571681 | 0.659341 | [0.085 0.915] | 0.535 |
+| (0.45, 95) | 0.121518 | 0.412482 | 0.534 | [0.084 0.466 0. 0.45 ] | 0.0959745 | 0.562883 | 0.658858 | [0.084 0.916] | 0.534 |
+| (0.45, 96) | 0.0951344 | 0.426866 | 0.522 | [0.072 0.478 0. 0.45 ] | 0.0639835 | 0.589137 | 0.65312 | [0.072 0.928] | 0.522 |
+| (0.45, 97) | 0.0712756 | 0.461724 | 0.533 | [0.083 0.467 0. 0.45 ] | 0.0543197 | 0.604056 | 0.658376 | [0.083 0.917] | 0.533 |
+| (0.45, 98) | 0.0954362 | 0.448564 | 0.544 | [0.094 0.456 0. 0.45 ] | 0.0673074 | 0.596409 | 0.663717 | [0.094 0.906] | 0.544 |
+| (0.45, 99) | 0.103458 | 0.428542 | 0.532 | [0.082 0.468 0. 0.45 ] | 0.0707815 | 0.587113 | 0.657895 | [0.082 0.918] | 0.532 |
+| (0.5, 0) | 0.0823199 | 0.48668 | 0.569 | [0.071 0.429 0.002 0.498] | 0.0658081 | 0.63216 | 0.697968 | [0.073 0.927] | 0.569 |
+| (0.5, 1) | 0.0714074 | 0.492593 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0533071 | 0.643072 | 0.696379 | [0.064 0.936] | 0.564 |
+| (0.5, 2) | 0.0913782 | 0.477622 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0608316 | 0.63798 | 0.698812 | [0.069 0.931] | 0.569 |
+| (0.5, 3) | 0.0980838 | 0.467916 | 0.566 | [0.066 0.434 0. 0.5 ] | 0.0728228 | 0.624527 | 0.69735 | [0.066 0.934] | 0.566 |
+| (0.5, 4) | 0.0713764 | 0.485624 | 0.557 | [0.06 0.44 0.003 0.497] | 0.0545128 | 0.637206 | 0.691719 | [0.063 0.937] | 0.557 |
+| (0.5, 5) | 0.109045 | 0.462955 | 0.572 | [0.073 0.427 0.001 0.499] | 0.069359 | 0.630501 | 0.69986 | [0.074 0.926] | 0.572 |
+| (0.5, 6) | 0.0859611 | 0.500039 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0553646 | 0.651849 | 0.707214 | [0.086 0.914] | 0.586 |
+| (0.5, 7) | 0.0853441 | 0.483656 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0633528 | 0.635459 | 0.698812 | [0.069 0.931] | 0.569 |
+| (0.5, 8) | 0.132703 | 0.442297 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.0890792 | 0.612675 | 0.701754 | [0.075 0.925] | 0.575 |
+| (0.5, 9) | 0.0901357 | 0.484864 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.061493 | 0.640261 | 0.701754 | [0.075 0.925] | 0.575 |
+| (0.5, 10) | 0.0896721 | 0.492328 | 0.582 | [0.083 0.417 0.001 0.499] | 0.05777 | 0.647032 | 0.704802 | [0.084 0.916] | 0.582 |
+| (0.5, 11) | 0.104675 | 0.472325 | 0.577 | [0.078 0.422 0.001 0.499] | 0.0722944 | 0.630028 | 0.702322 | [0.079 0.921] | 0.577 |
+| (0.5, 12) | 0.106432 | 0.467568 | 0.574 | [0.074 0.426 0. 0.5 ] | 0.0760253 | 0.625237 | 0.701262 | [0.074 0.926] | 0.574 |
+| (0.5, 13) | 0.0447724 | 0.536228 | 0.581 | [0.082 0.418 0.001 0.499] | 0.0338064 | 0.670499 | 0.704305 | [0.083 0.917] | 0.581 |
+| (0.5, 14) | 0.08127 | 0.49473 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0546865 | 0.647561 | 0.702247 | [0.076 0.924] | 0.576 |
+| (0.5, 15) | 0.0927274 | 0.466273 | 0.559 | [0.059 0.441 0. 0.5 ] | 0.0689874 | 0.624975 | 0.693963 | [0.059 0.941] | 0.559 |
+| (0.5, 16) | 0.0895199 | 0.49148 | 0.581 | [0.082 0.418 0.001 0.499] | 0.0676034 | 0.636701 | 0.704305 | [0.083 0.917] | 0.581 |
+| (0.5, 17) | 0.101514 | 0.471486 | 0.573 | [0.073 0.427 0. 0.5 ] | 0.0786432 | 0.622128 | 0.700771 | [0.073 0.927] | 0.573 |
+| (0.5, 18) | 0.0802439 | 0.488756 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0639173 | 0.634895 | 0.698812 | [0.069 0.931] | 0.569 |
+| (0.5, 19) | 0.094629 | 0.466371 | 0.561 | [0.061 0.439 0. 0.5 ] | 0.0745545 | 0.620373 | 0.694927 | [0.061 0.939] | 0.561 |
+| (0.5, 20) | 0.0639745 | 0.506026 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.0458685 | 0.653432 | 0.699301 | [0.07 0.93] | 0.57 |
+| (0.5, 21) | 0.0647483 | 0.507252 | 0.572 | [0.073 0.427 0.001 0.499] | 0.0419894 | 0.65787 | 0.69986 | [0.074 0.926] | 0.572 |
+| (0.5, 22) | 0.0906012 | 0.469399 | 0.56 | [0.06 0.44 0. 0.5 ] | 0.0719325 | 0.622512 | 0.694444 | [0.06 0.94] | 0.56 |
+| (0.5, 23) | 0.0792254 | 0.484775 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0515546 | 0.644824 | 0.696379 | [0.064 0.936] | 0.564 |
+| (0.5, 24) | 0.089042 | 0.475958 | 0.565 | [0.065 0.435 0. 0.5 ] | 0.0625937 | 0.63427 | 0.696864 | [0.065 0.935] | 0.565 |
+| (0.5, 25) | 0.0693021 | 0.508698 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0390147 | 0.66422 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 26) | 0.0826301 | 0.47537 | 0.558 | [0.058 0.442 0. 0.5 ] | 0.0662074 | 0.627274 | 0.693481 | [0.058 0.942] | 0.558 |
+| (0.5, 27) | 0.0865851 | 0.486415 | 0.573 | [0.074 0.426 0.001 0.499] | 0.0592513 | 0.6411 | 0.700351 | [0.075 0.925] | 0.573 |
+| (0.5, 28) | 0.098346 | 0.477654 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0675682 | 0.634679 | 0.702247 | [0.076 0.924] | 0.576 |
+| (0.5, 29) | 0.106672 | 0.465328 | 0.572 | [0.072 0.428 0. 0.5 ] | 0.0687628 | 0.631517 | 0.70028 | [0.072 0.928] | 0.572 |
+| (0.5, 30) | 0.0814945 | 0.491505 | 0.573 | [0.074 0.426 0.001 0.499] | 0.0639574 | 0.636394 | 0.700351 | [0.075 0.925] | 0.573 |
+| (0.5, 31) | 0.089467 | 0.491533 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0609881 | 0.643734 | 0.704722 | [0.081 0.919] | 0.581 |
+| (0.5, 32) | 0.118053 | 0.457947 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0806901 | 0.621557 | 0.702247 | [0.076 0.924] | 0.576 |
+| (0.5, 33) | 0.0825452 | 0.499455 | 0.582 | [0.082 0.418 0. 0.5 ] | 0.0582277 | 0.646991 | 0.705219 | [0.082 0.918] | 0.582 |
+| (0.5, 34) | 0.0417537 | 0.522246 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0305612 | 0.665818 | 0.696379 | [0.064 0.936] | 0.564 |
+| (0.5, 35) | 0.0785123 | 0.502488 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0475305 | 0.657191 | 0.704722 | [0.081 0.919] | 0.581 |
+| (0.5, 36) | 0.0744245 | 0.511576 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0489571 | 0.658257 | 0.707214 | [0.086 0.914] | 0.586 |
+| (0.5, 37) | 0.0843737 | 0.491626 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0653751 | 0.636872 | 0.702247 | [0.076 0.924] | 0.576 |
+| (0.5, 38) | 0.09586 | 0.47114 | 0.567 | [0.069 0.431 0.002 0.498] | 0.0624039 | 0.634587 | 0.696991 | [0.071 0.929] | 0.567 |
+| (0.5, 39) | 0.0986446 | 0.471355 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.0662648 | 0.633036 | 0.699301 | [0.07 0.93] | 0.57 |
+| (0.5, 40) | 0.108438 | 0.460562 | 0.569 | [0.07 0.43 0.001 0.499] | 0.0689099 | 0.629481 | 0.69839 | [0.071 0.929] | 0.569 |
+| (0.5, 41) | 0.0767079 | 0.524292 | 0.601 | [0.101 0.399 0. 0.5 ] | 0.0610743 | 0.653722 | 0.714796 | [0.101 0.899] | 0.601 |
+| (0.5, 42) | 0.0732868 | 0.501713 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.0550139 | 0.64674 | 0.701754 | [0.075 0.925] | 0.575 |
+| (0.5, 43) | 0.0867752 | 0.495225 | 0.582 | [0.082 0.418 0. 0.5 ] | 0.0691998 | 0.636019 | 0.705219 | [0.082 0.918] | 0.582 |
+| (0.5, 44) | 0.0828599 | 0.50414 | 0.587 | [0.089 0.411 0.002 0.498] | 0.0641183 | 0.642766 | 0.706884 | [0.091 0.909] | 0.587 |
+| (0.5, 45) | 0.0958384 | 0.493162 | 0.589 | [0.089 0.411 0. 0.5 ] | 0.067415 | 0.641302 | 0.708717 | [0.089 0.911] | 0.589 |
+| (0.5, 46) | 0.094656 | 0.483344 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0723339 | 0.630901 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 47) | 0.0912958 | 0.476704 | 0.568 | [0.068 0.432 0. 0.5 ] | 0.0622567 | 0.636067 | 0.698324 | [0.068 0.932] | 0.568 |
+| (0.5, 48) | 0.0869253 | 0.491075 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0550731 | 0.648162 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 49) | 0.0468182 | 0.517182 | 0.564 | [0.064 0.436 0. 0.5 ] | 0.0355723 | 0.660806 | 0.696379 | [0.064 0.936] | 0.564 |
+| (0.5, 50) | 0.0751574 | 0.489843 | 0.565 | [0.066 0.434 0.001 0.499] | 0.0543628 | 0.642078 | 0.696441 | [0.067 0.933] | 0.565 |
+| (0.5, 51) | 0.0801626 | 0.511837 | 0.592 | [0.092 0.408 0. 0.5 ] | 0.0670399 | 0.643187 | 0.710227 | [0.092 0.908] | 0.592 |
+| (0.5, 52) | 0.0800749 | 0.499925 | 0.58 | [0.08 0.42 0. 0.5 ] | 0.0537815 | 0.650444 | 0.704225 | [0.08 0.92] | 0.58 |
+| (0.5, 53) | 0.0895674 | 0.487433 | 0.577 | [0.077 0.423 0. 0.5 ] | 0.0634805 | 0.63926 | 0.702741 | [0.077 0.923] | 0.577 |
+| (0.5, 54) | 0.083454 | 0.484546 | 0.568 | [0.068 0.432 0. 0.5 ] | 0.061941 | 0.636383 | 0.698324 | [0.068 0.932] | 0.568 |
+| (0.5, 55) | 0.0657226 | 0.511277 | 0.577 | [0.078 0.422 0.001 0.499] | 0.053739 | 0.648583 | 0.702322 | [0.079 0.921] | 0.577 |
+| (0.5, 56) | 0.0652427 | 0.517757 | 0.583 | [0.083 0.417 0. 0.5 ] | 0.0528151 | 0.652901 | 0.705716 | [0.083 0.917] | 0.583 |
+| (0.5, 57) | 0.08749 | 0.49551 | 0.583 | [0.084 0.416 0.001 0.499] | 0.0566554 | 0.648645 | 0.7053 | [0.085 0.915] | 0.583 |
+| (0.5, 58) | 0.0876101 | 0.47539 | 0.563 | [0.063 0.437 0. 0.5 ] | 0.0661026 | 0.629792 | 0.695894 | [0.063 0.937] | 0.563 |
+| (0.5, 59) | 0.081788 | 0.504212 | 0.586 | [0.087 0.413 0.001 0.499] | 0.063427 | 0.643372 | 0.706799 | [0.088 0.912] | 0.586 |
+| (0.5, 60) | 0.08172 | 0.48428 | 0.566 | [0.066 0.434 0. 0.5 ] | 0.0662614 | 0.631089 | 0.69735 | [0.066 0.934] | 0.566 |
+| (0.5, 61) | 0.108461 | 0.451539 | 0.56 | [0.061 0.439 0.001 0.499] | 0.0744602 | 0.619559 | 0.694019 | [0.062 0.938] | 0.56 |
+| (0.5, 62) | 0.0928987 | 0.476101 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0653223 | 0.63349 | 0.698812 | [0.069 0.931] | 0.569 |
+| (0.5, 63) | 0.0916214 | 0.487379 | 0.579 | [0.079 0.421 0. 0.5 ] | 0.0658141 | 0.637916 | 0.70373 | [0.079 0.921] | 0.579 |
+| (0.5, 64) | 0.0774471 | 0.500553 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0503743 | 0.652861 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 65) | 0.0649944 | 0.505006 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.0464662 | 0.652835 | 0.699301 | [0.07 0.93] | 0.57 |
+| (0.5, 66) | 0.112129 | 0.459871 | 0.572 | [0.072 0.428 0. 0.5 ] | 0.0782461 | 0.622034 | 0.70028 | [0.072 0.928] | 0.572 |
+| (0.5, 67) | 0.0465229 | 0.539477 | 0.586 | [0.087 0.413 0.001 0.499] | 0.0326439 | 0.674155 | 0.706799 | [0.088 0.912] | 0.586 |
+| (0.5, 68) | 0.0947336 | 0.477266 | 0.572 | [0.072 0.428 0. 0.5 ] | 0.0738824 | 0.626398 | 0.70028 | [0.072 0.928] | 0.572 |
+| (0.5, 69) | 0.0904762 | 0.471524 | 0.562 | [0.062 0.438 0. 0.5 ] | 0.0632376 | 0.632173 | 0.69541 | [0.062 0.938] | 0.562 |
+| (0.5, 70) | 0.0690796 | 0.51192 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0519332 | 0.652788 | 0.704722 | [0.081 0.919] | 0.581 |
+| (0.5, 71) | 0.0983992 | 0.465601 | 0.564 | [0.065 0.435 0.001 0.499] | 0.0771774 | 0.618778 | 0.695955 | [0.066 0.934] | 0.564 |
+| (0.5, 72) | 0.0972073 | 0.477793 | 0.575 | [0.075 0.425 0. 0.5 ] | 0.0747774 | 0.626977 | 0.701754 | [0.075 0.925] | 0.575 |
+| (0.5, 73) | 0.0639479 | 0.518052 | 0.582 | [0.083 0.417 0.001 0.499] | 0.0473908 | 0.657411 | 0.704802 | [0.084 0.916] | 0.582 |
+| (0.5, 74) | 0.0487624 | 0.529238 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0355232 | 0.667712 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 75) | 0.0990139 | 0.468986 | 0.568 | [0.069 0.431 0.001 0.499] | 0.0652727 | 0.632629 | 0.697902 | [0.07 0.93] | 0.568 |
+| (0.5, 76) | 0.0674569 | 0.510543 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0482796 | 0.654955 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 77) | 0.104605 | 0.473395 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0767052 | 0.62653 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 78) | 0.101666 | 0.483334 | 0.585 | [0.085 0.415 0. 0.5 ] | 0.0646452 | 0.642069 | 0.706714 | [0.085 0.915] | 0.585 |
+| (0.5, 79) | 0.0801886 | 0.480811 | 0.561 | [0.061 0.439 0. 0.5 ] | 0.0615175 | 0.63341 | 0.694927 | [0.061 0.939] | 0.561 |
+| (0.5, 80) | 0.0946084 | 0.482392 | 0.577 | [0.077 0.423 0. 0.5 ] | 0.0679813 | 0.634759 | 0.702741 | [0.077 0.923] | 0.577 |
+| (0.5, 81) | 0.106413 | 0.474587 | 0.581 | [0.081 0.419 0. 0.5 ] | 0.0724391 | 0.632283 | 0.704722 | [0.081 0.919] | 0.581 |
+| (0.5, 82) | 0.0781018 | 0.487898 | 0.566 | [0.067 0.433 0.001 0.499] | 0.0478596 | 0.649068 | 0.696927 | [0.068 0.932] | 0.566 |
+| (0.5, 83) | 0.0936024 | 0.473398 | 0.567 | [0.067 0.433 0. 0.5 ] | 0.0720418 | 0.625795 | 0.697837 | [0.067 0.933] | 0.567 |
+| (0.5, 84) | 0.111706 | 0.459294 | 0.571 | [0.071 0.429 0. 0.5 ] | 0.0712875 | 0.628503 | 0.69979 | [0.071 0.929] | 0.571 |
+| (0.5, 85) | 0.0536686 | 0.513331 | 0.567 | [0.067 0.433 0. 0.5 ] | 0.039865 | 0.657972 | 0.697837 | [0.067 0.933] | 0.567 |
+| (0.5, 86) | 0.0633176 | 0.509682 | 0.573 | [0.073 0.427 0. 0.5 ] | 0.0460594 | 0.654711 | 0.700771 | [0.073 0.927] | 0.573 |
+| (0.5, 87) | 0.0521377 | 0.525862 | 0.578 | [0.078 0.422 0. 0.5 ] | 0.0411703 | 0.662065 | 0.703235 | [0.078 0.922] | 0.578 |
+| (0.5, 88) | 0.0845024 | 0.501498 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0657795 | 0.641434 | 0.707214 | [0.086 0.914] | 0.586 |
+| (0.5, 89) | 0.0716476 | 0.514352 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0514473 | 0.655766 | 0.707214 | [0.086 0.914] | 0.586 |
+| (0.5, 90) | 0.0727238 | 0.512276 | 0.585 | [0.085 0.415 0. 0.5 ] | 0.0502498 | 0.656464 | 0.706714 | [0.085 0.915] | 0.585 |
+| (0.5, 91) | 0.0693259 | 0.507674 | 0.577 | [0.077 0.423 0. 0.5 ] | 0.0515734 | 0.651167 | 0.702741 | [0.077 0.923] | 0.577 |
+| (0.5, 92) | 0.0893712 | 0.486629 | 0.576 | [0.076 0.424 0. 0.5 ] | 0.0645728 | 0.637674 | 0.702247 | [0.076 0.924] | 0.576 |
+| (0.5, 93) | 0.0645983 | 0.509402 | 0.574 | [0.075 0.425 0.001 0.499] | 0.0470981 | 0.653745 | 0.700843 | [0.076 0.924] | 0.574 |
+| (0.5, 94) | 0.0577857 | 0.528214 | 0.586 | [0.086 0.414 0. 0.5 ] | 0.0477799 | 0.659434 | 0.707214 | [0.086 0.914] | 0.586 |
+| (0.5, 95) | 0.0683137 | 0.511686 | 0.58 | [0.08 0.42 0. 0.5 ] | 0.0438813 | 0.660344 | 0.704225 | [0.08 0.92] | 0.58 |
+| (0.5, 96) | 0.0836411 | 0.485359 | 0.569 | [0.069 0.431 0. 0.5 ] | 0.0653466 | 0.633465 | 0.698812 | [0.069 0.931] | 0.569 |
+| (0.5, 97) | 0.0842354 | 0.485765 | 0.57 | [0.07 0.43 0. 0.5 ] | 0.048951 | 0.65035 | 0.699301 | [0.07 0.93] | 0.57 |
+| (0.5, 98) | 0.100673 | 0.472327 | 0.573 | [0.073 0.427 0. 0.5 ] | 0.0649737 | 0.635797 | 0.700771 | [0.073 0.927] | 0.573 |
+| (0.5, 99) | 0.0852149 | 0.486785 | 0.572 | [0.073 0.427 0.001 0.499] | 0.0583452 | 0.641515 | 0.69986 | [0.074 0.926] | 0.572 |
+| (0.55, 0) | 0.0730904 | 0.53891 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0428355 | 0.696412 | 0.739247 | [0.062 0.938] | 0.612 |
+| (0.55, 1) | 0.0661012 | 0.542899 | 0.609 | [0.059 0.391 0. 0.55 ] | 0.0467022 | 0.691058 | 0.73776 | [0.059 0.941] | 0.609 |
+| (0.55, 2) | 0.0644516 | 0.542548 | 0.607 | [0.057 0.393 0. 0.55 ] | 0.046827 | 0.689945 | 0.736772 | [0.057 0.943] | 0.607 |
+| (0.55, 3) | 0.0620741 | 0.547926 | 0.61 | [0.06 0.39 0. 0.55] | 0.0387163 | 0.699539 | 0.738255 | [0.06 0.94] | 0.61 |
+| (0.55, 4) | 0.0833749 | 0.528625 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.05636 | 0.682887 | 0.739247 | [0.062 0.938] | 0.612 |
+| (0.55, 5) | 0.1047 | 0.5133 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0670869 | 0.675153 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 6) | 0.0682258 | 0.538774 | 0.607 | [0.057 0.393 0. 0.55 ] | 0.0365568 | 0.700215 | 0.736772 | [0.057 0.943] | 0.607 |
+| (0.55, 7) | 0.0636036 | 0.566396 | 0.63 | [0.081 0.369 0.001 0.549] | 0.0466895 | 0.701267 | 0.747956 | [0.082 0.918] | 0.63 |
+| (0.55, 8) | 0.0886129 | 0.523387 | 0.612 | [0.063 0.387 0.001 0.549] | 0.058874 | 0.680022 | 0.738896 | [0.064 0.936] | 0.612 |
+| (0.55, 9) | 0.0695911 | 0.535409 | 0.605 | [0.056 0.394 0.001 0.549] | 0.0521205 | 0.683312 | 0.735432 | [0.057 0.943] | 0.605 |
+| (0.55, 10) | 0.0832089 | 0.543791 | 0.627 | [0.077 0.373 0. 0.55 ] | 0.0564085 | 0.690367 | 0.746775 | [0.077 0.923] | 0.627 |
+| (0.55, 11) | 0.0741853 | 0.553815 | 0.628 | [0.079 0.371 0.001 0.549] | 0.0503493 | 0.696589 | 0.746939 | [0.08 0.92] | 0.628 |
+| (0.55, 12) | 0.0767586 | 0.530241 | 0.607 | [0.058 0.392 0.001 0.549] | 0.054906 | 0.681513 | 0.736419 | [0.059 0.941] | 0.607 |
+| (0.55, 13) | 0.108092 | 0.515908 | 0.624 | [0.074 0.376 0. 0.55 ] | 0.0698793 | 0.675378 | 0.745257 | [0.074 0.926] | 0.624 |
+| (0.55, 14) | 0.0878994 | 0.532101 | 0.62 | [0.071 0.379 0.001 0.549] | 0.0573614 | 0.685534 | 0.742896 | [0.072 0.928] | 0.62 |
+| (0.55, 15) | 0.0678694 | 0.559131 | 0.627 | [0.077 0.373 0. 0.55 ] | 0.042195 | 0.70458 | 0.746775 | [0.077 0.923] | 0.627 |
+| (0.55, 16) | 0.0683432 | 0.539657 | 0.608 | [0.058 0.392 0. 0.55 ] | 0.0498925 | 0.687373 | 0.737265 | [0.058 0.942] | 0.608 |
+| (0.55, 17) | 0.0753853 | 0.536615 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0528654 | 0.686382 | 0.739247 | [0.062 0.938] | 0.612 |
+| (0.55, 18) | 0.086495 | 0.527505 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0563929 | 0.683499 | 0.739892 | [0.066 0.934] | 0.614 |
+| (0.55, 19) | 0.0657372 | 0.545263 | 0.611 | [0.061 0.389 0. 0.55 ] | 0.0404072 | 0.698344 | 0.738751 | [0.061 0.939] | 0.611 |
+| (0.55, 20) | 0.108858 | 0.504142 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0840232 | 0.655721 | 0.739744 | [0.063 0.937] | 0.613 |
+| (0.55, 21) | 0.0967053 | 0.505295 | 0.602 | [0.053 0.397 0.001 0.549] | 0.066302 | 0.667655 | 0.733957 | [0.054 0.946] | 0.602 |
+| (0.55, 22) | 0.0630256 | 0.553974 | 0.617 | [0.068 0.382 0.001 0.549] | 0.045882 | 0.695509 | 0.741391 | [0.069 0.931] | 0.617 |
+| (0.55, 23) | 0.0913141 | 0.522686 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0593481 | 0.680894 | 0.740242 | [0.064 0.936] | 0.614 |
+| (0.55, 24) | 0.0817313 | 0.530269 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0508022 | 0.688445 | 0.739247 | [0.062 0.938] | 0.612 |
+| (0.55, 25) | 0.077761 | 0.540239 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0587776 | 0.683463 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 26) | 0.117069 | 0.500931 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0827969 | 0.659443 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 27) | 0.0470736 | 0.581926 | 0.629 | [0.08 0.37 0.001 0.549] | 0.0371326 | 0.710315 | 0.747447 | [0.081 0.919] | 0.629 |
+| (0.55, 28) | 0.0650752 | 0.559925 | 0.625 | [0.076 0.374 0.001 0.549] | 0.0448129 | 0.700605 | 0.745418 | [0.077 0.923] | 0.625 |
+| (0.55, 29) | 0.0881858 | 0.528814 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0568185 | 0.684921 | 0.74174 | [0.067 0.933] | 0.617 |
+| (0.55, 30) | 0.0977565 | 0.528244 | 0.626 | [0.076 0.374 0. 0.55 ] | 0.0690057 | 0.677263 | 0.746269 | [0.076 0.924] | 0.626 |
+| (0.55, 31) | 0.0871869 | 0.523813 | 0.611 | [0.061 0.389 0. 0.55 ] | 0.0582915 | 0.680459 | 0.738751 | [0.061 0.939] | 0.611 |
+| (0.55, 32) | 0.0728003 | 0.5452 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0543715 | 0.687869 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 33) | 0.0809225 | 0.523078 | 0.604 | [0.054 0.396 0. 0.55 ] | 0.0520946 | 0.6832 | 0.735294 | [0.054 0.946] | 0.604 |
+| (0.55, 34) | 0.100559 | 0.526441 | 0.627 | [0.077 0.373 0. 0.55 ] | 0.0630208 | 0.683754 | 0.746775 | [0.077 0.923] | 0.627 |
+| (0.55, 35) | 0.103207 | 0.513793 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0645554 | 0.677184 | 0.74174 | [0.067 0.933] | 0.617 |
+| (0.55, 36) | 0.0817379 | 0.536262 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0547587 | 0.687481 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 37) | 0.075124 | 0.537876 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0481441 | 0.6916 | 0.739744 | [0.063 0.937] | 0.613 |
+| (0.55, 38) | 0.0678917 | 0.557108 | 0.625 | [0.075 0.375 0. 0.55 ] | 0.0452231 | 0.70054 | 0.745763 | [0.075 0.925] | 0.625 |
+| (0.55, 39) | 0.0702522 | 0.550748 | 0.621 | [0.072 0.378 0.001 0.549] | 0.0474194 | 0.695979 | 0.743399 | [0.073 0.927] | 0.621 |
+| (0.55, 40) | 0.0989642 | 0.522036 | 0.621 | [0.071 0.379 0. 0.55 ] | 0.061899 | 0.681847 | 0.743746 | [0.071 0.929] | 0.621 |
+| (0.55, 41) | 0.0844022 | 0.539598 | 0.624 | [0.074 0.376 0. 0.55 ] | 0.0556893 | 0.689568 | 0.745257 | [0.074 0.926] | 0.624 |
+| (0.55, 42) | 0.0793985 | 0.555601 | 0.635 | [0.086 0.364 0.001 0.549] | 0.0532486 | 0.697264 | 0.750513 | [0.087 0.913] | 0.635 |
+| (0.55, 43) | 0.0422454 | 0.564755 | 0.607 | [0.058 0.392 0.001 0.549] | 0.0257601 | 0.710658 | 0.736419 | [0.059 0.941] | 0.607 |
+| (0.55, 44) | 0.0642159 | 0.551784 | 0.616 | [0.066 0.384 0. 0.55 ] | 0.0499338 | 0.691306 | 0.74124 | [0.066 0.934] | 0.616 |
+| (0.55, 45) | 0.0775302 | 0.54147 | 0.619 | [0.069 0.381 0. 0.55 ] | 0.0494472 | 0.693294 | 0.742741 | [0.069 0.931] | 0.619 |
+| (0.55, 46) | 0.0855431 | 0.530457 | 0.616 | [0.066 0.384 0. 0.55 ] | 0.0539876 | 0.687252 | 0.74124 | [0.066 0.934] | 0.616 |
+| (0.55, 47) | 0.0621009 | 0.567899 | 0.63 | [0.081 0.369 0.001 0.549] | 0.0462904 | 0.701666 | 0.747956 | [0.082 0.918] | 0.63 |
+| (0.55, 48) | 0.0883259 | 0.526674 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0598105 | 0.680581 | 0.740391 | [0.067 0.933] | 0.615 |
+| (0.55, 49) | 0.0951236 | 0.512876 | 0.608 | [0.059 0.391 0.001 0.549] | 0.0690868 | 0.667826 | 0.736913 | [0.06 0.94] | 0.608 |
+| (0.55, 50) | 0.0554219 | 0.551578 | 0.607 | [0.057 0.393 0. 0.55 ] | 0.0409083 | 0.695863 | 0.736772 | [0.057 0.943] | 0.607 |
+| (0.55, 51) | 0.0839772 | 0.516023 | 0.6 | [0.053 0.397 0.003 0.547] | 0.0600569 | 0.672206 | 0.732262 | [0.056 0.944] | 0.6 |
+| (0.55, 52) | 0.12439 | 0.48961 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0840354 | 0.656207 | 0.740242 | [0.064 0.936] | 0.614 |
+| (0.55, 53) | 0.0616151 | 0.552385 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0439556 | 0.695937 | 0.739892 | [0.066 0.934] | 0.614 |
+| (0.55, 54) | 0.0917346 | 0.531265 | 0.623 | [0.073 0.377 0. 0.55 ] | 0.0659632 | 0.67879 | 0.744753 | [0.073 0.927] | 0.623 |
+| (0.55, 55) | 0.0825903 | 0.53441 | 0.617 | [0.068 0.382 0.001 0.549] | 0.0581616 | 0.683229 | 0.741391 | [0.069 0.931] | 0.617 |
+| (0.55, 56) | 0.0439757 | 0.564024 | 0.608 | [0.058 0.392 0. 0.55 ] | 0.0307259 | 0.706539 | 0.737265 | [0.058 0.942] | 0.608 |
+| (0.55, 57) | 0.0791233 | 0.533877 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0549126 | 0.684832 | 0.739744 | [0.063 0.937] | 0.613 |
+| (0.55, 58) | 0.0466274 | 0.568373 | 0.615 | [0.065 0.385 0. 0.55 ] | 0.0319929 | 0.708748 | 0.740741 | [0.065 0.935] | 0.615 |
+| (0.55, 59) | 0.0716604 | 0.54134 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0421397 | 0.697605 | 0.739744 | [0.063 0.937] | 0.613 |
+| (0.55, 60) | 0.0891312 | 0.525869 | 0.615 | [0.066 0.384 0.001 0.549] | 0.055412 | 0.684979 | 0.740391 | [0.067 0.933] | 0.615 |
+| (0.55, 61) | 0.050594 | 0.567406 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0318906 | 0.71035 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 62) | 0.0764588 | 0.536541 | 0.613 | [0.064 0.386 0.001 0.549] | 0.0534303 | 0.685964 | 0.739394 | [0.065 0.935] | 0.613 |
+| (0.55, 63) | 0.0825997 | 0.5264 | 0.609 | [0.059 0.391 0. 0.55 ] | 0.0549614 | 0.682798 | 0.73776 | [0.059 0.941] | 0.609 |
+| (0.55, 64) | 0.0790597 | 0.53894 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0599859 | 0.682254 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 65) | 0.102482 | 0.509518 | 0.612 | [0.062 0.388 0. 0.55 ] | 0.0717024 | 0.667545 | 0.739247 | [0.062 0.938] | 0.612 |
+| (0.55, 66) | 0.0946111 | 0.521389 | 0.616 | [0.067 0.383 0.001 0.549] | 0.0639841 | 0.676907 | 0.740891 | [0.068 0.932] | 0.616 |
+| (0.55, 67) | 0.0656431 | 0.551357 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0496327 | 0.692107 | 0.74174 | [0.067 0.933] | 0.617 |
+| (0.55, 68) | 0.069672 | 0.551328 | 0.621 | [0.071 0.379 0. 0.55 ] | 0.0451221 | 0.698624 | 0.743746 | [0.071 0.929] | 0.621 |
+| (0.55, 69) | 0.0642955 | 0.555705 | 0.62 | [0.07 0.38 0. 0.55] | 0.0396424 | 0.703601 | 0.743243 | [0.07 0.93] | 0.62 |
+| (0.55, 70) | 0.0843746 | 0.530625 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0508608 | 0.68953 | 0.740391 | [0.067 0.933] | 0.615 |
+| (0.55, 71) | 0.0788593 | 0.531141 | 0.61 | [0.06 0.39 0. 0.55] | 0.0476278 | 0.690627 | 0.738255 | [0.06 0.94] | 0.61 |
+| (0.55, 72) | 0.0766319 | 0.540368 | 0.617 | [0.067 0.383 0. 0.55 ] | 0.0548507 | 0.686889 | 0.74174 | [0.067 0.933] | 0.617 |
+| (0.55, 73) | 0.0480531 | 0.566947 | 0.615 | [0.065 0.385 0. 0.55 ] | 0.0363437 | 0.704397 | 0.740741 | [0.065 0.935] | 0.615 |
+| (0.55, 74) | 0.101802 | 0.516198 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0708638 | 0.671376 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 75) | 0.0852682 | 0.540732 | 0.626 | [0.076 0.374 0. 0.55 ] | 0.0630882 | 0.68318 | 0.746269 | [0.076 0.924] | 0.626 |
+| (0.55, 76) | 0.0654355 | 0.555565 | 0.621 | [0.073 0.377 0.002 0.548] | 0.048294 | 0.694757 | 0.743051 | [0.075 0.925] | 0.621 |
+| (0.55, 77) | 0.0788674 | 0.540133 | 0.619 | [0.07 0.38 0.001 0.549] | 0.0505293 | 0.691864 | 0.742394 | [0.071 0.929] | 0.619 |
+| (0.55, 78) | 0.0809986 | 0.521001 | 0.602 | [0.052 0.398 0. 0.55 ] | 0.0579031 | 0.676409 | 0.734312 | [0.052 0.948] | 0.602 |
+| (0.55, 79) | 0.0710941 | 0.543906 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0542047 | 0.686186 | 0.740391 | [0.067 0.933] | 0.615 |
+| (0.55, 80) | 0.104299 | 0.515701 | 0.62 | [0.071 0.379 0.001 0.549] | 0.065018 | 0.677878 | 0.742896 | [0.072 0.928] | 0.62 |
+| (0.55, 81) | 0.053892 | 0.565108 | 0.619 | [0.069 0.381 0. 0.55 ] | 0.0370133 | 0.705728 | 0.742741 | [0.069 0.931] | 0.619 |
+| (0.55, 82) | 0.0392997 | 0.5717 | 0.611 | [0.061 0.389 0. 0.55 ] | 0.0282315 | 0.710519 | 0.738751 | [0.061 0.939] | 0.611 |
+| (0.55, 83) | 0.0996358 | 0.514364 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0624861 | 0.677406 | 0.739892 | [0.066 0.934] | 0.614 |
+| (0.55, 84) | 0.0668299 | 0.56717 | 0.634 | [0.084 0.366 0. 0.55 ] | 0.049494 | 0.700847 | 0.750341 | [0.084 0.916] | 0.634 |
+| (0.55, 85) | 0.0628239 | 0.555176 | 0.618 | [0.068 0.382 0. 0.55 ] | 0.0445864 | 0.697654 | 0.74224 | [0.068 0.932] | 0.618 |
+| (0.55, 86) | 0.080314 | 0.529686 | 0.61 | [0.06 0.39 0. 0.55] | 0.0544223 | 0.683833 | 0.738255 | [0.06 0.94] | 0.61 |
+| (0.55, 87) | 0.0760951 | 0.544905 | 0.621 | [0.071 0.379 0. 0.55 ] | 0.0544041 | 0.689342 | 0.743746 | [0.071 0.929] | 0.621 |
+| (0.55, 88) | 0.0713211 | 0.557679 | 0.629 | [0.079 0.371 0. 0.55 ] | 0.0527228 | 0.695068 | 0.747791 | [0.079 0.921] | 0.629 |
+| (0.55, 89) | 0.0759801 | 0.53702 | 0.613 | [0.063 0.387 0. 0.55 ] | 0.0498224 | 0.689922 | 0.739744 | [0.063 0.937] | 0.613 |
+| (0.55, 90) | 0.0725677 | 0.541432 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0533703 | 0.686872 | 0.740242 | [0.064 0.936] | 0.614 |
+| (0.55, 91) | 0.0842715 | 0.530729 | 0.615 | [0.066 0.384 0.001 0.549] | 0.0616303 | 0.678761 | 0.740391 | [0.067 0.933] | 0.615 |
+| (0.55, 92) | 0.0881018 | 0.525898 | 0.614 | [0.065 0.385 0.001 0.549] | 0.0610744 | 0.678818 | 0.739892 | [0.066 0.934] | 0.614 |
+| (0.55, 93) | 0.0972321 | 0.513768 | 0.611 | [0.062 0.388 0.001 0.549] | 0.0641005 | 0.674299 | 0.738399 | [0.063 0.937] | 0.611 |
+| (0.55, 94) | 0.0627574 | 0.562243 | 0.625 | [0.075 0.375 0. 0.55 ] | 0.0409383 | 0.704824 | 0.745763 | [0.075 0.925] | 0.625 |
+| (0.55, 95) | 0.07313 | 0.53787 | 0.611 | [0.062 0.388 0.001 0.549] | 0.0538739 | 0.684526 | 0.738399 | [0.063 0.937] | 0.611 |
+| (0.55, 96) | 0.0938753 | 0.508125 | 0.602 | [0.053 0.397 0.001 0.549] | 0.0607252 | 0.673232 | 0.733957 | [0.054 0.946] | 0.602 |
+| (0.55, 97) | 0.0986028 | 0.515397 | 0.614 | [0.064 0.386 0. 0.55 ] | 0.0621644 | 0.678078 | 0.740242 | [0.064 0.936] | 0.614 |
+| (0.55, 98) | 0.0961309 | 0.527869 | 0.624 | [0.074 0.376 0. 0.55 ] | 0.05855 | 0.686707 | 0.745257 | [0.074 0.926] | 0.624 |
+| (0.55, 99) | 0.0959075 | 0.505093 | 0.601 | [0.052 0.398 0.001 0.549] | 0.0639415 | 0.669525 | 0.733467 | [0.053 0.947] | 0.601 |
+| (0.6, 0) | 0.0881511 | 0.577849 | 0.666 | [0.067 0.333 0.001 0.599] | 0.055237 | 0.726747 | 0.781984 | [0.068 0.932] | 0.666 |
+| (0.6, 1) | 0.0676567 | 0.594343 | 0.662 | [0.063 0.337 0.001 0.599] | 0.0477349 | 0.732213 | 0.779948 | [0.064 0.936] | 0.662 |
+| (0.6, 2) | 0.0491176 | 0.612882 | 0.662 | [0.062 0.338 0. 0.6 ] | 0.027934 | 0.7523 | 0.780234 | [0.062 0.938] | 0.662 |
+| (0.6, 3) | 0.0568165 | 0.596183 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.035421 | 0.740274 | 0.775695 | [0.053 0.947] | 0.653 |
+| (0.6, 4) | 0.0615035 | 0.605496 | 0.667 | [0.068 0.332 0.001 0.599] | 0.040621 | 0.741874 | 0.782495 | [0.069 0.931] | 0.667 |
+| (0.6, 5) | 0.0730526 | 0.589947 | 0.663 | [0.063 0.337 0. 0.6 ] | 0.0445382 | 0.736204 | 0.780742 | [0.063 0.937] | 0.663 |
+| (0.6, 6) | 0.0522423 | 0.607758 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0293391 | 0.749882 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 7) | 0.0615754 | 0.594425 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0386705 | 0.738532 | 0.777202 | [0.056 0.944] | 0.656 |
+| (0.6, 8) | 0.0665795 | 0.582421 | 0.649 | [0.049 0.351 0. 0.6 ] | 0.0407432 | 0.732951 | 0.773694 | [0.049 0.951] | 0.649 |
+| (0.6, 9) | 0.0737038 | 0.576296 | 0.65 | [0.051 0.349 0.001 0.599] | 0.0521496 | 0.721752 | 0.773902 | [0.052 0.948] | 0.65 |
+| (0.6, 10) | 0.085578 | 0.578422 | 0.664 | [0.064 0.336 0. 0.6 ] | 0.0560622 | 0.725188 | 0.78125 | [0.064 0.936] | 0.664 |
+| (0.6, 11) | 0.064456 | 0.598544 | 0.663 | [0.064 0.336 0.001 0.599] | 0.0459933 | 0.734463 | 0.780456 | [0.065 0.935] | 0.663 |
+| (0.6, 12) | 0.0562835 | 0.604716 | 0.661 | [0.061 0.339 0. 0.6 ] | 0.0319463 | 0.747781 | 0.779727 | [0.061 0.939] | 0.661 |
+| (0.6, 13) | 0.0716397 | 0.59336 | 0.665 | [0.065 0.335 0. 0.6 ] | 0.0419245 | 0.739834 | 0.781759 | [0.065 0.935] | 0.665 |
+| (0.6, 14) | 0.0583248 | 0.601675 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0437987 | 0.735422 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 15) | 0.0434325 | 0.614568 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.0282215 | 0.749989 | 0.77821 | [0.058 0.942] | 0.658 |
+| (0.6, 16) | 0.047439 | 0.621561 | 0.669 | [0.07 0.33 0.001 0.599] | 0.0270545 | 0.756464 | 0.783519 | [0.071 0.929] | 0.669 |
+| (0.6, 17) | 0.0933332 | 0.582667 | 0.676 | [0.077 0.323 0.001 0.599] | 0.058648 | 0.728474 | 0.787122 | [0.078 0.922] | 0.676 |
+| (0.6, 18) | 0.0390986 | 0.632901 | 0.672 | [0.072 0.328 0. 0.6 ] | 0.0259942 | 0.759346 | 0.78534 | [0.072 0.928] | 0.672 |
+| (0.6, 19) | 0.0678786 | 0.600121 | 0.668 | [0.068 0.332 0. 0.6 ] | 0.0480079 | 0.735282 | 0.78329 | [0.068 0.932] | 0.668 |
+| (0.6, 20) | 0.0539102 | 0.60209 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0370685 | 0.740134 | 0.777202 | [0.056 0.944] | 0.656 |
+| (0.6, 21) | 0.0820918 | 0.574908 | 0.657 | [0.058 0.342 0.001 0.599] | 0.0477883 | 0.729629 | 0.777417 | [0.059 0.941] | 0.657 |
+| (0.6, 22) | 0.0825172 | 0.577483 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0515437 | 0.727677 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 23) | 0.0568959 | 0.596104 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0359543 | 0.739741 | 0.775695 | [0.053 0.947] | 0.653 |
+| (0.6, 24) | 0.0690674 | 0.599933 | 0.669 | [0.069 0.331 0. 0.6 ] | 0.0425673 | 0.741234 | 0.783801 | [0.069 0.931] | 0.669 |
+| (0.6, 25) | 0.076607 | 0.581393 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.048413 | 0.729797 | 0.77821 | [0.058 0.942] | 0.658 |
+| (0.6, 26) | 0.0757756 | 0.580224 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0556539 | 0.721548 | 0.777202 | [0.056 0.944] | 0.656 |
+| (0.6, 27) | 0.0648862 | 0.578114 | 0.643 | [0.044 0.356 0.001 0.599] | 0.0435439 | 0.726874 | 0.770418 | [0.045 0.955] | 0.643 |
+| (0.6, 28) | 0.0528143 | 0.600186 | 0.653 | [0.054 0.346 0.001 0.599] | 0.0340945 | 0.74131 | 0.775405 | [0.055 0.945] | 0.653 |
+| (0.6, 29) | 0.0667359 | 0.601264 | 0.668 | [0.068 0.332 0. 0.6 ] | 0.0335976 | 0.749692 | 0.78329 | [0.068 0.932] | 0.668 |
+| (0.6, 30) | 0.0675497 | 0.58545 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0414239 | 0.734271 | 0.775695 | [0.053 0.947] | 0.653 |
+| (0.6, 31) | 0.0660047 | 0.598995 | 0.665 | [0.066 0.334 0.001 0.599] | 0.0426951 | 0.738779 | 0.781474 | [0.067 0.933] | 0.665 |
+| (0.6, 32) | 0.0442055 | 0.618795 | 0.663 | [0.063 0.337 0. 0.6 ] | 0.030497 | 0.750245 | 0.780742 | [0.063 0.937] | 0.663 |
+| (0.6, 33) | 0.0443751 | 0.609625 | 0.654 | [0.057 0.343 0.003 0.597] | 0.021217 | 0.754108 | 0.775325 | [0.06 0.94] | 0.654 |
+| (0.6, 34) | 0.0943248 | 0.576675 | 0.671 | [0.072 0.328 0.001 0.599] | 0.0621463 | 0.722399 | 0.784545 | [0.073 0.927] | 0.671 |
+| (0.6, 35) | 0.0535663 | 0.600434 | 0.654 | [0.054 0.346 0. 0.6 ] | 0.0296445 | 0.746552 | 0.776197 | [0.054 0.946] | 0.654 |
+| (0.6, 36) | 0.0605562 | 0.604444 | 0.665 | [0.065 0.335 0. 0.6 ] | 0.0392217 | 0.742537 | 0.781759 | [0.065 0.935] | 0.665 |
+| (0.6, 37) | 0.0866943 | 0.573306 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0538976 | 0.725323 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 38) | 0.0545823 | 0.593418 | 0.648 | [0.048 0.352 0. 0.6 ] | 0.0352752 | 0.737921 | 0.773196 | [0.048 0.952] | 0.648 |
+| (0.6, 39) | 0.0336199 | 0.63738 | 0.671 | [0.071 0.329 0. 0.6 ] | 0.0231063 | 0.76172 | 0.784827 | [0.071 0.929] | 0.671 |
+| (0.6, 40) | 0.087924 | 0.585076 | 0.673 | [0.074 0.326 0.001 0.599] | 0.0570552 | 0.728519 | 0.785574 | [0.075 0.925] | 0.673 |
+| (0.6, 41) | 0.0627829 | 0.594217 | 0.657 | [0.057 0.343 0. 0.6 ] | 0.0367148 | 0.740991 | 0.777706 | [0.057 0.943] | 0.657 |
+| (0.6, 42) | 0.0661217 | 0.588878 | 0.655 | [0.055 0.345 0. 0.6 ] | 0.0462947 | 0.730404 | 0.776699 | [0.055 0.945] | 0.655 |
+| (0.6, 43) | 0.0472093 | 0.608791 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0315161 | 0.745686 | 0.777202 | [0.056 0.944] | 0.656 |
+| (0.6, 44) | 0.062447 | 0.595553 | 0.658 | [0.059 0.341 0.001 0.599] | 0.0393384 | 0.738584 | 0.777922 | [0.06 0.94] | 0.658 |
+| (0.6, 45) | 0.0553339 | 0.597666 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0316878 | 0.744007 | 0.775695 | [0.053 0.947] | 0.653 |
+| (0.6, 46) | 0.0603068 | 0.612693 | 0.673 | [0.073 0.327 0. 0.6 ] | 0.0403993 | 0.745455 | 0.785855 | [0.073 0.927] | 0.673 |
+| (0.6, 47) | 0.05245 | 0.59255 | 0.645 | [0.045 0.355 0. 0.6 ] | 0.0331539 | 0.73855 | 0.771704 | [0.045 0.955] | 0.645 |
+| (0.6, 48) | 0.0380303 | 0.61797 | 0.656 | [0.057 0.343 0.001 0.599] | 0.0253723 | 0.751541 | 0.776913 | [0.058 0.942] | 0.656 |
+| (0.6, 49) | 0.0738868 | 0.593113 | 0.667 | [0.067 0.333 0. 0.6 ] | 0.0450897 | 0.737689 | 0.782779 | [0.067 0.933] | 0.667 |
+| (0.6, 50) | 0.0354761 | 0.619524 | 0.655 | [0.055 0.345 0. 0.6 ] | 0.0207475 | 0.755952 | 0.776699 | [0.055 0.945] | 0.655 |
+| (0.6, 51) | 0.0437408 | 0.600259 | 0.644 | [0.046 0.354 0.002 0.598] | 0.0251752 | 0.745443 | 0.770619 | [0.048 0.952] | 0.644 |
+| (0.6, 52) | 0.0453087 | 0.612691 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.0260618 | 0.752148 | 0.77821 | [0.058 0.942] | 0.658 |
+| (0.6, 53) | 0.0722881 | 0.592712 | 0.665 | [0.065 0.335 0. 0.6 ] | 0.047134 | 0.734625 | 0.781759 | [0.065 0.935] | 0.665 |
+| (0.6, 54) | 0.0421048 | 0.615895 | 0.658 | [0.059 0.341 0.001 0.599] | 0.0287259 | 0.749196 | 0.777922 | [0.06 0.94] | 0.658 |
+| (0.6, 55) | 0.066419 | 0.595581 | 0.662 | [0.062 0.338 0. 0.6 ] | 0.048597 | 0.731637 | 0.780234 | [0.062 0.938] | 0.662 |
+| (0.6, 56) | 0.0490829 | 0.605917 | 0.655 | [0.056 0.344 0.001 0.599] | 0.0286827 | 0.747727 | 0.77641 | [0.057 0.943] | 0.655 |
+| (0.6, 57) | 0.066909 | 0.583091 | 0.65 | [0.05 0.35 0. 0.6 ] | 0.0391516 | 0.735042 | 0.774194 | [0.05 0.95] | 0.65 |
+| (0.6, 58) | 0.0463631 | 0.608637 | 0.655 | [0.057 0.343 0.002 0.598] | 0.0324057 | 0.743714 | 0.776119 | [0.059 0.941] | 0.655 |
+| (0.6, 59) | 0.0634421 | 0.586558 | 0.65 | [0.05 0.35 0. 0.6 ] | 0.0366035 | 0.73759 | 0.774194 | [0.05 0.95] | 0.65 |
+| (0.6, 60) | 0.0772581 | 0.582742 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0456753 | 0.733546 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 61) | 0.0671458 | 0.591854 | 0.659 | [0.06 0.34 0.001 0.599] | 0.0450789 | 0.733349 | 0.778428 | [0.061 0.939] | 0.659 |
+| (0.6, 62) | 0.0522664 | 0.599734 | 0.652 | [0.054 0.346 0.002 0.598] | 0.0359455 | 0.738666 | 0.774611 | [0.056 0.944] | 0.652 |
+| (0.6, 63) | 0.063116 | 0.588884 | 0.652 | [0.052 0.348 0. 0.6 ] | 0.0464068 | 0.728787 | 0.775194 | [0.052 0.948] | 0.652 |
+| (0.6, 64) | 0.0512798 | 0.61072 | 0.662 | [0.062 0.338 0. 0.6 ] | 0.0361072 | 0.744127 | 0.780234 | [0.062 0.938] | 0.662 |
+| (0.6, 65) | 0.0398496 | 0.62515 | 0.665 | [0.066 0.334 0.001 0.599] | 0.0283116 | 0.753163 | 0.781474 | [0.067 0.933] | 0.665 |
+| (0.6, 66) | 0.05223 | 0.60377 | 0.656 | [0.056 0.344 0. 0.6 ] | 0.0330846 | 0.744118 | 0.777202 | [0.056 0.944] | 0.656 |
+| (0.6, 67) | 0.0785234 | 0.581477 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0465799 | 0.732641 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 68) | 0.0458468 | 0.604153 | 0.65 | [0.051 0.349 0.001 0.599] | 0.0325445 | 0.741357 | 0.773902 | [0.052 0.948] | 0.65 |
+| (0.6, 69) | 0.0860971 | 0.577903 | 0.664 | [0.065 0.335 0.001 0.599] | 0.0522512 | 0.728714 | 0.780965 | [0.066 0.934] | 0.664 |
+| (0.6, 70) | 0.0806746 | 0.589325 | 0.67 | [0.071 0.329 0.001 0.599] | 0.0519335 | 0.732098 | 0.784031 | [0.072 0.928] | 0.67 |
+| (0.6, 71) | 0.0784531 | 0.577547 | 0.656 | [0.057 0.343 0.001 0.599] | 0.0508206 | 0.726092 | 0.776913 | [0.058 0.942] | 0.656 |
+| (0.6, 72) | 0.0399431 | 0.613057 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.0248862 | 0.750809 | 0.775695 | [0.053 0.947] | 0.653 |
+| (0.6, 73) | 0.0907004 | 0.5673 | 0.658 | [0.058 0.342 0. 0.6 ] | 0.0579146 | 0.720295 | 0.77821 | [0.058 0.942] | 0.658 |
+| (0.6, 74) | 0.0589133 | 0.596087 | 0.655 | [0.057 0.343 0.002 0.598] | 0.035358 | 0.740761 | 0.776119 | [0.059 0.941] | 0.655 |
+| (0.6, 75) | 0.0447162 | 0.624284 | 0.669 | [0.07 0.33 0.001 0.599] | 0.0297811 | 0.753738 | 0.783519 | [0.071 0.929] | 0.669 |
+| (0.6, 76) | 0.0764676 | 0.583532 | 0.66 | [0.061 0.339 0.001 0.599] | 0.0455743 | 0.733359 | 0.778934 | [0.062 0.938] | 0.66 |
+| (0.6, 77) | 0.0816418 | 0.584358 | 0.666 | [0.066 0.334 0. 0.6 ] | 0.0474277 | 0.734841 | 0.782269 | [0.066 0.934] | 0.666 |
+| (0.6, 78) | 0.0735751 | 0.572425 | 0.646 | [0.047 0.353 0.001 0.599] | 0.0540717 | 0.717836 | 0.771907 | [0.048 0.952] | 0.646 |
+| (0.6, 79) | 0.0570677 | 0.596932 | 0.654 | [0.055 0.345 0.001 0.599] | 0.0358959 | 0.740011 | 0.775907 | [0.056 0.944] | 0.654 |
+| (0.6, 80) | 0.0479097 | 0.60509 | 0.653 | [0.053 0.347 0. 0.6 ] | 0.032508 | 0.743187 | 0.775695 | [0.053 0.947] | 0.653 |
+| (0.6, 81) | 0.0575586 | 0.594441 | 0.652 | [0.052 0.348 0. 0.6 ] | 0.038032 | 0.737162 | 0.775194 | [0.052 0.948] | 0.652 |
+| (0.6, 82) | 0.0761639 | 0.587836 | 0.664 | [0.064 0.336 0. 0.6 ] | 0.0527736 | 0.728476 | 0.78125 | [0.064 0.936] | 0.664 |
+| (0.6, 83) | 0.0529422 | 0.607058 | 0.66 | [0.062 0.338 0.002 0.598] | 0.0371465 | 0.741499 | 0.778646 | [0.064 0.936] | 0.66 |
+| (0.6, 84) | 0.0580051 | 0.595995 | 0.654 | [0.055 0.345 0.001 0.599] | 0.0419757 | 0.733931 | 0.775907 | [0.056 0.944] | 0.654 |
+| (0.6, 85) | 0.0759486 | 0.587051 | 0.663 | [0.064 0.336 0.001 0.599] | 0.0539609 | 0.726495 | 0.780456 | [0.065 0.935] | 0.663 |
+| (0.6, 86) | 0.055749 | 0.619251 | 0.675 | [0.076 0.324 0.001 0.599] | 0.0404567 | 0.746149 | 0.786605 | [0.077 0.923] | 0.675 |
+| (0.6, 87) | 0.0509463 | 0.610054 | 0.661 | [0.061 0.339 0. 0.6 ] | 0.0335963 | 0.746131 | 0.779727 | [0.061 0.939] | 0.661 |
+| (0.6, 88) | 0.0355192 | 0.647481 | 0.683 | [0.083 0.317 0. 0.6 ] | 0.0262492 | 0.764786 | 0.791035 | [0.083 0.917] | 0.683 |
+| (0.6, 89) | 0.0640233 | 0.596977 | 0.661 | [0.061 0.339 0. 0.6 ] | 0.0340662 | 0.745661 | 0.779727 | [0.061 0.939] | 0.661 |
+| (0.6, 90) | 0.0701055 | 0.599894 | 0.67 | [0.07 0.33 0. 0.6 ] | 0.0407704 | 0.743543 | 0.784314 | [0.07 0.93] | 0.67 |
+| (0.6, 91) | 0.0341839 | 0.616816 | 0.651 | [0.052 0.348 0.001 0.599] | 0.0247255 | 0.749677 | 0.774402 | [0.053 0.947] | 0.651 |
+| (0.6, 92) | 0.0685819 | 0.611418 | 0.68 | [0.08 0.32 0. 0.6 ] | 0.0442119 | 0.745262 | 0.789474 | [0.08 0.92] | 0.68 |
+| (0.6, 93) | 0.0894146 | 0.567585 | 0.657 | [0.058 0.342 0.001 0.599] | 0.0539746 | 0.723443 | 0.777417 | [0.059 0.941] | 0.657 |
+| (0.6, 94) | 0.0650644 | 0.598936 | 0.664 | [0.064 0.336 0. 0.6 ] | 0.037461 | 0.743789 | 0.78125 | [0.064 0.936] | 0.664 |
+| (0.6, 95) | 0.0508844 | 0.599116 | 0.65 | [0.05 0.35 0. 0.6 ] | 0.0363045 | 0.737889 | 0.774194 | [0.05 0.95] | 0.65 |
+| (0.6, 96) | 0.0661985 | 0.603802 | 0.67 | [0.07 0.33 0. 0.6 ] | 0.039231 | 0.745083 | 0.784314 | [0.07 0.93] | 0.67 |
+| (0.6, 97) | 0.0892339 | 0.565766 | 0.655 | [0.057 0.343 0.002 0.598] | 0.0551233 | 0.720996 | 0.776119 | [0.059 0.941] | 0.655 |
+| (0.6, 98) | 0.0976272 | 0.562373 | 0.66 | [0.06 0.34 0. 0.6 ] | 0.0597714 | 0.719449 | 0.779221 | [0.06 0.94] | 0.66 |
+| (0.6, 99) | 0.0636941 | 0.593306 | 0.657 | [0.058 0.342 0.001 0.599] | 0.0418411 | 0.735576 | 0.777417 | [0.059 0.941] | 0.657 |
+| (0.65, 0) | 0.0739099 | 0.61709 | 0.691 | [0.041 0.309 0. 0.65 ] | 0.0526754 | 0.75528 | 0.807955 | [0.041 0.959] | 0.691 |
+| (0.65, 1) | 0.0477952 | 0.658205 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0325986 | 0.78296 | 0.815558 | [0.056 0.944] | 0.706 |
+| (0.65, 2) | 0.0229299 | 0.67707 | 0.7 | [0.05 0.3 0. 0.65] | 0.0159672 | 0.796533 | 0.8125 | [0.05 0.95] | 0.7 |
+| (0.65, 3) | 0.0538452 | 0.645155 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0312362 | 0.780756 | 0.811993 | [0.049 0.951] | 0.699 |
+| (0.65, 4) | 0.0925105 | 0.61149 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0581155 | 0.756421 | 0.814536 | [0.054 0.946] | 0.704 |
+| (0.65, 5) | 0.0578091 | 0.647191 | 0.705 | [0.056 0.294 0.001 0.649] | 0.0351116 | 0.779703 | 0.814815 | [0.057 0.943] | 0.705 |
+| (0.65, 6) | 0.062668 | 0.629332 | 0.692 | [0.042 0.308 0. 0.65 ] | 0.0378076 | 0.77065 | 0.808458 | [0.042 0.958] | 0.692 |
+| (0.65, 7) | 0.0638892 | 0.645111 | 0.709 | [0.06 0.29 0.001 0.649] | 0.0344787 | 0.782387 | 0.816866 | [0.061 0.939] | 0.709 |
+| (0.65, 8) | 0.0890857 | 0.608914 | 0.698 | [0.049 0.301 0.001 0.649] | 0.0547982 | 0.756452 | 0.81125 | [0.05 0.95] | 0.698 |
+| (0.65, 9) | 0.0611097 | 0.63789 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0413559 | 0.770637 | 0.811993 | [0.049 0.951] | 0.699 |
+| (0.65, 10) | 0.0562112 | 0.632789 | 0.689 | [0.039 0.311 0. 0.65 ] | 0.0323477 | 0.774605 | 0.806952 | [0.039 0.961] | 0.689 |
+| (0.65, 11) | 0.0589517 | 0.638048 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0366973 | 0.774282 | 0.810979 | [0.047 0.953] | 0.697 |
+| (0.65, 12) | 0.0482449 | 0.654755 | 0.703 | [0.053 0.297 0. 0.65 ] | 0.0320813 | 0.781945 | 0.814026 | [0.053 0.947] | 0.703 |
+| (0.65, 13) | 0.0736681 | 0.636332 | 0.71 | [0.061 0.289 0.001 0.649] | 0.0420889 | 0.775291 | 0.81738 | [0.062 0.938] | 0.71 |
+| (0.65, 14) | 0.0430404 | 0.66396 | 0.707 | [0.057 0.293 0. 0.65 ] | 0.0287048 | 0.787366 | 0.81607 | [0.057 0.943] | 0.707 |
+| (0.65, 15) | 0.0560687 | 0.637931 | 0.694 | [0.045 0.305 0.001 0.649] | 0.0310618 | 0.778165 | 0.809227 | [0.046 0.954] | 0.694 |
+| (0.65, 16) | 0.0456324 | 0.653368 | 0.699 | [0.05 0.3 0.001 0.649] | 0.0263883 | 0.785369 | 0.811757 | [0.051 0.949] | 0.699 |
+| (0.65, 17) | 0.064613 | 0.632387 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0387813 | 0.772198 | 0.810979 | [0.047 0.953] | 0.697 |
+| (0.65, 18) | 0.0734902 | 0.62551 | 0.699 | [0.052 0.298 0.003 0.647] | 0.0453684 | 0.765917 | 0.811285 | [0.055 0.945] | 0.699 |
+| (0.65, 19) | 0.0628344 | 0.639166 | 0.702 | [0.054 0.296 0.002 0.648] | 0.0345718 | 0.778477 | 0.813049 | [0.056 0.944] | 0.702 |
+| (0.65, 20) | 0.0673456 | 0.640654 | 0.708 | [0.059 0.291 0.001 0.649] | 0.0388652 | 0.777487 | 0.816352 | [0.06 0.94] | 0.708 |
+| (0.65, 21) | 0.0752692 | 0.617731 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0459319 | 0.763029 | 0.808961 | [0.043 0.957] | 0.693 |
+| (0.65, 22) | 0.0450542 | 0.652946 | 0.698 | [0.049 0.301 0.001 0.649] | 0.0298831 | 0.781367 | 0.81125 | [0.05 0.95] | 0.698 |
+| (0.65, 23) | 0.0337217 | 0.675278 | 0.709 | [0.06 0.29 0.001 0.649] | 0.0242411 | 0.792625 | 0.816866 | [0.061 0.939] | 0.709 |
+| (0.65, 24) | 0.052651 | 0.649349 | 0.702 | [0.054 0.296 0.002 0.648] | 0.0312041 | 0.781845 | 0.813049 | [0.056 0.944] | 0.702 |
+| (0.65, 25) | 0.0663186 | 0.632681 | 0.699 | [0.05 0.3 0.001 0.649] | 0.0405875 | 0.77117 | 0.811757 | [0.051 0.949] | 0.699 |
+| (0.65, 26) | 0.0504554 | 0.668545 | 0.719 | [0.069 0.281 0. 0.65 ] | 0.0367366 | 0.785528 | 0.822264 | [0.069 0.931] | 0.719 |
+| (0.65, 27) | 0.0624661 | 0.646534 | 0.709 | [0.06 0.29 0.001 0.649] | 0.0340857 | 0.78278 | 0.816866 | [0.061 0.939] | 0.709 |
+| (0.65, 28) | 0.0504084 | 0.651592 | 0.702 | [0.054 0.296 0.002 0.648] | 0.0300143 | 0.783035 | 0.813049 | [0.056 0.944] | 0.702 |
+| (0.65, 29) | 0.0659238 | 0.629076 | 0.695 | [0.046 0.304 0.001 0.649] | 0.0444182 | 0.765314 | 0.809732 | [0.047 0.953] | 0.695 |
+| (0.65, 30) | 0.0823759 | 0.623624 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0473784 | 0.76818 | 0.815558 | [0.056 0.944] | 0.706 |
+| (0.65, 31) | 0.06098 | 0.63702 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.0393581 | 0.772128 | 0.811486 | [0.048 0.952] | 0.698 |
+| (0.65, 32) | 0.0843391 | 0.613661 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.0515263 | 0.759959 | 0.811486 | [0.048 0.952] | 0.698 |
+| (0.65, 33) | 0.0906488 | 0.620351 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.0539358 | 0.764189 | 0.818125 | [0.061 0.939] | 0.711 |
+| (0.65, 34) | 0.051511 | 0.654489 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0330441 | 0.782514 | 0.815558 | [0.056 0.944] | 0.706 |
+| (0.65, 35) | 0.068127 | 0.623873 | 0.692 | [0.044 0.306 0.002 0.648] | 0.0475416 | 0.760438 | 0.80798 | [0.046 0.954] | 0.692 |
+| (0.65, 36) | 0.05139 | 0.65561 | 0.707 | [0.058 0.292 0.001 0.649] | 0.0342364 | 0.781603 | 0.815839 | [0.059 0.941] | 0.707 |
+| (0.65, 37) | 0.0553304 | 0.64467 | 0.7 | [0.05 0.3 0. 0.65] | 0.0339875 | 0.778513 | 0.8125 | [0.05 0.95] | 0.7 |
+| (0.65, 38) | 0.0220005 | 0.683 | 0.705 | [0.058 0.292 0.003 0.647] | 0.0105615 | 0.803787 | 0.814349 | [0.061 0.939] | 0.705 |
+| (0.65, 39) | 0.0344814 | 0.684519 | 0.719 | [0.069 0.281 0. 0.65 ] | 0.0200217 | 0.802243 | 0.822264 | [0.069 0.931] | 0.719 |
+| (0.65, 40) | 0.0192848 | 0.687715 | 0.707 | [0.058 0.292 0.001 0.649] | 0.0118281 | 0.804011 | 0.815839 | [0.059 0.941] | 0.707 |
+| (0.65, 41) | 0.0629462 | 0.641054 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0417315 | 0.772805 | 0.814536 | [0.054 0.946] | 0.704 |
+| (0.65, 42) | 0.0509591 | 0.648041 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0323075 | 0.779685 | 0.811993 | [0.049 0.951] | 0.699 |
+| (0.65, 43) | 0.0284053 | 0.684595 | 0.713 | [0.063 0.287 0. 0.65 ] | 0.0186126 | 0.800543 | 0.819156 | [0.063 0.937] | 0.713 |
+| (0.65, 44) | 0.0542485 | 0.646751 | 0.701 | [0.051 0.299 0. 0.65 ] | 0.0377042 | 0.775304 | 0.813008 | [0.051 0.949] | 0.701 |
+| (0.65, 45) | 0.0473474 | 0.648653 | 0.696 | [0.046 0.304 0. 0.65 ] | 0.0312429 | 0.779231 | 0.810474 | [0.046 0.954] | 0.696 |
+| (0.65, 46) | 0.0573545 | 0.647646 | 0.705 | [0.055 0.295 0. 0.65 ] | 0.0328666 | 0.78218 | 0.815047 | [0.055 0.945] | 0.705 |
+| (0.65, 47) | 0.0778962 | 0.630104 | 0.708 | [0.058 0.292 0. 0.65 ] | 0.0481544 | 0.768428 | 0.816583 | [0.058 0.942] | 0.708 |
+| (0.65, 48) | 0.0636552 | 0.634345 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.042687 | 0.768799 | 0.811486 | [0.048 0.952] | 0.698 |
+| (0.65, 49) | 0.0684301 | 0.62757 | 0.696 | [0.046 0.304 0. 0.65 ] | 0.0417784 | 0.768695 | 0.810474 | [0.046 0.954] | 0.696 |
+| (0.65, 50) | 0.0600838 | 0.648916 | 0.709 | [0.059 0.291 0. 0.65 ] | 0.0338159 | 0.78328 | 0.817096 | [0.059 0.941] | 0.709 |
+| (0.65, 51) | 0.0315922 | 0.670408 | 0.702 | [0.052 0.298 0. 0.65 ] | 0.0197787 | 0.793738 | 0.813517 | [0.052 0.948] | 0.702 |
+| (0.65, 52) | 0.0805029 | 0.622497 | 0.703 | [0.053 0.297 0. 0.65 ] | 0.0511013 | 0.762925 | 0.814026 | [0.053 0.947] | 0.703 |
+| (0.65, 53) | 0.0684217 | 0.642578 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.0392399 | 0.778885 | 0.818125 | [0.061 0.939] | 0.711 |
+| (0.65, 54) | 0.0478134 | 0.656187 | 0.704 | [0.055 0.295 0.001 0.649] | 0.0278887 | 0.786415 | 0.814304 | [0.056 0.944] | 0.704 |
+| (0.65, 55) | 0.042591 | 0.654409 | 0.697 | [0.048 0.302 0.001 0.649] | 0.0266163 | 0.784127 | 0.810743 | [0.049 0.951] | 0.697 |
+| (0.65, 56) | 0.029453 | 0.676547 | 0.706 | [0.057 0.293 0.001 0.649] | 0.0176713 | 0.797655 | 0.815327 | [0.058 0.942] | 0.706 |
+| (0.65, 57) | 0.0740491 | 0.622951 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0467645 | 0.764215 | 0.810979 | [0.047 0.953] | 0.697 |
+| (0.65, 58) | 0.0721752 | 0.626825 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0467288 | 0.765264 | 0.811993 | [0.049 0.951] | 0.699 |
+| (0.65, 59) | 0.0720319 | 0.631968 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0479897 | 0.766547 | 0.814536 | [0.054 0.946] | 0.704 |
+| (0.65, 60) | 0.0632844 | 0.629716 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0401505 | 0.76881 | 0.808961 | [0.043 0.957] | 0.693 |
+| (0.65, 61) | 0.0312424 | 0.673758 | 0.705 | [0.056 0.294 0.001 0.649] | 0.0161445 | 0.79867 | 0.814815 | [0.057 0.943] | 0.705 |
+| (0.65, 62) | 0.0886932 | 0.611307 | 0.7 | [0.05 0.3 0. 0.65] | 0.0558643 | 0.756636 | 0.8125 | [0.05 0.95] | 0.7 |
+| (0.65, 63) | 0.0666069 | 0.627393 | 0.694 | [0.044 0.306 0. 0.65 ] | 0.0392557 | 0.770209 | 0.809465 | [0.044 0.956] | 0.694 |
+| (0.65, 64) | 0.0493815 | 0.650619 | 0.7 | [0.05 0.3 0. 0.65] | 0.033134 | 0.779366 | 0.8125 | [0.05 0.95] | 0.7 |
+| (0.65, 65) | 0.0743474 | 0.627653 | 0.702 | [0.053 0.297 0.001 0.649] | 0.0455442 | 0.767739 | 0.813283 | [0.054 0.946] | 0.702 |
+| (0.65, 66) | 0.0590576 | 0.642942 | 0.702 | [0.052 0.298 0. 0.65 ] | 0.0378606 | 0.775656 | 0.813517 | [0.052 0.948] | 0.702 |
+| (0.65, 67) | 0.0504622 | 0.640538 | 0.691 | [0.042 0.308 0.001 0.649] | 0.0288882 | 0.778828 | 0.807716 | [0.043 0.957] | 0.691 |
+| (0.65, 68) | 0.0491287 | 0.651871 | 0.701 | [0.051 0.299 0. 0.65 ] | 0.0298382 | 0.78317 | 0.813008 | [0.051 0.949] | 0.701 |
+| (0.65, 69) | 0.0671233 | 0.625877 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0465888 | 0.762372 | 0.808961 | [0.043 0.957] | 0.693 |
+| (0.65, 70) | 0.0581822 | 0.649818 | 0.708 | [0.059 0.291 0.001 0.649] | 0.039018 | 0.777334 | 0.816352 | [0.06 0.94] | 0.708 |
+| (0.65, 71) | 0.0656468 | 0.639353 | 0.705 | [0.055 0.295 0. 0.65 ] | 0.0450479 | 0.769999 | 0.815047 | [0.055 0.945] | 0.705 |
+| (0.65, 72) | 0.042696 | 0.659304 | 0.702 | [0.052 0.298 0. 0.65 ] | 0.029769 | 0.783748 | 0.813517 | [0.052 0.948] | 0.702 |
+| (0.65, 73) | 0.0621281 | 0.642872 | 0.705 | [0.055 0.295 0. 0.65 ] | 0.0356486 | 0.779398 | 0.815047 | [0.055 0.945] | 0.705 |
+| (0.65, 74) | 0.0614174 | 0.638583 | 0.7 | [0.05 0.3 0. 0.65] | 0.0417064 | 0.770794 | 0.8125 | [0.05 0.95] | 0.7 |
+| (0.65, 75) | 0.0690815 | 0.636919 | 0.706 | [0.056 0.294 0. 0.65 ] | 0.0382886 | 0.77727 | 0.815558 | [0.056 0.944] | 0.706 |
+| (0.65, 76) | 0.0663326 | 0.632667 | 0.699 | [0.049 0.301 0. 0.65 ] | 0.0417255 | 0.770267 | 0.811993 | [0.049 0.951] | 0.699 |
+| (0.65, 77) | 0.0329796 | 0.66402 | 0.697 | [0.047 0.303 0. 0.65 ] | 0.0208125 | 0.790167 | 0.810979 | [0.047 0.953] | 0.697 |
+| (0.65, 78) | 0.0305704 | 0.66243 | 0.693 | [0.043 0.307 0. 0.65 ] | 0.0199287 | 0.789032 | 0.808961 | [0.043 0.957] | 0.693 |
+| (0.65, 79) | 0.0591355 | 0.651865 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.033893 | 0.784232 | 0.818125 | [0.061 0.939] | 0.711 |
+| (0.65, 80) | 0.0828419 | 0.621158 | 0.704 | [0.055 0.295 0.001 0.649] | 0.0513442 | 0.762959 | 0.814304 | [0.056 0.944] | 0.704 |
+| (0.65, 81) | 0.0405789 | 0.653421 | 0.694 | [0.044 0.306 0. 0.65 ] | 0.0252821 | 0.784182 | 0.809465 | [0.044 0.956] | 0.694 |
+| (0.65, 82) | 0.0552317 | 0.631768 | 0.687 | [0.037 0.313 0. 0.65 ] | 0.0343555 | 0.771596 | 0.805952 | [0.037 0.963] | 0.687 |
+| (0.65, 83) | 0.0558149 | 0.656185 | 0.712 | [0.062 0.288 0. 0.65 ] | 0.032602 | 0.786038 | 0.81864 | [0.062 0.938] | 0.712 |
+| (0.65, 84) | 0.0477823 | 0.663218 | 0.711 | [0.061 0.289 0. 0.65 ] | 0.025912 | 0.792213 | 0.818125 | [0.061 0.939] | 0.711 |
+| (0.65, 85) | 0.0763267 | 0.624673 | 0.701 | [0.052 0.298 0.001 0.649] | 0.0468193 | 0.765955 | 0.812774 | [0.053 0.947] | 0.701 |
+| (0.65, 86) | 0.0360446 | 0.657955 | 0.694 | [0.044 0.306 0. 0.65 ] | 0.0189634 | 0.790501 | 0.809465 | [0.044 0.956] | 0.694 |
+| (0.65, 87) | 0.0756674 | 0.622333 | 0.698 | [0.05 0.3 0.002 0.648] | 0.0459044 | 0.765109 | 0.811014 | [0.052 0.948] | 0.698 |
+| (0.65, 88) | 0.071613 | 0.627387 | 0.699 | [0.051 0.299 0.002 0.648] | 0.0411009 | 0.770421 | 0.811522 | [0.053 0.947] | 0.699 |
+| (0.65, 89) | 0.0559207 | 0.652079 | 0.708 | [0.059 0.291 0.001 0.649] | 0.0337589 | 0.782593 | 0.816352 | [0.06 0.94] | 0.708 |
+| (0.65, 90) | 0.0897853 | 0.600215 | 0.69 | [0.043 0.307 0.003 0.647] | 0.0598717 | 0.746861 | 0.806733 | [0.046 0.954] | 0.69 |
+| (0.65, 91) | 0.0652016 | 0.625798 | 0.691 | [0.041 0.309 0. 0.65 ] | 0.0389561 | 0.768999 | 0.807955 | [0.041 0.959] | 0.691 |
+| (0.65, 92) | 0.0780821 | 0.632918 | 0.711 | [0.062 0.288 0.001 0.649] | 0.0459551 | 0.77194 | 0.817895 | [0.063 0.937] | 0.711 |
+| (0.65, 93) | 0.0369541 | 0.667046 | 0.704 | [0.054 0.296 0. 0.65 ] | 0.0196589 | 0.794877 | 0.814536 | [0.054 0.946] | 0.704 |
+| (0.65, 94) | 0.0868486 | 0.613151 | 0.7 | [0.05 0.3 0. 0.65] | 0.052447 | 0.760053 | 0.8125 | [0.05 0.95] | 0.7 |
+| (0.65, 95) | 0.0358453 | 0.659155 | 0.695 | [0.046 0.304 0.001 0.649] | 0.0240181 | 0.785714 | 0.809732 | [0.047 0.953] | 0.695 |
+| (0.65, 96) | 0.0577789 | 0.650221 | 0.708 | [0.058 0.292 0. 0.65 ] | 0.0355455 | 0.781037 | 0.816583 | [0.058 0.942] | 0.708 |
+| (0.65, 97) | 0.0486151 | 0.645385 | 0.694 | [0.045 0.305 0.001 0.649] | 0.0316332 | 0.777594 | 0.809227 | [0.046 0.954] | 0.694 |
+| (0.65, 98) | 0.04014 | 0.65786 | 0.698 | [0.048 0.302 0. 0.65 ] | 0.0231171 | 0.788369 | 0.811486 | [0.048 0.952] | 0.698 |
+| (0.65, 99) | 0.0660544 | 0.650946 | 0.717 | [0.069 0.281 0.002 0.648] | 0.0386239 | 0.782149 | 0.820773 | [0.071 0.929] | 0.717 |
+| (0.7, 0) | 0.0257237 | 0.713276 | 0.739 | [0.039 0.261 0. 0.7 ] | 0.0158348 | 0.827031 | 0.842866 | [0.039 0.961] | 0.739 |
+| (0.7, 1) | 0.0460058 | 0.694994 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.0269198 | 0.816962 | 0.843882 | [0.041 0.959] | 0.741 |
+| (0.7, 2) | 0.042295 | 0.707705 | 0.75 | [0.051 0.249 0.001 0.699] | 0.0283674 | 0.819934 | 0.848301 | [0.052 0.948] | 0.75 |
+| (0.7, 3) | 0.0288274 | 0.716173 | 0.745 | [0.048 0.252 0.003 0.697] | 0.0176749 | 0.827686 | 0.845361 | [0.051 0.949] | 0.745 |
+| (0.7, 4) | 0.018103 | 0.731897 | 0.75 | [0.051 0.249 0.001 0.699] | 0.0117766 | 0.836524 | 0.848301 | [0.052 0.948] | 0.75 |
+| (0.7, 5) | 0.0264212 | 0.724579 | 0.751 | [0.051 0.249 0. 0.7 ] | 0.0160402 | 0.832959 | 0.848999 | [0.051 0.949] | 0.751 |
+| (0.7, 6) | 0.0509385 | 0.697061 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0314891 | 0.815784 | 0.847273 | [0.05 0.95] | 0.748 |
+| (0.7, 7) | 0.0454696 | 0.71053 | 0.756 | [0.056 0.244 0. 0.7 ] | 0.0292168 | 0.822365 | 0.851582 | [0.056 0.944] | 0.756 |
+| (0.7, 8) | 0.0431997 | 0.7028 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0222566 | 0.824176 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 9) | 0.0663396 | 0.67366 | 0.74 | [0.04 0.26 0. 0.7 ] | 0.0383664 | 0.805007 | 0.843373 | [0.04 0.96] | 0.74 |
+| (0.7, 10) | 0.0436339 | 0.702366 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.021438 | 0.824995 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 11) | 0.0669556 | 0.677044 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0409375 | 0.804286 | 0.845224 | [0.046 0.954] | 0.744 |
+| (0.7, 12) | 0.0236731 | 0.732327 | 0.756 | [0.056 0.244 0. 0.7 ] | 0.0114491 | 0.840132 | 0.851582 | [0.056 0.944] | 0.756 |
+| (0.7, 13) | 0.0543776 | 0.695622 | 0.75 | [0.051 0.249 0.001 0.699] | 0.0311781 | 0.817123 | 0.848301 | [0.052 0.948] | 0.75 |
+| (0.7, 14) | 0.0219647 | 0.722035 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0127436 | 0.83248 | 0.845224 | [0.046 0.954] | 0.744 |
+| (0.7, 15) | 0.04204 | 0.70096 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0265375 | 0.818363 | 0.8449 | [0.043 0.957] | 0.743 |
+| (0.7, 16) | 0.0428157 | 0.693184 | 0.736 | [0.037 0.263 0.001 0.699] | 0.0243824 | 0.816773 | 0.841155 | [0.038 0.962] | 0.736 |
+| (0.7, 17) | 0.0241334 | 0.712867 | 0.737 | [0.038 0.262 0.001 0.699] | 0.0143424 | 0.827319 | 0.841662 | [0.039 0.961] | 0.737 |
+| (0.7, 18) | 0.0369606 | 0.702039 | 0.739 | [0.039 0.261 0. 0.7 ] | 0.0251595 | 0.817706 | 0.842866 | [0.039 0.961] | 0.739 |
+| (0.7, 19) | 0.0357608 | 0.708239 | 0.744 | [0.046 0.254 0.002 0.698] | 0.0229315 | 0.822105 | 0.845036 | [0.048 0.952] | 0.744 |
+| (0.7, 20) | 0.0544485 | 0.688552 | 0.743 | [0.044 0.256 0.001 0.699] | 0.0318225 | 0.81289 | 0.844713 | [0.045 0.955] | 0.743 |
+| (0.7, 21) | 0.0619287 | 0.696071 | 0.758 | [0.058 0.242 0. 0.7 ] | 0.0351504 | 0.817468 | 0.852619 | [0.058 0.942] | 0.758 |
+| (0.7, 22) | 0.04091 | 0.69509 | 0.736 | [0.037 0.263 0.001 0.699] | 0.0261895 | 0.814966 | 0.841155 | [0.038 0.962] | 0.736 |
+| (0.7, 23) | 0.0581635 | 0.696836 | 0.755 | [0.055 0.245 0. 0.7 ] | 0.0322321 | 0.818832 | 0.851064 | [0.055 0.945] | 0.755 |
+| (0.7, 24) | 0.031157 | 0.713843 | 0.745 | [0.046 0.254 0.001 0.699] | 0.020101 | 0.825634 | 0.845735 | [0.047 0.953] | 0.745 |
+| (0.7, 25) | 0.0699032 | 0.679097 | 0.749 | [0.049 0.251 0. 0.7 ] | 0.0441162 | 0.803855 | 0.847971 | [0.049 0.951] | 0.749 |
+| (0.7, 26) | 0.0365515 | 0.704449 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.02384 | 0.820042 | 0.843882 | [0.041 0.959] | 0.741 |
+| (0.7, 27) | 0.051094 | 0.686906 | 0.738 | [0.04 0.26 0.002 0.698] | 0.0296508 | 0.812327 | 0.841978 | [0.042 0.958] | 0.738 |
+| (0.7, 28) | 0.0580445 | 0.695955 | 0.754 | [0.054 0.246 0. 0.7 ] | 0.0329645 | 0.817582 | 0.850547 | [0.054 0.946] | 0.754 |
+| (0.7, 29) | 0.0581874 | 0.687813 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0329015 | 0.813531 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 30) | 0.0596123 | 0.683388 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0371841 | 0.807716 | 0.8449 | [0.043 0.957] | 0.743 |
+| (0.7, 31) | 0.0457276 | 0.695272 | 0.741 | [0.043 0.257 0.002 0.698] | 0.0284045 | 0.8151 | 0.843505 | [0.045 0.955] | 0.741 |
+| (0.7, 32) | 0.0302288 | 0.712771 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0195378 | 0.825363 | 0.8449 | [0.043 0.957] | 0.743 |
+| (0.7, 33) | 0.0102201 | 0.73978 | 0.75 | [0.05 0.25 0. 0.7 ] | 0.00445961 | 0.844025 | 0.848485 | [0.05 0.95] | 0.75 |
+| (0.7, 34) | 0.0382468 | 0.706753 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0235733 | 0.822348 | 0.845921 | [0.045 0.955] | 0.745 |
+| (0.7, 35) | 0.0399682 | 0.706032 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0243874 | 0.822045 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 36) | 0.0552478 | 0.685752 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.0321503 | 0.811732 | 0.843882 | [0.041 0.959] | 0.741 |
+| (0.7, 37) | 0.0626886 | 0.683311 | 0.746 | [0.047 0.253 0.001 0.699] | 0.0357774 | 0.81047 | 0.846247 | [0.048 0.952] | 0.746 |
+| (0.7, 38) | 0.0941167 | 0.653883 | 0.748 | [0.048 0.252 0. 0.7 ] | 0.0630955 | 0.784362 | 0.847458 | [0.048 0.952] | 0.748 |
+| (0.7, 39) | 0.0540688 | 0.684931 | 0.739 | [0.039 0.261 0. 0.7 ] | 0.0299878 | 0.812878 | 0.842866 | [0.039 0.961] | 0.739 |
+| (0.7, 40) | 0.0768883 | 0.673112 | 0.75 | [0.05 0.25 0. 0.7 ] | 0.0440604 | 0.804424 | 0.848485 | [0.05 0.95] | 0.75 |
+| (0.7, 41) | 0.0345316 | 0.705468 | 0.74 | [0.042 0.258 0.002 0.698] | 0.0216253 | 0.82137 | 0.842995 | [0.044 0.956] | 0.74 |
+| (0.7, 42) | 0.0386848 | 0.702315 | 0.741 | [0.042 0.258 0.001 0.699] | 0.0241046 | 0.819589 | 0.843693 | [0.043 0.957] | 0.741 |
+| (0.7, 43) | 0.0599738 | 0.673026 | 0.733 | [0.034 0.266 0.001 0.699] | 0.0351087 | 0.804531 | 0.83964 | [0.035 0.965] | 0.733 |
+| (0.7, 44) | 0.0584178 | 0.686582 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0322826 | 0.813639 | 0.845921 | [0.045 0.955] | 0.745 |
+| (0.7, 45) | 0.0447354 | 0.700265 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0272621 | 0.818659 | 0.845921 | [0.045 0.955] | 0.745 |
+| (0.7, 46) | 0.0340733 | 0.718927 | 0.753 | [0.053 0.247 0. 0.7 ] | 0.0217421 | 0.828288 | 0.85003 | [0.053 0.947] | 0.753 |
+| (0.7, 47) | 0.0335992 | 0.719401 | 0.753 | [0.053 0.247 0. 0.7 ] | 0.020345 | 0.829685 | 0.85003 | [0.053 0.947] | 0.753 |
+| (0.7, 48) | 0.0205774 | 0.714423 | 0.735 | [0.036 0.264 0.001 0.699] | 0.0129594 | 0.82769 | 0.840649 | [0.037 0.963] | 0.735 |
+| (0.7, 49) | 0.0587974 | 0.686203 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0339661 | 0.811955 | 0.845921 | [0.045 0.955] | 0.745 |
+| (0.7, 50) | 0.0351737 | 0.719826 | 0.755 | [0.056 0.244 0.001 0.699] | 0.0199776 | 0.830905 | 0.850883 | [0.057 0.943] | 0.755 |
+| (0.7, 51) | 0.0267817 | 0.728218 | 0.755 | [0.055 0.245 0. 0.7 ] | 0.0161224 | 0.834941 | 0.851064 | [0.055 0.945] | 0.755 |
+| (0.7, 52) | 0.0472808 | 0.698719 | 0.746 | [0.047 0.253 0.001 0.699] | 0.0257035 | 0.820544 | 0.846247 | [0.048 0.952] | 0.746 |
+| (0.7, 53) | 0.0651052 | 0.670895 | 0.736 | [0.036 0.264 0. 0.7 ] | 0.0414622 | 0.799884 | 0.841346 | [0.036 0.964] | 0.736 |
+| (0.7, 54) | 0.0266103 | 0.71839 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0163738 | 0.829548 | 0.845921 | [0.045 0.955] | 0.745 |
+| (0.7, 55) | 0.0556272 | 0.685373 | 0.741 | [0.042 0.258 0.001 0.699] | 0.0349463 | 0.808747 | 0.843693 | [0.043 0.957] | 0.741 |
+| (0.7, 56) | 0.0522764 | 0.689724 | 0.742 | [0.044 0.256 0.002 0.698] | 0.0302049 | 0.81381 | 0.844015 | [0.046 0.954] | 0.742 |
+| (0.7, 57) | 0.0489347 | 0.701065 | 0.75 | [0.05 0.25 0. 0.7 ] | 0.0319756 | 0.816509 | 0.848485 | [0.05 0.95] | 0.75 |
+| (0.7, 58) | 0.0572132 | 0.690787 | 0.748 | [0.048 0.252 0. 0.7 ] | 0.0348496 | 0.812608 | 0.847458 | [0.048 0.952] | 0.748 |
+| (0.7, 59) | 0.0616845 | 0.687316 | 0.749 | [0.052 0.248 0.003 0.697] | 0.0364798 | 0.810937 | 0.847416 | [0.055 0.945] | 0.749 |
+| (0.7, 60) | 0.0266481 | 0.719352 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0112287 | 0.835204 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 61) | 0.0431471 | 0.703853 | 0.747 | [0.047 0.253 0. 0.7 ] | 0.0277927 | 0.819152 | 0.846945 | [0.047 0.953] | 0.747 |
+| (0.7, 62) | 0.058813 | 0.695187 | 0.754 | [0.055 0.245 0.001 0.699] | 0.0385337 | 0.811831 | 0.850365 | [0.056 0.944] | 0.754 |
+| (0.7, 63) | 0.044278 | 0.703722 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0263027 | 0.82097 | 0.847273 | [0.05 0.95] | 0.748 |
+| (0.7, 64) | 0.0824936 | 0.657506 | 0.74 | [0.041 0.259 0.001 0.699] | 0.0498315 | 0.793353 | 0.843185 | [0.042 0.958] | 0.74 |
+| (0.7, 65) | 0.0487397 | 0.69226 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.0273824 | 0.8165 | 0.843882 | [0.041 0.959] | 0.741 |
+| (0.7, 66) | 0.0456017 | 0.700398 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0291693 | 0.817264 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 67) | 0.0599507 | 0.682049 | 0.742 | [0.042 0.258 0. 0.7 ] | 0.0336685 | 0.810722 | 0.844391 | [0.042 0.958] | 0.742 |
+| (0.7, 68) | 0.0606527 | 0.686347 | 0.747 | [0.049 0.251 0.002 0.698] | 0.0362096 | 0.810364 | 0.846574 | [0.051 0.949] | 0.747 |
+| (0.7, 69) | 0.0634868 | 0.670513 | 0.734 | [0.034 0.266 0. 0.7 ] | 0.0382688 | 0.802067 | 0.840336 | [0.034 0.966] | 0.734 |
+| (0.7, 70) | 0.0314017 | 0.715598 | 0.747 | [0.049 0.251 0.002 0.698] | 0.0198875 | 0.826686 | 0.846574 | [0.051 0.949] | 0.747 |
+| (0.7, 71) | 0.0570147 | 0.693985 | 0.751 | [0.051 0.249 0. 0.7 ] | 0.0312233 | 0.817776 | 0.848999 | [0.051 0.949] | 0.751 |
+| (0.7, 72) | 0.0439817 | 0.690018 | 0.734 | [0.035 0.265 0.001 0.699] | 0.0238598 | 0.816284 | 0.840144 | [0.036 0.964] | 0.734 |
+| (0.7, 73) | 0.0455512 | 0.698449 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0244858 | 0.820738 | 0.845224 | [0.046 0.954] | 0.744 |
+| (0.7, 74) | 0.0488415 | 0.697158 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0275018 | 0.818931 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 75) | 0.040398 | 0.701602 | 0.742 | [0.042 0.258 0. 0.7 ] | 0.025014 | 0.819377 | 0.844391 | [0.042 0.958] | 0.742 |
+| (0.7, 76) | 0.0338518 | 0.711148 | 0.745 | [0.045 0.255 0. 0.7 ] | 0.0211698 | 0.824752 | 0.845921 | [0.045 0.955] | 0.745 |
+| (0.7, 77) | 0.0635197 | 0.67848 | 0.742 | [0.042 0.258 0. 0.7 ] | 0.0368786 | 0.807512 | 0.844391 | [0.042 0.958] | 0.742 |
+| (0.7, 78) | 0.0168386 | 0.730161 | 0.747 | [0.048 0.252 0.001 0.699] | 0.00937337 | 0.837386 | 0.84676 | [0.049 0.951] | 0.747 |
+| (0.7, 79) | 0.0418986 | 0.714101 | 0.756 | [0.056 0.244 0. 0.7 ] | 0.025139 | 0.826443 | 0.851582 | [0.056 0.944] | 0.756 |
+| (0.7, 80) | 0.037095 | 0.711905 | 0.749 | [0.049 0.251 0. 0.7 ] | 0.0236265 | 0.824344 | 0.847971 | [0.049 0.951] | 0.749 |
+| (0.7, 81) | 0.0355185 | 0.710481 | 0.746 | [0.047 0.253 0.001 0.699] | 0.023162 | 0.823085 | 0.846247 | [0.048 0.952] | 0.746 |
+| (0.7, 82) | 0.051202 | 0.689798 | 0.741 | [0.043 0.257 0.002 0.698] | 0.0302617 | 0.813243 | 0.843505 | [0.045 0.955] | 0.741 |
+| (0.7, 83) | 0.0127804 | 0.72822 | 0.741 | [0.041 0.259 0. 0.7 ] | 0.00508636 | 0.838795 | 0.843882 | [0.041 0.959] | 0.741 |
+| (0.7, 84) | 0.0571513 | 0.682849 | 0.74 | [0.042 0.258 0.002 0.698] | 0.0317753 | 0.81122 | 0.842995 | [0.044 0.956] | 0.74 |
+| (0.7, 85) | 0.03966 | 0.70434 | 0.744 | [0.044 0.256 0. 0.7 ] | 0.0248263 | 0.820584 | 0.845411 | [0.044 0.956] | 0.744 |
+| (0.7, 86) | 0.0395805 | 0.70942 | 0.749 | [0.05 0.25 0.001 0.699] | 0.0253555 | 0.822431 | 0.847787 | [0.051 0.949] | 0.749 |
+| (0.7, 87) | 0.0439101 | 0.70109 | 0.745 | [0.046 0.254 0.001 0.699] | 0.0245246 | 0.82121 | 0.845735 | [0.047 0.953] | 0.745 |
+| (0.7, 88) | 0.0251373 | 0.720863 | 0.746 | [0.046 0.254 0. 0.7 ] | 0.0166981 | 0.829735 | 0.846433 | [0.046 0.954] | 0.746 |
+| (0.7, 89) | 0.0427015 | 0.700298 | 0.743 | [0.043 0.257 0. 0.7 ] | 0.0273584 | 0.817542 | 0.8449 | [0.043 0.957] | 0.743 |
+| (0.7, 90) | 0.0521871 | 0.687813 | 0.74 | [0.04 0.26 0. 0.7 ] | 0.0297551 | 0.813618 | 0.843373 | [0.04 0.96] | 0.74 |
+| (0.7, 91) | 0.0432122 | 0.695788 | 0.739 | [0.04 0.26 0.001 0.699] | 0.0262949 | 0.816381 | 0.842676 | [0.041 0.959] | 0.739 |
+| (0.7, 92) | 0.0378549 | 0.706145 | 0.744 | [0.045 0.255 0.001 0.699] | 0.0179952 | 0.827228 | 0.845224 | [0.046 0.954] | 0.744 |
+| (0.7, 93) | 0.0545061 | 0.693494 | 0.748 | [0.048 0.252 0. 0.7 ] | 0.0338916 | 0.813566 | 0.847458 | [0.048 0.952] | 0.748 |
+| (0.7, 94) | 0.0669098 | 0.67309 | 0.74 | [0.04 0.26 0. 0.7 ] | 0.0398733 | 0.8035 | 0.843373 | [0.04 0.96] | 0.74 |
+| (0.7, 95) | 0.0615466 | 0.686453 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0419311 | 0.805342 | 0.847273 | [0.05 0.95] | 0.748 |
+| (0.7, 96) | 0.0643432 | 0.684657 | 0.749 | [0.049 0.251 0. 0.7 ] | 0.0391777 | 0.808793 | 0.847971 | [0.049 0.951] | 0.749 |
+| (0.7, 97) | 0.0318799 | 0.69612 | 0.728 | [0.03 0.27 0.002 0.698] | 0.0182705 | 0.81866 | 0.83693 | [0.032 0.968] | 0.728 |
+| (0.7, 98) | 0.0286473 | 0.719353 | 0.748 | [0.049 0.251 0.001 0.699] | 0.0153222 | 0.831951 | 0.847273 | [0.05 0.95] | 0.748 |
+| (0.7, 99) | 0.048621 | 0.683379 | 0.732 | [0.032 0.268 0. 0.7 ] | 0.0314276 | 0.807901 | 0.839329 | [0.032 0.968] | 0.732 |
+| (0.75, 0) | 0.0290489 | 0.763951 | 0.793 | [0.043 0.207 0. 0.75 ] | 0.0188064 | 0.859928 | 0.878735 | [0.043 0.957] | 0.793 |
+| (0.75, 1) | 0.0213086 | 0.783691 | 0.805 | [0.055 0.195 0. 0.75 ] | 0.0131107 | 0.871845 | 0.884956 | [0.055 0.945] | 0.805 |
+| (0.75, 2) | 0.0258045 | 0.769195 | 0.795 | [0.046 0.204 0.001 0.749] | 0.0152213 | 0.864403 | 0.879624 | [0.047 0.953] | 0.795 |
+| (0.75, 3) | 0.0499394 | 0.737061 | 0.787 | [0.037 0.213 0. 0.75 ] | 0.0290134 | 0.846643 | 0.875657 | [0.037 0.963] | 0.787 |
+| (0.75, 4) | 0.0376303 | 0.74437 | 0.782 | [0.032 0.218 0. 0.75 ] | 0.0197061 | 0.853402 | 0.873108 | [0.032 0.968] | 0.782 |
+| (0.75, 5) | 0.0469517 | 0.733048 | 0.78 | [0.03 0.22 0. 0.75] | 0.0263483 | 0.845745 | 0.872093 | [0.03 0.97] | 0.78 |
+| (0.75, 6) | 0.0370853 | 0.757915 | 0.795 | [0.046 0.204 0.001 0.749] | 0.0226526 | 0.856972 | 0.879624 | [0.047 0.953] | 0.795 |
+| (0.75, 7) | 0.0310667 | 0.756933 | 0.788 | [0.038 0.212 0. 0.75 ] | 0.0161298 | 0.860038 | 0.876168 | [0.038 0.962] | 0.788 |
+| (0.75, 8) | 0.0332692 | 0.761731 | 0.795 | [0.047 0.203 0.002 0.748] | 0.0202977 | 0.859185 | 0.879483 | [0.049 0.951] | 0.795 |
+| (0.75, 9) | 0.0136944 | 0.777306 | 0.791 | [0.041 0.209 0. 0.75 ] | 0.00761378 | 0.870092 | 0.877706 | [0.041 0.959] | 0.791 |
+| (0.75, 10) | 0.0441472 | 0.740853 | 0.785 | [0.036 0.214 0.001 0.749] | 0.0265147 | 0.847975 | 0.874489 | [0.037 0.963] | 0.785 |
+| (0.75, 11) | 0.00733119 | 0.775669 | 0.783 | [0.034 0.216 0.001 0.749] | 0.00279004 | 0.870679 | 0.873469 | [0.035 0.965] | 0.783 |
+| (0.75, 12) | 0.0121353 | 0.770865 | 0.783 | [0.035 0.215 0.002 0.748] | 0.00702411 | 0.866298 | 0.873322 | [0.037 0.963] | 0.783 |
+| (0.75, 13) | 0.0565286 | 0.731471 | 0.788 | [0.039 0.211 0.001 0.749] | 0.0321032 | 0.84392 | 0.876023 | [0.04 0.96] | 0.788 |
+| (0.75, 14) | 0.0152813 | 0.769719 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.00888373 | 0.865752 | 0.874636 | [0.035 0.965] | 0.785 |
+| (0.75, 15) | 0.0153936 | 0.772606 | 0.788 | [0.039 0.211 0.001 0.749] | 0.00762887 | 0.868395 | 0.876023 | [0.04 0.96] | 0.788 |
+| (0.75, 16) | 0.0119624 | 0.778038 | 0.79 | [0.042 0.208 0.002 0.748] | 0.00732564 | 0.869579 | 0.876905 | [0.044 0.956] | 0.79 |
+| (0.75, 17) | 0.0485998 | 0.7364 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.0266139 | 0.848022 | 0.874636 | [0.035 0.965] | 0.785 |
+| (0.75, 18) | 0.026567 | 0.751433 | 0.778 | [0.03 0.22 0.002 0.748] | 0.0149359 | 0.855844 | 0.87078 | [0.032 0.968] | 0.778 |
+| (0.75, 19) | 0.0434839 | 0.746516 | 0.79 | [0.04 0.21 0. 0.75] | 0.0227465 | 0.854447 | 0.877193 | [0.04 0.96] | 0.79 |
+| (0.75, 20) | 0.00358118 | 0.779419 | 0.783 | [0.035 0.215 0.002 0.748] | 0.00161839 | 0.871703 | 0.873322 | [0.037 0.963] | 0.783 |
+| (0.75, 21) | 0.0250464 | 0.757954 | 0.783 | [0.033 0.217 0. 0.75 ] | 0.0141667 | 0.85945 | 0.873617 | [0.033 0.967] | 0.783 |
+| (0.75, 22) | 0.00593084 | 0.793069 | 0.799 | [0.049 0.201 0. 0.75 ] | 0.00302196 | 0.878812 | 0.881834 | [0.049 0.951] | 0.799 |
+| (0.75, 23) | 0.0645649 | 0.724435 | 0.789 | [0.041 0.209 0.002 0.748] | 0.0377325 | 0.838659 | 0.876391 | [0.043 0.957] | 0.789 |
+| (0.75, 24) | 0.0404161 | 0.745584 | 0.786 | [0.036 0.214 0. 0.75 ] | 0.022775 | 0.852371 | 0.875146 | [0.036 0.964] | 0.786 |
+| (0.75, 25) | 0.0593057 | 0.727694 | 0.787 | [0.038 0.212 0.001 0.749] | 0.0333993 | 0.842112 | 0.875511 | [0.039 0.961] | 0.787 |
+| (0.75, 26) | 0.0611953 | 0.737805 | 0.799 | [0.049 0.201 0. 0.75 ] | 0.0339211 | 0.847913 | 0.881834 | [0.049 0.951] | 0.799 |
+| (0.75, 27) | 0.0335309 | 0.764469 | 0.798 | [0.049 0.201 0.001 0.749] | 0.0187754 | 0.862401 | 0.881176 | [0.05 0.95] | 0.798 |
+| (0.75, 28) | 0.0467563 | 0.734244 | 0.781 | [0.032 0.218 0.001 0.749] | 0.0259504 | 0.846502 | 0.872452 | [0.033 0.967] | 0.781 |
+| (0.75, 29) | 0.0367851 | 0.757215 | 0.794 | [0.045 0.205 0.001 0.749] | 0.0220216 | 0.857086 | 0.879108 | [0.046 0.954] | 0.794 |
+| (0.75, 30) | 0.0561704 | 0.73983 | 0.796 | [0.047 0.203 0.001 0.749] | 0.0301069 | 0.850034 | 0.880141 | [0.048 0.952] | 0.796 |
+| (0.75, 31) | 0.036463 | 0.759537 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0194914 | 0.86079 | 0.880282 | [0.046 0.954] | 0.796 |
+| (0.75, 32) | 0.0115699 | 0.76443 | 0.776 | [0.027 0.223 0.001 0.749] | 0.00582438 | 0.864094 | 0.869919 | [0.028 0.972] | 0.776 |
+| (0.75, 33) | 0.0385213 | 0.755479 | 0.794 | [0.044 0.206 0. 0.75 ] | 0.0240675 | 0.855182 | 0.87925 | [0.044 0.956] | 0.794 |
+| (0.75, 34) | 0.0279748 | 0.762025 | 0.79 | [0.04 0.21 0. 0.75] | 0.0177323 | 0.859461 | 0.877193 | [0.04 0.96] | 0.79 |
+| (0.75, 35) | 0.0437401 | 0.73526 | 0.779 | [0.031 0.219 0.002 0.748] | 0.0250926 | 0.846194 | 0.871287 | [0.033 0.967] | 0.779 |
+| (0.75, 36) | 0.024253 | 0.758747 | 0.783 | [0.034 0.216 0.001 0.749] | 0.0142197 | 0.85925 | 0.873469 | [0.035 0.965] | 0.783 |
+| (0.75, 37) | 0.0511354 | 0.726865 | 0.778 | [0.029 0.221 0.001 0.749] | 0.0319916 | 0.838939 | 0.87093 | [0.03 0.97] | 0.778 |
+| (0.75, 38) | 0.0391688 | 0.741831 | 0.781 | [0.032 0.218 0.001 0.749] | 0.0227259 | 0.849726 | 0.872452 | [0.033 0.967] | 0.781 |
+| (0.75, 39) | 0.049827 | 0.737173 | 0.787 | [0.038 0.212 0.001 0.749] | 0.0270195 | 0.848492 | 0.875511 | [0.039 0.961] | 0.787 |
+| (0.75, 40) | 0.0114272 | 0.785573 | 0.797 | [0.047 0.203 0. 0.75 ] | 0.00614797 | 0.874651 | 0.880799 | [0.047 0.953] | 0.797 |
+| (0.75, 41) | 0.0306715 | 0.762329 | 0.793 | [0.044 0.206 0.001 0.749] | 0.0183691 | 0.860223 | 0.878592 | [0.045 0.955] | 0.793 |
+| (0.75, 42) | 0.0395072 | 0.747493 | 0.787 | [0.039 0.211 0.002 0.748] | 0.0247259 | 0.85064 | 0.875366 | [0.041 0.959] | 0.787 |
+| (0.75, 43) | 0.0434636 | 0.749536 | 0.793 | [0.044 0.206 0.001 0.749] | 0.0248327 | 0.85376 | 0.878592 | [0.045 0.955] | 0.793 |
+| (0.75, 44) | 0.0360129 | 0.744987 | 0.781 | [0.031 0.219 0. 0.75 ] | 0.0199793 | 0.852621 | 0.8726 | [0.031 0.969] | 0.781 |
+| (0.75, 45) | 0.0280378 | 0.755962 | 0.784 | [0.035 0.215 0.001 0.749] | 0.0137074 | 0.860272 | 0.873979 | [0.036 0.964] | 0.784 |
+| (0.75, 46) | 0.0215758 | 0.774424 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0126768 | 0.867605 | 0.880282 | [0.046 0.954] | 0.796 |
+| (0.75, 47) | 0.0523155 | 0.739684 | 0.792 | [0.042 0.208 0. 0.75 ] | 0.0300079 | 0.848212 | 0.87822 | [0.042 0.958] | 0.792 |
+| (0.75, 48) | 0.0602019 | 0.728798 | 0.789 | [0.04 0.21 0.001 0.749] | 0.0383976 | 0.838138 | 0.876536 | [0.041 0.959] | 0.789 |
+| (0.75, 49) | 0.047031 | 0.739969 | 0.787 | [0.038 0.212 0.001 0.749] | 0.0290799 | 0.846431 | 0.875511 | [0.039 0.961] | 0.787 |
+| (0.75, 50) | 0.0273783 | 0.768622 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0135753 | 0.866706 | 0.880282 | [0.046 0.954] | 0.796 |
+| (0.75, 51) | 0.02684 | 0.76216 | 0.789 | [0.041 0.209 0.002 0.748] | 0.0131259 | 0.863265 | 0.876391 | [0.043 0.957] | 0.789 |
+| (0.75, 52) | 0.0400329 | 0.747967 | 0.788 | [0.039 0.211 0.001 0.749] | 0.0219925 | 0.854031 | 0.876023 | [0.04 0.96] | 0.788 |
+| (0.75, 53) | 0.0356267 | 0.753373 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.0208528 | 0.855828 | 0.87668 | [0.039 0.961] | 0.789 |
+| (0.75, 54) | 0.0441881 | 0.744812 | 0.789 | [0.04 0.21 0.001 0.749] | 0.0265353 | 0.850001 | 0.876536 | [0.041 0.959] | 0.789 |
+| (0.75, 55) | 0.0309762 | 0.749024 | 0.78 | [0.031 0.219 0.001 0.749] | 0.0178195 | 0.854125 | 0.871944 | [0.032 0.968] | 0.78 |
+| (0.75, 56) | 0.0161385 | 0.772862 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.00984521 | 0.866835 | 0.87668 | [0.039 0.961] | 0.789 |
+| (0.75, 57) | 0.0170935 | 0.761907 | 0.779 | [0.03 0.22 0.001 0.749] | 0.00916119 | 0.862276 | 0.871437 | [0.031 0.969] | 0.779 |
+| (0.75, 58) | 0.0354674 | 0.749533 | 0.785 | [0.036 0.214 0.001 0.749] | 0.0220898 | 0.852399 | 0.874489 | [0.037 0.963] | 0.785 |
+| (0.75, 59) | 0.025201 | 0.760799 | 0.786 | [0.036 0.214 0. 0.75 ] | 0.0151774 | 0.859968 | 0.875146 | [0.036 0.964] | 0.786 |
+| (0.75, 60) | 0.0272636 | 0.755736 | 0.783 | [0.033 0.217 0. 0.75 ] | 0.0156835 | 0.857933 | 0.873617 | [0.033 0.967] | 0.783 |
+| (0.75, 61) | 0.0433661 | 0.750634 | 0.794 | [0.045 0.205 0.001 0.749] | 0.0228797 | 0.856228 | 0.879108 | [0.046 0.954] | 0.794 |
+| (0.75, 62) | 0.0538387 | 0.737161 | 0.791 | [0.041 0.209 0. 0.75 ] | 0.0292089 | 0.848497 | 0.877706 | [0.041 0.959] | 0.791 |
+| (0.75, 63) | 0.0224127 | 0.764587 | 0.787 | [0.037 0.213 0. 0.75 ] | 0.0128879 | 0.862769 | 0.875657 | [0.037 0.963] | 0.787 |
+| (0.75, 64) | 0.034333 | 0.754667 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.0213609 | 0.855319 | 0.87668 | [0.039 0.961] | 0.789 |
+| (0.75, 65) | 0.00924564 | 0.775754 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.00490077 | 0.869735 | 0.874636 | [0.035 0.965] | 0.785 |
+| (0.75, 66) | 0.00451873 | 0.786481 | 0.791 | [0.041 0.209 0. 0.75 ] | 0.00214582 | 0.87556 | 0.877706 | [0.041 0.959] | 0.791 |
+| (0.75, 67) | 0.0517501 | 0.74025 | 0.792 | [0.044 0.206 0.002 0.748] | 0.028609 | 0.849325 | 0.877934 | [0.046 0.954] | 0.792 |
+| (0.75, 68) | 0.0343641 | 0.754636 | 0.789 | [0.04 0.21 0.001 0.749] | 0.0192369 | 0.857299 | 0.876536 | [0.041 0.959] | 0.789 |
+| (0.75, 69) | 0.0344314 | 0.750569 | 0.785 | [0.035 0.215 0. 0.75 ] | 0.0205979 | 0.854038 | 0.874636 | [0.035 0.965] | 0.785 |
+| (0.75, 70) | 0.0261044 | 0.767896 | 0.794 | [0.045 0.205 0.001 0.749] | 0.0139256 | 0.865182 | 0.879108 | [0.046 0.954] | 0.794 |
+| (0.75, 71) | 0.0363507 | 0.753649 | 0.79 | [0.04 0.21 0. 0.75] | 0.0210632 | 0.85613 | 0.877193 | [0.04 0.96] | 0.79 |
+| (0.75, 72) | 0.0405785 | 0.741422 | 0.782 | [0.035 0.215 0.003 0.747] | 0.0217776 | 0.850886 | 0.872664 | [0.038 0.962] | 0.782 |
+| (0.75, 73) | 0.0170575 | 0.767942 | 0.785 | [0.036 0.214 0.001 0.749] | 0.00850885 | 0.86598 | 0.874489 | [0.037 0.963] | 0.785 |
+| (0.75, 74) | 0.0375071 | 0.750493 | 0.788 | [0.039 0.211 0.001 0.749] | 0.021137 | 0.854886 | 0.876023 | [0.04 0.96] | 0.788 |
+| (0.75, 75) | 0.0371426 | 0.748857 | 0.786 | [0.037 0.213 0.001 0.749] | 0.0210716 | 0.853928 | 0.875 | [0.038 0.962] | 0.786 |
+| (0.75, 76) | 0.0648981 | 0.724102 | 0.789 | [0.039 0.211 0. 0.75 ] | 0.0374199 | 0.83926 | 0.87668 | [0.039 0.961] | 0.789 |
+| (0.75, 77) | 0.0389063 | 0.741094 | 0.78 | [0.031 0.219 0.001 0.749] | 0.0219382 | 0.850006 | 0.871944 | [0.032 0.968] | 0.78 |
+| (0.75, 78) | 0.046141 | 0.745859 | 0.792 | [0.042 0.208 0. 0.75 ] | 0.0284288 | 0.849791 | 0.87822 | [0.042 0.958] | 0.792 |
+| (0.75, 79) | 0.0459182 | 0.746082 | 0.792 | [0.042 0.208 0. 0.75 ] | 0.0254524 | 0.852768 | 0.87822 | [0.042 0.958] | 0.792 |
+| (0.75, 80) | 0.0367849 | 0.750215 | 0.787 | [0.039 0.211 0.002 0.748] | 0.0190088 | 0.856357 | 0.875366 | [0.041 0.959] | 0.787 |
+| (0.75, 81) | 0.0214734 | 0.769527 | 0.791 | [0.042 0.208 0.001 0.749] | 0.0109792 | 0.866584 | 0.877563 | [0.043 0.957] | 0.791 |
+| (0.75, 82) | 0.0606138 | 0.723386 | 0.784 | [0.034 0.216 0. 0.75 ] | 0.0346787 | 0.839447 | 0.874126 | [0.034 0.966] | 0.784 |
+| (0.75, 83) | 0.0179434 | 0.767057 | 0.785 | [0.036 0.214 0.001 0.749] | 0.00789914 | 0.86659 | 0.874489 | [0.037 0.963] | 0.785 |
+| (0.75, 84) | 0.0356262 | 0.747374 | 0.783 | [0.035 0.215 0.002 0.748] | 0.0210658 | 0.852256 | 0.873322 | [0.037 0.963] | 0.783 |
+| (0.75, 85) | 0.0263657 | 0.756634 | 0.783 | [0.034 0.216 0.001 0.749] | 0.0141479 | 0.859321 | 0.873469 | [0.035 0.965] | 0.783 |
+| (0.75, 86) | 0.0293021 | 0.743698 | 0.773 | [0.024 0.226 0.001 0.749] | 0.017352 | 0.851054 | 0.868406 | [0.025 0.975] | 0.773 |
+| (0.75, 87) | 0.026603 | 0.759397 | 0.786 | [0.036 0.214 0. 0.75 ] | 0.016022 | 0.859124 | 0.875146 | [0.036 0.964] | 0.786 |
+| (0.75, 88) | 0.0406937 | 0.747306 | 0.788 | [0.04 0.21 0.002 0.748] | 0.0228616 | 0.853017 | 0.875878 | [0.042 0.958] | 0.788 |
+| (0.75, 89) | 0.0458613 | 0.732139 | 0.778 | [0.028 0.222 0. 0.75 ] | 0.0270263 | 0.844054 | 0.87108 | [0.028 0.972] | 0.778 |
+| (0.75, 90) | 0.0341579 | 0.760842 | 0.795 | [0.045 0.205 0. 0.75 ] | 0.0208155 | 0.85895 | 0.879765 | [0.045 0.955] | 0.795 |
+| (0.75, 91) | 0.038191 | 0.760809 | 0.799 | [0.05 0.2 0.001 0.749] | 0.0213842 | 0.860311 | 0.881695 | [0.051 0.949] | 0.799 |
+| (0.75, 92) | 0.0372172 | 0.743783 | 0.781 | [0.031 0.219 0. 0.75 ] | 0.0198746 | 0.852726 | 0.8726 | [0.031 0.969] | 0.781 |
+| (0.75, 93) | 0.0567933 | 0.727207 | 0.784 | [0.036 0.214 0.002 0.748] | 0.0351011 | 0.838731 | 0.873832 | [0.038 0.962] | 0.784 |
+| (0.75, 94) | 0.0228502 | 0.76015 | 0.783 | [0.034 0.216 0.001 0.749] | 0.0115927 | 0.861877 | 0.873469 | [0.035 0.965] | 0.783 |
+| (0.75, 95) | 0.0450282 | 0.738972 | 0.784 | [0.034 0.216 0. 0.75 ] | 0.0242723 | 0.849854 | 0.874126 | [0.034 0.966] | 0.784 |
+| (0.75, 96) | 0.0540909 | 0.743909 | 0.798 | [0.048 0.202 0. 0.75 ] | 0.0295038 | 0.851812 | 0.881316 | [0.048 0.952] | 0.798 |
+| (0.75, 97) | 0.0563787 | 0.723621 | 0.78 | [0.03 0.22 0. 0.75] | 0.0350677 | 0.837025 | 0.872093 | [0.03 0.97] | 0.78 |
+| (0.75, 98) | 0.028261 | 0.766739 | 0.795 | [0.046 0.204 0.001 0.749] | 0.0140084 | 0.865616 | 0.879624 | [0.047 0.953] | 0.795 |
+| (0.75, 99) | 0.019607 | 0.776393 | 0.796 | [0.046 0.204 0. 0.75 ] | 0.0109948 | 0.869287 | 0.880282 | [0.046 0.954] | 0.796 |
+| (0.8, 0) | 0.0409423 | 0.793058 | 0.834 | [0.035 0.165 0.001 0.799] | 0.0217691 | 0.884127 | 0.905896 | [0.036 0.964] | 0.834 |
+| (0.8, 1) | 0.00912837 | 0.815872 | 0.825 | [0.026 0.174 0.001 0.799] | 0.0048623 | 0.896435 | 0.901297 | [0.027 0.973] | 0.825 |
+| (0.8, 2) | 0.0216766 | 0.806323 | 0.828 | [0.03 0.17 0.002 0.798] | 0.010707 | 0.892008 | 0.902715 | [0.032 0.968] | 0.828 |
+| (0.8, 3) | 0.00863246 | 0.816368 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.00504774 | 0.896361 | 0.901408 | [0.025 0.975] | 0.825 |
+| (0.8, 4) | 0.0276359 | 0.796364 | 0.824 | [0.025 0.175 0.001 0.799] | 0.0157953 | 0.884994 | 0.900789 | [0.026 0.974] | 0.824 |
+| (0.8, 5) | 0.00270277 | 0.815297 | 0.818 | [0.018 0.182 0. 0.8 ] | 0.00111215 | 0.896755 | 0.897868 | [0.018 0.982] | 0.818 |
+| (0.8, 6) | 0.0210912 | 0.800909 | 0.822 | [0.023 0.177 0.001 0.799] | 0.0116788 | 0.888096 | 0.899775 | [0.024 0.976] | 0.822 |
+| (0.8, 7) | 0.0458864 | 0.780114 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.0255575 | 0.876359 | 0.901917 | [0.026 0.974] | 0.826 |
+| (0.8, 8) | 0.0325411 | 0.799459 | 0.832 | [0.033 0.167 0.001 0.799] | 0.0179992 | 0.886871 | 0.90487 | [0.034 0.966] | 0.832 |
+| (0.8, 9) | 0.0374835 | 0.792517 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0210132 | 0.882942 | 0.903955 | [0.03 0.97] | 0.83 |
+| (0.8, 10) | 0.0330656 | 0.787934 | 0.821 | [0.022 0.178 0.001 0.799] | 0.0178779 | 0.88139 | 0.899268 | [0.023 0.977] | 0.821 |
+| (0.8, 11) | 0.005432 | 0.826568 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.00301292 | 0.901964 | 0.904977 | [0.032 0.968] | 0.832 |
+| (0.8, 12) | 0.00380289 | 0.822197 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.00202778 | 0.899889 | 0.901917 | [0.026 0.974] | 0.826 |
+| (0.8, 13) | 0.00720171 | 0.815798 | 0.823 | [0.023 0.177 0. 0.8 ] | 0.00305894 | 0.897335 | 0.900394 | [0.023 0.977] | 0.823 |
+| (0.8, 14) | 0.0172814 | 0.807719 | 0.825 | [0.027 0.173 0.002 0.798] | 0.00767473 | 0.893511 | 0.901186 | [0.029 0.971] | 0.825 |
+| (0.8, 15) | 0.0120847 | 0.816915 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.00646782 | 0.896977 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 16) | 0.0263668 | 0.792633 | 0.819 | [0.019 0.181 0. 0.8 ] | 0.0145246 | 0.883847 | 0.898372 | [0.019 0.981] | 0.819 |
+| (0.8, 17) | 0.032205 | 0.797795 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0186486 | 0.885306 | 0.903955 | [0.03 0.97] | 0.83 |
+| (0.8, 18) | 0.0364903 | 0.78451 | 0.821 | [0.023 0.177 0.002 0.798] | 0.0199892 | 0.879166 | 0.899155 | [0.025 0.975] | 0.821 |
+| (0.8, 19) | 0.0445238 | 0.794476 | 0.839 | [0.039 0.161 0. 0.8 ] | 0.025349 | 0.883226 | 0.908575 | [0.039 0.961] | 0.839 |
+| (0.8, 20) | 0.0180783 | 0.798922 | 0.817 | [0.017 0.183 0. 0.8 ] | 0.0101047 | 0.887259 | 0.897364 | [0.017 0.983] | 0.817 |
+| (0.8, 21) | 0.0245807 | 0.804419 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0148101 | 0.888634 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 22) | 0.0244787 | 0.804521 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0137768 | 0.889668 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 23) | 0.0193507 | 0.802649 | 0.822 | [0.022 0.178 0. 0.8 ] | 0.0108588 | 0.889029 | 0.899888 | [0.022 0.978] | 0.822 |
+| (0.8, 24) | 0.0354281 | 0.792572 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.019193 | 0.883741 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 25) | 0.021107 | 0.810893 | 0.832 | [0.033 0.167 0.001 0.799] | 0.0122716 | 0.892598 | 0.90487 | [0.034 0.966] | 0.832 |
+| (0.8, 26) | 0.0189653 | 0.809035 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.0110574 | 0.891877 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 27) | 0.0427835 | 0.783216 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.0234921 | 0.878424 | 0.901917 | [0.026 0.974] | 0.826 |
+| (0.8, 28) | 0.0388648 | 0.795135 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.0206372 | 0.885365 | 0.906002 | [0.034 0.966] | 0.834 |
+| (0.8, 29) | 0.0484156 | 0.780584 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0269235 | 0.876412 | 0.903335 | [0.031 0.969] | 0.829 |
+| (0.8, 30) | 0.0189334 | 0.809067 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.00894551 | 0.893989 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 31) | 0.0348533 | 0.795147 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0206885 | 0.883266 | 0.903955 | [0.03 0.97] | 0.83 |
+| (0.8, 32) | 0.0298236 | 0.797176 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0154133 | 0.887012 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 33) | 0.0308446 | 0.790155 | 0.821 | [0.021 0.179 0. 0.8 ] | 0.0177848 | 0.881597 | 0.899382 | [0.021 0.979] | 0.821 |
+| (0.8, 34) | 0.0173788 | 0.815621 | 0.833 | [0.035 0.165 0.002 0.798] | 0.00986453 | 0.895411 | 0.905275 | [0.037 0.963] | 0.833 |
+| (0.8, 35) | 0.0274772 | 0.797523 | 0.825 | [0.027 0.173 0.002 0.798] | 0.016222 | 0.884964 | 0.901186 | [0.029 0.971] | 0.825 |
+| (0.8, 36) | 0.00890272 | 0.823097 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.0056062 | 0.899371 | 0.904977 | [0.032 0.968] | 0.832 |
+| (0.8, 37) | 0.0382181 | 0.786782 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0212881 | 0.88012 | 0.901408 | [0.025 0.975] | 0.825 |
+| (0.8, 38) | 0.0243138 | 0.802686 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0120784 | 0.890347 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 39) | 0.0384636 | 0.792536 | 0.831 | [0.032 0.168 0.001 0.799] | 0.0225441 | 0.881814 | 0.904358 | [0.033 0.967] | 0.831 |
+| (0.8, 40) | 0.0253619 | 0.801638 | 0.827 | [0.028 0.172 0.001 0.799] | 0.0150565 | 0.887259 | 0.902315 | [0.029 0.971] | 0.827 |
+| (0.8, 41) | 0.000229561 | 0.82877 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.000929264 | 0.904374 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 42) | 0.0225886 | 0.807411 | 0.83 | [0.031 0.169 0.001 0.799] | 0.0118405 | 0.892006 | 0.903846 | [0.032 0.968] | 0.83 |
+| (0.8, 43) | 0.0194196 | 0.80858 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.00990255 | 0.893032 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 44) | 0.00644612 | 0.832554 | 0.839 | [0.04 0.16 0.001 0.799] | 0.00352805 | 0.904943 | 0.908471 | [0.041 0.959] | 0.839 |
+| (0.8, 45) | 0.0505133 | 0.779487 | 0.83 | [0.03 0.17 0. 0.8 ] | 0.0279151 | 0.87604 | 0.903955 | [0.03 0.97] | 0.83 |
+| (0.8, 46) | 0.0373503 | 0.79165 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.020021 | 0.883423 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 47) | 0.0360948 | 0.792905 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0211833 | 0.882152 | 0.903335 | [0.031 0.969] | 0.829 |
+| (0.8, 48) | 0.017169 | 0.817831 | 0.835 | [0.035 0.165 0. 0.8 ] | 0.00976995 | 0.896746 | 0.906516 | [0.035 0.965] | 0.835 |
+| (0.8, 49) | 0.0305348 | 0.803465 | 0.834 | [0.035 0.165 0.001 0.799] | 0.0180311 | 0.887865 | 0.905896 | [0.036 0.964] | 0.834 |
+| (0.8, 50) | 0.0293145 | 0.797686 | 0.827 | [0.029 0.171 0.002 0.798] | 0.0166065 | 0.885598 | 0.902205 | [0.031 0.969] | 0.827 |
+| (0.8, 51) | 0.0280583 | 0.802942 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0152134 | 0.889252 | 0.904466 | [0.031 0.969] | 0.831 |
+| (0.8, 52) | 0.0273535 | 0.798646 | 0.826 | [0.026 0.174 0. 0.8 ] | 0.0140662 | 0.88785 | 0.901917 | [0.026 0.974] | 0.826 |
+| (0.8, 53) | 0.037029 | 0.794971 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.0200333 | 0.884944 | 0.904977 | [0.032 0.968] | 0.832 |
+| (0.8, 54) | 0.02648 | 0.79652 | 0.823 | [0.023 0.177 0. 0.8 ] | 0.0137327 | 0.886661 | 0.900394 | [0.023 0.977] | 0.823 |
+| (0.8, 55) | 0.0147235 | 0.812277 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.00601093 | 0.896414 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 56) | 0.0248399 | 0.81016 | 0.835 | [0.035 0.165 0. 0.8 ] | 0.0143239 | 0.892192 | 0.906516 | [0.035 0.965] | 0.835 |
+| (0.8, 57) | 0.0104378 | 0.837438 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.00708952 | 0.909515 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 58) | 0.0244922 | 0.799508 | 0.824 | [0.024 0.176 0. 0.8 ] | 0.0127094 | 0.888191 | 0.900901 | [0.024 0.976] | 0.824 |
+| (0.8, 59) | 0.0260415 | 0.800959 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0150998 | 0.887325 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 60) | 0.0267759 | 0.809224 | 0.836 | [0.036 0.164 0. 0.8 ] | 0.0160896 | 0.89094 | 0.907029 | [0.036 0.964] | 0.836 |
+| (0.8, 61) | 0.0225115 | 0.797488 | 0.82 | [0.021 0.179 0.001 0.799] | 0.0122826 | 0.88648 | 0.898763 | [0.022 0.978] | 0.82 |
+| (0.8, 62) | 0.0343597 | 0.79264 | 0.827 | [0.029 0.171 0.002 0.798] | 0.0190629 | 0.883142 | 0.902205 | [0.031 0.969] | 0.827 |
+| (0.8, 63) | 0.0159727 | 0.813027 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0089236 | 0.894521 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 64) | 0.0416964 | 0.791304 | 0.833 | [0.033 0.167 0. 0.8 ] | 0.0222044 | 0.883285 | 0.90549 | [0.033 0.967] | 0.833 |
+| (0.8, 65) | 0.0316177 | 0.796382 | 0.828 | [0.031 0.169 0.003 0.797] | 0.0189897 | 0.883615 | 0.902605 | [0.034 0.966] | 0.828 |
+| (0.8, 66) | 0.0404031 | 0.794597 | 0.835 | [0.035 0.165 0. 0.8 ] | 0.0213009 | 0.885215 | 0.906516 | [0.035 0.965] | 0.835 |
+| (0.8, 67) | 0.0437875 | 0.790213 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.0242558 | 0.881746 | 0.906002 | [0.034 0.966] | 0.834 |
+| (0.8, 68) | 0.0164454 | 0.817555 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.00894291 | 0.897059 | 0.906002 | [0.034 0.966] | 0.834 |
+| (0.8, 69) | 0.0331339 | 0.794866 | 0.828 | [0.029 0.171 0.001 0.799] | 0.0186214 | 0.884203 | 0.902825 | [0.03 0.97] | 0.828 |
+| (0.8, 70) | 0.0282686 | 0.803731 | 0.832 | [0.032 0.168 0. 0.8 ] | 0.0170943 | 0.887883 | 0.904977 | [0.032 0.968] | 0.832 |
+| (0.8, 71) | 0.0266922 | 0.803308 | 0.83 | [0.031 0.169 0.001 0.799] | 0.0152941 | 0.888552 | 0.903846 | [0.032 0.968] | 0.83 |
+| (0.8, 72) | 0.0192176 | 0.805782 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0112241 | 0.890184 | 0.901408 | [0.025 0.975] | 0.825 |
+| (0.8, 73) | 0.0452923 | 0.778708 | 0.824 | [0.024 0.176 0. 0.8 ] | 0.0253478 | 0.875553 | 0.900901 | [0.024 0.976] | 0.824 |
+| (0.8, 74) | 0.0284065 | 0.800593 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0153539 | 0.887981 | 0.903335 | [0.031 0.969] | 0.829 |
+| (0.8, 75) | 0.019628 | 0.811372 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0115092 | 0.892957 | 0.904466 | [0.031 0.969] | 0.831 |
+| (0.8, 76) | 0.0254376 | 0.802562 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.0147003 | 0.888234 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 77) | 0.0274572 | 0.797543 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0140591 | 0.887349 | 0.901408 | [0.025 0.975] | 0.825 |
+| (0.8, 78) | 0.0268882 | 0.806112 | 0.833 | [0.035 0.165 0.002 0.798] | 0.0145238 | 0.890751 | 0.905275 | [0.037 0.963] | 0.833 |
+| (0.8, 79) | 0.0274169 | 0.803583 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0154312 | 0.889035 | 0.904466 | [0.031 0.969] | 0.831 |
+| (0.8, 80) | 0.0421947 | 0.792805 | 0.835 | [0.037 0.163 0.002 0.798] | 0.0234039 | 0.882899 | 0.906303 | [0.039 0.961] | 0.835 |
+| (0.8, 81) | 0.0341685 | 0.791831 | 0.826 | [0.029 0.171 0.003 0.797] | 0.0188428 | 0.882741 | 0.901584 | [0.032 0.968] | 0.826 |
+| (0.8, 82) | 0.0425206 | 0.791479 | 0.834 | [0.034 0.166 0. 0.8 ] | 0.0250496 | 0.880953 | 0.906002 | [0.034 0.966] | 0.834 |
+| (0.8, 83) | 0.0240059 | 0.805994 | 0.83 | [0.031 0.169 0.001 0.799] | 0.0139455 | 0.889901 | 0.903846 | [0.032 0.968] | 0.83 |
+| (0.8, 84) | 0.0177441 | 0.804256 | 0.822 | [0.022 0.178 0. 0.8 ] | 0.00957679 | 0.890311 | 0.899888 | [0.022 0.978] | 0.822 |
+| (0.8, 85) | 0.00355815 | 0.829442 | 0.833 | [0.034 0.166 0.001 0.799] | 0.000679917 | 0.904703 | 0.905382 | [0.035 0.965] | 0.833 |
+| (0.8, 86) | 0.0074582 | 0.823542 | 0.831 | [0.032 0.168 0.001 0.799] | 0.00372776 | 0.90063 | 0.904358 | [0.033 0.967] | 0.831 |
+| (0.8, 87) | 0.0431926 | 0.785807 | 0.829 | [0.029 0.171 0. 0.8 ] | 0.0239931 | 0.879451 | 0.903444 | [0.029 0.971] | 0.829 |
+| (0.8, 88) | 0.0312967 | 0.793703 | 0.825 | [0.025 0.175 0. 0.8 ] | 0.0164912 | 0.884917 | 0.901408 | [0.025 0.975] | 0.825 |
+| (0.8, 89) | 0.0111373 | 0.815863 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.00594957 | 0.896476 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 90) | 0.0255766 | 0.802423 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.013677 | 0.889258 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 91) | 0.0221193 | 0.808881 | 0.831 | [0.031 0.169 0. 0.8 ] | 0.0110527 | 0.893413 | 0.904466 | [0.031 0.969] | 0.831 |
+| (0.8, 92) | 0.0231501 | 0.80585 | 0.829 | [0.03 0.17 0.001 0.799] | 0.0134434 | 0.889892 | 0.903335 | [0.031 0.969] | 0.829 |
+| (0.8, 93) | 0.0233668 | 0.797633 | 0.821 | [0.021 0.179 0. 0.8 ] | 0.0137534 | 0.885628 | 0.899382 | [0.021 0.979] | 0.821 |
+| (0.8, 94) | 0.00688933 | 0.826111 | 0.833 | [0.034 0.166 0.001 0.799] | 0.0037811 | 0.901601 | 0.905382 | [0.035 0.965] | 0.833 |
+| (0.8, 95) | 0.0243997 | 0.8096 | 0.834 | [0.036 0.164 0.002 0.798] | 0.0114362 | 0.894353 | 0.905789 | [0.038 0.962] | 0.834 |
+| (0.8, 96) | 0.0228605 | 0.80514 | 0.828 | [0.028 0.172 0. 0.8 ] | 0.0123032 | 0.890631 | 0.902935 | [0.028 0.972] | 0.828 |
+| (0.8, 97) | 0.0287869 | 0.797213 | 0.826 | [0.027 0.173 0.001 0.799] | 0.0146776 | 0.887128 | 0.901806 | [0.028 0.972] | 0.826 |
+| (0.8, 98) | 0.0243104 | 0.80269 | 0.827 | [0.027 0.173 0. 0.8 ] | 0.0133648 | 0.88906 | 0.902425 | [0.027 0.973] | 0.827 |
+| (0.8, 99) | 0.034638 | 0.793362 | 0.828 | [0.029 0.171 0.001 0.799] | 0.0180954 | 0.884729 | 0.902825 | [0.03 0.97] | 0.828 |
+| (0.85, 0) | 0.00916264 | 0.856837 | 0.866 | [0.017 0.133 0.001 0.849] | 0.00395676 | 0.922899 | 0.926856 | [0.018 0.982] | 0.866 |
+| (0.85, 1) | 0.0242384 | 0.842762 | 0.867 | [0.019 0.131 0.002 0.848] | 0.0126504 | 0.914632 | 0.927283 | [0.021 0.979] | 0.867 |
+| (0.85, 2) | 0.0059672 | 0.874967 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00366687 | 0.932043 | 0.928376 | [0.021 0.979] | 0.869 |
+| (0.85, 3) | 0.0185452 | 0.856455 | 0.875 | [0.025 0.125 0. 0.85 ] | 0.00887886 | 0.922628 | 0.931507 | [0.025 0.975] | 0.875 |
+| (0.85, 4) | 0.0223926 | 0.854607 | 0.877 | [0.027 0.123 0. 0.85 ] | 0.0109393 | 0.921589 | 0.932529 | [0.027 0.973] | 0.877 |
+| (0.85, 5) | 0.0275382 | 0.843462 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.0144402 | 0.915029 | 0.92947 | [0.021 0.979] | 0.871 |
+| (0.85, 6) | 0.0116306 | 0.864369 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0066333 | 0.925384 | 0.932018 | [0.026 0.974] | 0.876 |
+| (0.85, 7) | 0.0293276 | 0.839672 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0167791 | 0.911675 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 8) | 0.00853504 | 0.862465 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.00453054 | 0.924939 | 0.92947 | [0.021 0.979] | 0.871 |
+| (0.85, 9) | 0.00844529 | 0.877445 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00527631 | 0.933731 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 10) | 0.0174929 | 0.851507 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00949055 | 0.918886 | 0.928376 | [0.021 0.979] | 0.869 |
+| (0.85, 11) | 0.032037 | 0.834963 | 0.867 | [0.017 0.133 0. 0.85 ] | 0.0178529 | 0.909588 | 0.927441 | [0.017 0.983] | 0.867 |
+| (0.85, 12) | 0.02062 | 0.85538 | 0.876 | [0.027 0.123 0.001 0.849] | 0.0106596 | 0.921283 | 0.931943 | [0.028 0.972] | 0.876 |
+| (0.85, 13) | 0.0300872 | 0.839913 | 0.87 | [0.02 0.13 0. 0.85] | 0.0169147 | 0.912047 | 0.928962 | [0.02 0.98] | 0.87 |
+| (0.85, 14) | 0.0185164 | 0.847484 | 0.866 | [0.016 0.134 0. 0.85 ] | 0.0095133 | 0.917422 | 0.926936 | [0.016 0.984] | 0.866 |
+| (0.85, 15) | 0.00594455 | 0.867055 | 0.873 | [0.023 0.127 0. 0.85 ] | 0.00319687 | 0.92729 | 0.930487 | [0.023 0.977] | 0.873 |
+| (0.85, 16) | 0.0159766 | 0.858023 | 0.874 | [0.025 0.125 0.001 0.849] | 0.00772593 | 0.923195 | 0.930921 | [0.026 0.974] | 0.874 |
+| (0.85, 17) | 0.0102021 | 0.862798 | 0.873 | [0.024 0.126 0.001 0.849] | 0.00582044 | 0.924591 | 0.930411 | [0.025 0.975] | 0.873 |
+| (0.85, 18) | 0.0345923 | 0.835408 | 0.87 | [0.021 0.129 0.001 0.849] | 0.0201934 | 0.908691 | 0.928884 | [0.022 0.978] | 0.87 |
+| (0.85, 19) | 0.0164631 | 0.855537 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00789905 | 0.922079 | 0.929978 | [0.022 0.978] | 0.872 |
+| (0.85, 20) | 0.0369302 | 0.83707 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.0197393 | 0.911257 | 0.930997 | [0.024 0.976] | 0.874 |
+| (0.85, 21) | 0.0297006 | 0.844299 | 0.874 | [0.026 0.124 0.002 0.848] | 0.0157164 | 0.915129 | 0.930845 | [0.028 0.972] | 0.874 |
+| (0.85, 22) | 0.00637133 | 0.869629 | 0.876 | [0.027 0.123 0.001 0.849] | 0.00337797 | 0.928565 | 0.931943 | [0.028 0.972] | 0.876 |
+| (0.85, 23) | 0.0257953 | 0.836205 | 0.862 | [0.015 0.135 0.003 0.847] | 0.0138807 | 0.910792 | 0.924672 | [0.018 0.982] | 0.862 |
+| (0.85, 24) | 0.00337444 | 0.868626 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00166765 | 0.92831 | 0.929978 | [0.022 0.978] | 0.872 |
+| (0.85, 25) | 0.024588 | 0.851412 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0122872 | 0.91973 | 0.932018 | [0.026 0.974] | 0.876 |
+| (0.85, 26) | 0.0175407 | 0.853459 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00848404 | 0.920908 | 0.929392 | [0.023 0.977] | 0.871 |
+| (0.85, 27) | 0.0188113 | 0.853189 | 0.872 | [0.023 0.127 0.001 0.849] | 0.00993147 | 0.91997 | 0.929901 | [0.024 0.976] | 0.872 |
+| (0.85, 28) | 0.0102198 | 0.88022 | 0.87 | [0.021 0.129 0.001 0.849] | 0.0060185 | 0.934903 | 0.928884 | [0.022 0.978] | 0.87 |
+| (0.85, 29) | 0.0236431 | 0.844357 | 0.868 | [0.018 0.132 0. 0.85 ] | 0.0131277 | 0.91482 | 0.927948 | [0.018 0.982] | 0.868 |
+| (0.85, 30) | 0.0294663 | 0.840534 | 0.87 | [0.02 0.13 0. 0.85] | 0.0164557 | 0.912506 | 0.928962 | [0.02 0.98] | 0.87 |
+| (0.85, 31) | 0.0125447 | 0.858455 | 0.871 | [0.023 0.127 0.002 0.848] | 0.00581342 | 0.923502 | 0.929315 | [0.025 0.975] | 0.871 |
+| (0.85, 32) | 0.0168929 | 0.851107 | 0.868 | [0.018 0.132 0. 0.85 ] | 0.00838249 | 0.919565 | 0.927948 | [0.018 0.982] | 0.868 |
+| (0.85, 33) | 0.0416726 | 0.827327 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0237554 | 0.904699 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 34) | 0.00899809 | 0.860002 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00365011 | 0.924726 | 0.928376 | [0.021 0.979] | 0.869 |
+| (0.85, 35) | 0.012989 | 0.855011 | 0.868 | [0.02 0.13 0.002 0.848] | 0.00666622 | 0.921124 | 0.92779 | [0.022 0.978] | 0.868 |
+| (0.85, 36) | 0.0118965 | 0.859103 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00526969 | 0.924123 | 0.929392 | [0.023 0.977] | 0.871 |
+| (0.85, 37) | 0.0351497 | 0.83185 | 0.867 | [0.019 0.131 0.002 0.848] | 0.0192705 | 0.908012 | 0.927283 | [0.021 0.979] | 0.867 |
+| (0.85, 38) | 0.000781362 | 0.875781 | 0.875 | [0.025 0.125 0. 0.85 ] | 0.000880589 | 0.932387 | 0.931507 | [0.025 0.975] | 0.875 |
+| (0.85, 39) | 0.0148084 | 0.861192 | 0.876 | [0.028 0.122 0.002 0.848] | 0.00707788 | 0.92479 | 0.931868 | [0.03 0.97] | 0.876 |
+| (0.85, 40) | 0.033094 | 0.839906 | 0.873 | [0.024 0.126 0.001 0.849] | 0.0174848 | 0.912926 | 0.930411 | [0.025 0.975] | 0.873 |
+| (0.85, 41) | 0.00491038 | 0.87191 | 0.867 | [0.018 0.132 0.001 0.849] | 0.00317792 | 0.93054 | 0.927362 | [0.019 0.981] | 0.867 |
+| (0.85, 42) | 0.0118285 | 0.859172 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.00646193 | 0.923008 | 0.92947 | [0.021 0.979] | 0.871 |
+| (0.85, 43) | 0.0222668 | 0.853733 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0109554 | 0.921062 | 0.932018 | [0.026 0.974] | 0.876 |
+| (0.85, 44) | 0.0208303 | 0.85017 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.0116156 | 0.917854 | 0.92947 | [0.021 0.979] | 0.871 |
+| (0.85, 45) | 0.0232634 | 0.844737 | 0.868 | [0.018 0.132 0. 0.85 ] | 0.0132446 | 0.914703 | 0.927948 | [0.018 0.982] | 0.868 |
+| (0.85, 46) | 0.0286176 | 0.837382 | 0.866 | [0.018 0.132 0.002 0.848] | 0.0152861 | 0.91149 | 0.926776 | [0.02 0.98] | 0.866 |
+| (0.85, 47) | 0.0189883 | 0.848012 | 0.867 | [0.018 0.132 0.001 0.849] | 0.0098411 | 0.917521 | 0.927362 | [0.019 0.981] | 0.867 |
+| (0.85, 48) | 0.0291667 | 0.846833 | 0.876 | [0.026 0.124 0. 0.85 ] | 0.0162761 | 0.915741 | 0.932018 | [0.026 0.974] | 0.876 |
+| (0.85, 49) | 0.0139737 | 0.852026 | 0.866 | [0.017 0.133 0.001 0.849] | 0.00675732 | 0.920099 | 0.926856 | [0.018 0.982] | 0.866 |
+| (0.85, 50) | 0.028988 | 0.840012 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0155634 | 0.912891 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 51) | 0.019931 | 0.850069 | 0.87 | [0.021 0.129 0.001 0.849] | 0.0114954 | 0.917389 | 0.928884 | [0.022 0.978] | 0.87 |
+| (0.85, 52) | 0.0126395 | 0.86136 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.00694487 | 0.924052 | 0.930997 | [0.024 0.976] | 0.874 |
+| (0.85, 53) | 0.0174681 | 0.847532 | 0.865 | [0.016 0.134 0.001 0.849] | 0.00971912 | 0.916631 | 0.92635 | [0.017 0.983] | 0.865 |
+| (0.85, 54) | 0.000984246 | 0.871984 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00097317 | 0.930366 | 0.929392 | [0.023 0.977] | 0.871 |
+| (0.85, 55) | 0.00821199 | 0.860788 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00444453 | 0.92401 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 56) | 0.00862268 | 0.861377 | 0.87 | [0.02 0.13 0. 0.85] | 0.00347912 | 0.925483 | 0.928962 | [0.02 0.98] | 0.87 |
+| (0.85, 57) | 0.00934159 | 0.878342 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00568831 | 0.934143 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 58) | 0.0128164 | 0.857184 | 0.87 | [0.021 0.129 0.001 0.849] | 0.00699737 | 0.921887 | 0.928884 | [0.022 0.978] | 0.87 |
+| (0.85, 59) | 0.0331427 | 0.850857 | 0.884 | [0.034 0.116 0. 0.85 ] | 0.0172442 | 0.918879 | 0.936123 | [0.034 0.966] | 0.884 |
+| (0.85, 60) | 0.00682919 | 0.856171 | 0.863 | [0.013 0.137 0. 0.85 ] | 0.00356046 | 0.921861 | 0.925422 | [0.013 0.987] | 0.863 |
+| (0.85, 61) | 0.0141476 | 0.853852 | 0.868 | [0.019 0.131 0.001 0.849] | 0.00671517 | 0.921154 | 0.927869 | [0.02 0.98] | 0.868 |
+| (0.85, 62) | 0.0187097 | 0.85029 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0105429 | 0.917911 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 63) | 0.00948473 | 0.851515 | 0.861 | [0.013 0.137 0.002 0.848] | 0.00445686 | 0.919794 | 0.924251 | [0.015 0.985] | 0.861 |
+| (0.85, 64) | 0.0145757 | 0.854424 | 0.869 | [0.02 0.13 0.001 0.849] | 0.00689778 | 0.921478 | 0.928376 | [0.021 0.979] | 0.869 |
+| (0.85, 65) | 0.00214502 | 0.869145 | 0.867 | [0.02 0.13 0.003 0.847] | 0.00168839 | 0.928891 | 0.927203 | [0.023 0.977] | 0.867 |
+| (0.85, 66) | 0.0170768 | 0.846923 | 0.864 | [0.014 0.136 0. 0.85 ] | 0.00957014 | 0.916356 | 0.925926 | [0.014 0.986] | 0.864 |
+| (0.85, 67) | 0.0227065 | 0.850294 | 0.873 | [0.026 0.124 0.003 0.847] | 0.0130022 | 0.917256 | 0.930258 | [0.029 0.971] | 0.873 |
+| (0.85, 68) | 0.0145889 | 0.860411 | 0.875 | [0.026 0.124 0.001 0.849] | 0.00836658 | 0.923065 | 0.931432 | [0.027 0.973] | 0.875 |
+| (0.85, 69) | 0.0364083 | 0.831592 | 0.868 | [0.02 0.13 0.002 0.848] | 0.019737 | 0.908053 | 0.92779 | [0.022 0.978] | 0.868 |
+| (0.85, 70) | 0.0242443 | 0.847756 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.0123723 | 0.917606 | 0.929978 | [0.022 0.978] | 0.872 |
+| (0.85, 71) | 0.00301728 | 0.867983 | 0.871 | [0.022 0.128 0.001 0.849] | 0.000460011 | 0.928932 | 0.929392 | [0.023 0.977] | 0.871 |
+| (0.85, 72) | 0.027528 | 0.846472 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.0146329 | 0.916364 | 0.930997 | [0.024 0.976] | 0.874 |
+| (0.85, 73) | 0.00503926 | 0.868961 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.00273599 | 0.928261 | 0.930997 | [0.024 0.976] | 0.874 |
+| (0.85, 74) | 0.00180717 | 0.867807 | 0.866 | [0.017 0.133 0.001 0.849] | 0.00122006 | 0.928076 | 0.926856 | [0.018 0.982] | 0.866 |
+| (0.85, 75) | 0.0113285 | 0.863672 | 0.875 | [0.029 0.121 0.004 0.846] | 0.00642303 | 0.924782 | 0.931205 | [0.033 0.967] | 0.875 |
+| (0.85, 76) | 0.0245245 | 0.853476 | 0.878 | [0.028 0.122 0. 0.85 ] | 0.0126659 | 0.920375 | 0.933041 | [0.028 0.972] | 0.878 |
+| (0.85, 77) | 0.0227488 | 0.846251 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.0117367 | 0.916718 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 78) | 0.00669301 | 0.875693 | 0.869 | [0.019 0.131 0. 0.85 ] | 0.00422216 | 0.932677 | 0.928454 | [0.019 0.981] | 0.869 |
+| (0.85, 79) | 0.00956554 | 0.856434 | 0.866 | [0.016 0.134 0. 0.85 ] | 0.00474536 | 0.92219 | 0.926936 | [0.016 0.984] | 0.866 |
+| (0.85, 80) | 0.00108528 | 0.872915 | 0.874 | [0.025 0.125 0.001 0.849] | 0.000293925 | 0.930627 | 0.930921 | [0.026 0.974] | 0.874 |
+| (0.85, 81) | 0.0139251 | 0.857075 | 0.871 | [0.022 0.128 0.001 0.849] | 0.00655939 | 0.922833 | 0.929392 | [0.023 0.977] | 0.871 |
+| (0.85, 82) | 0.0224209 | 0.851579 | 0.874 | [0.026 0.124 0.002 0.848] | 0.0118784 | 0.918967 | 0.930845 | [0.028 0.972] | 0.874 |
+| (0.85, 83) | 0.0234424 | 0.843558 | 0.867 | [0.017 0.133 0. 0.85 ] | 0.0127119 | 0.914729 | 0.927441 | [0.017 0.983] | 0.867 |
+| (0.85, 84) | 0.0127184 | 0.859282 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00659153 | 0.923387 | 0.929978 | [0.022 0.978] | 0.872 |
+| (0.85, 85) | 0.0139557 | 0.858044 | 0.872 | [0.023 0.127 0.001 0.849] | 0.0076882 | 0.922213 | 0.929901 | [0.024 0.976] | 0.872 |
+| (0.85, 86) | 0.00034068 | 0.870341 | 0.87 | [0.02 0.13 0. 0.85] | 0.001697 | 0.930659 | 0.928962 | [0.02 0.98] | 0.87 |
+| (0.85, 87) | 0.0113094 | 0.862691 | 0.874 | [0.024 0.126 0. 0.85 ] | 0.00628484 | 0.924712 | 0.930997 | [0.024 0.976] | 0.874 |
+| (0.85, 88) | 0.0272791 | 0.838721 | 0.866 | [0.016 0.134 0. 0.85 ] | 0.015109 | 0.911827 | 0.926936 | [0.016 0.984] | 0.866 |
+| (0.85, 89) | 0.014482 | 0.892482 | 0.878 | [0.028 0.122 0. 0.85 ] | 0.00856509 | 0.941606 | 0.933041 | [0.028 0.972] | 0.878 |
+| (0.85, 90) | 0.0142999 | 0.8577 | 0.872 | [0.022 0.128 0. 0.85 ] | 0.00755693 | 0.922421 | 0.929978 | [0.022 0.978] | 0.872 |
+| (0.85, 91) | 0.0421117 | 0.827888 | 0.87 | [0.02 0.13 0. 0.85] | 0.0233165 | 0.905645 | 0.928962 | [0.02 0.98] | 0.87 |
+| (0.85, 92) | 0.0311295 | 0.84587 | 0.877 | [0.027 0.123 0. 0.85 ] | 0.0160312 | 0.916498 | 0.932529 | [0.027 0.973] | 0.877 |
+| (0.85, 93) | 0.0141491 | 0.848851 | 0.863 | [0.015 0.135 0.002 0.848] | 0.00791631 | 0.917343 | 0.925259 | [0.017 0.983] | 0.863 |
+| (0.85, 94) | 0.0200191 | 0.851981 | 0.872 | [0.024 0.126 0.002 0.848] | 0.0103975 | 0.919427 | 0.929825 | [0.026 0.974] | 0.872 |
+| (0.85, 95) | 0.0261024 | 0.844898 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.014257 | 0.915213 | 0.92947 | [0.021 0.979] | 0.871 |
+| (0.85, 96) | 0.0153376 | 0.855662 | 0.871 | [0.021 0.129 0. 0.85 ] | 0.0082263 | 0.921243 | 0.92947 | [0.021 0.979] | 0.871 |
+| (0.85, 97) | 0.0226085 | 0.845392 | 0.868 | [0.019 0.131 0.001 0.849] | 0.0117309 | 0.916138 | 0.927869 | [0.02 0.98] | 0.868 |
+| (0.85, 98) | 0.0373645 | 0.833636 | 0.871 | [0.022 0.128 0.001 0.849] | 0.0202228 | 0.90917 | 0.929392 | [0.023 0.977] | 0.871 |
+| (0.85, 99) | 0.0195995 | 0.8574 | 0.877 | [0.027 0.123 0. 0.85 ] | 0.0100396 | 0.922489 | 0.932529 | [0.027 0.973] | 0.877 |
+| (0.9, 0) | 0.0301308 | 0.880869 | 0.911 | [0.012 0.088 0.001 0.899] | 0.0161845 | 0.936651 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 1) | 0.00656327 | 0.919563 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00410703 | 0.958002 | 0.953895 | [0.013 0.987] | 0.913 |
+| (0.9, 2) | 0.0144244 | 0.896576 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00736751 | 0.945468 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 3) | 0.0273018 | 0.891698 | 0.919 | [0.02 0.08 0.001 0.899] | 0.0150242 | 0.941868 | 0.956892 | [0.021 0.979] | 0.919 |
+| (0.9, 4) | 0.0168992 | 0.899101 | 0.916 | [0.016 0.084 0. 0.9 ] | 0.0085499 | 0.946864 | 0.955414 | [0.016 0.984] | 0.916 |
+| (0.9, 5) | 0.00223583 | 0.908764 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00063496 | 0.9522 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 6) | 0.00952175 | 0.904478 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00494578 | 0.949455 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 7) | 0.014533 | 0.899467 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.0074706 | 0.94693 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 8) | 0.01088 | 0.90212 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00584198 | 0.948053 | 0.953895 | [0.013 0.987] | 0.913 |
+| (0.9, 9) | 0.00749745 | 0.899503 | 0.907 | [0.008 0.092 0.001 0.899] | 0.00393881 | 0.946881 | 0.95082 | [0.009 0.991] | 0.907 |
+| (0.9, 10) | 0.0218657 | 0.890134 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.0115157 | 0.941874 | 0.95339 | [0.012 0.988] | 0.912 |
+| (0.9, 11) | 0.00199519 | 0.915005 | 0.917 | [0.018 0.082 0.001 0.899] | 0.0011787 | 0.954696 | 0.955875 | [0.019 0.981] | 0.917 |
+| (0.9, 12) | 0.00284903 | 0.924849 | 0.922 | [0.022 0.078 0. 0.9 ] | 0.00168534 | 0.960152 | 0.958466 | [0.022 0.978] | 0.922 |
+| (0.9, 13) | 0.00074074 | 0.910741 | 0.91 | [0.012 0.088 0.002 0.898] | 0.000999632 | 0.95328 | 0.95228 | [0.014 0.986] | 0.91 |
+| (0.9, 14) | 0.00416334 | 0.911837 | 0.916 | [0.016 0.084 0. 0.9 ] | 0.00221976 | 0.953194 | 0.955414 | [0.016 0.984] | 0.916 |
+| (0.9, 15) | 0.0169214 | 0.897079 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00901792 | 0.945383 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 16) | 0.0165161 | 0.900484 | 0.917 | [0.017 0.083 0. 0.9 ] | 0.00913514 | 0.946786 | 0.955921 | [0.017 0.983] | 0.917 |
+| (0.9, 17) | 0.00866541 | 0.909335 | 0.918 | [0.019 0.081 0.001 0.899] | 0.00399855 | 0.952384 | 0.956383 | [0.02 0.98] | 0.918 |
+| (0.9, 18) | 0.011116 | 0.929116 | 0.918 | [0.019 0.081 0.001 0.899] | 0.00686953 | 0.963253 | 0.956383 | [0.02 0.98] | 0.918 |
+| (0.9, 19) | 0.00628126 | 0.906719 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00329276 | 0.950602 | 0.953895 | [0.013 0.987] | 0.913 |
+| (0.9, 20) | 0.00487117 | 0.909129 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00222355 | 0.952129 | 0.954352 | [0.016 0.984] | 0.914 |
+| (0.9, 21) | 0.00958671 | 0.897413 | 0.907 | [0.008 0.092 0.001 0.899] | 0.0050069 | 0.945813 | 0.95082 | [0.009 0.991] | 0.907 |
+| (0.9, 22) | 0.00296476 | 0.912035 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00143269 | 0.953427 | 0.954859 | [0.017 0.983] | 0.915 |
+| (0.9, 23) | 0.00900789 | 0.907992 | 0.917 | [0.017 0.083 0. 0.9 ] | 0.00414382 | 0.951778 | 0.955921 | [0.017 0.983] | 0.917 |
+| (0.9, 24) | 0.00113461 | 0.924135 | 0.923 | [0.024 0.076 0.001 0.899] | 0.00144543 | 0.960379 | 0.958933 | [0.025 0.975] | 0.923 |
+| (0.9, 25) | 0.0173475 | 0.895653 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00891637 | 0.94493 | 0.953846 | [0.015 0.985] | 0.913 |
+| (0.9, 26) | 0.000654213 | 0.909346 | 0.91 | [0.011 0.089 0.001 0.899] | 0.000174876 | 0.952156 | 0.952331 | [0.012 0.988] | 0.91 |
+| (0.9, 27) | 0.00520818 | 0.908792 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00248187 | 0.951919 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 28) | 0.00428414 | 0.917284 | 0.913 | [0.015 0.085 0.002 0.898] | 0.00242611 | 0.956223 | 0.953797 | [0.017 0.983] | 0.913 |
+| (0.9, 29) | 0.00155474 | 0.922555 | 0.921 | [0.021 0.079 0. 0.9 ] | 0.00142622 | 0.959383 | 0.957956 | [0.021 0.979] | 0.921 |
+| (0.9, 30) | 0.015075 | 0.898925 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00843417 | 0.945918 | 0.954352 | [0.016 0.984] | 0.914 |
+| (0.9, 31) | 0.00664218 | 0.922642 | 0.916 | [0.017 0.083 0.001 0.899] | 0.00408139 | 0.959448 | 0.955367 | [0.018 0.982] | 0.916 |
+| (0.9, 32) | 0.00409654 | 0.908903 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00195499 | 0.951891 | 0.953846 | [0.015 0.985] | 0.913 |
+| (0.9, 33) | 0.0100621 | 0.903938 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00487939 | 0.949521 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 34) | 0.00666714 | 0.909333 | 0.916 | [0.018 0.082 0.002 0.898] | 0.00354481 | 0.951774 | 0.955319 | [0.02 0.98] | 0.916 |
+| (0.9, 35) | 0.00700774 | 0.904992 | 0.912 | [0.013 0.087 0.001 0.899] | 0.00362466 | 0.949716 | 0.95334 | [0.014 0.986] | 0.912 |
+| (0.9, 36) | 0.00340552 | 0.913594 | 0.917 | [0.017 0.083 0. 0.9 ] | 0.00179529 | 0.954126 | 0.955921 | [0.017 0.983] | 0.917 |
+| (0.9, 37) | 0.00453426 | 0.910466 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00190253 | 0.952957 | 0.954859 | [0.017 0.983] | 0.915 |
+| (0.9, 38) | 0.00414505 | 0.916145 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00284759 | 0.956237 | 0.95339 | [0.012 0.988] | 0.912 |
+| (0.9, 39) | 0.00205744 | 0.918943 | 0.921 | [0.021 0.079 0. 0.9 ] | 0.000530198 | 0.957426 | 0.957956 | [0.021 0.979] | 0.921 |
+| (0.9, 40) | 0.00382936 | 0.915171 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.00180558 | 0.955132 | 0.956938 | [0.019 0.981] | 0.919 |
+| (0.9, 41) | 0.00497108 | 0.904029 | 0.909 | [0.011 0.089 0.002 0.898] | 0.00217952 | 0.949596 | 0.951775 | [0.013 0.987] | 0.909 |
+| (0.9, 42) | 0.0112273 | 0.901773 | 0.913 | [0.013 0.087 0. 0.9 ] | 0.00593944 | 0.947956 | 0.953895 | [0.013 0.987] | 0.913 |
+| (0.9, 43) | 0.0170636 | 0.892936 | 0.91 | [0.01 0.09 0. 0.9 ] | 0.00909284 | 0.943288 | 0.952381 | [0.01 0.99] | 0.91 |
+| (0.9, 44) | 0.0162799 | 0.89772 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00884155 | 0.945511 | 0.954352 | [0.016 0.984] | 0.914 |
+| (0.9, 45) | 0.00426367 | 0.922264 | 0.918 | [0.018 0.082 0. 0.9 ] | 0.00234195 | 0.958771 | 0.956429 | [0.018 0.982] | 0.918 |
+| (0.9, 46) | 0.00151459 | 0.918485 | 0.92 | [0.02 0.08 0. 0.9 ] | 0.000635751 | 0.956811 | 0.957447 | [0.02 0.98] | 0.92 |
+| (0.9, 47) | 0.0134137 | 0.897586 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00688702 | 0.945948 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 48) | 0.0125112 | 0.902489 | 0.915 | [0.015 0.085 0. 0.9 ] | 0.00641199 | 0.948495 | 0.954907 | [0.015 0.985] | 0.915 |
+| (0.9, 49) | 0.00639305 | 0.914393 | 0.908 | [0.008 0.092 0. 0.9 ] | 0.00362208 | 0.954996 | 0.951374 | [0.008 0.992] | 0.908 |
+| (0.9, 50) | 0.00774922 | 0.906251 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.0041113 | 0.95029 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 51) | 0.0122481 | 0.898752 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00615901 | 0.946676 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 52) | 0.0058903 | 0.90511 | 0.911 | [0.011 0.089 0. 0.9 ] | 0.00296234 | 0.949923 | 0.952885 | [0.011 0.989] | 0.911 |
+| (0.9, 53) | 0.00697218 | 0.912028 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.0035033 | 0.953435 | 0.956938 | [0.019 0.981] | 0.919 |
+| (0.9, 54) | 0.00297486 | 0.912025 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00088718 | 0.953972 | 0.954859 | [0.017 0.983] | 0.915 |
+| (0.9, 55) | 0.0137413 | 0.898259 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00730465 | 0.946085 | 0.95339 | [0.012 0.988] | 0.912 |
+| (0.9, 56) | 0.0064383 | 0.918438 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00363441 | 0.957024 | 0.95339 | [0.012 0.988] | 0.912 |
+| (0.9, 57) | 0.00642233 | 0.902578 | 0.909 | [0.012 0.088 0.003 0.897] | 0.00295656 | 0.948768 | 0.951724 | [0.015 0.985] | 0.909 |
+| (0.9, 58) | 0.0107958 | 0.920796 | 0.91 | [0.011 0.089 0.001 0.899] | 0.00590905 | 0.95824 | 0.952331 | [0.012 0.988] | 0.91 |
+| (0.9, 59) | 0.000578272 | 0.908422 | 0.909 | [0.009 0.091 0. 0.9 ] | 0.000168299 | 0.951709 | 0.951877 | [0.009 0.991] | 0.909 |
+| (0.9, 60) | 0.0124924 | 0.906508 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.00642065 | 0.950517 | 0.956938 | [0.019 0.981] | 0.919 |
+| (0.9, 61) | 0.0155213 | 0.894479 | 0.91 | [0.012 0.088 0.002 0.898] | 0.00832079 | 0.943959 | 0.95228 | [0.014 0.986] | 0.91 |
+| (0.9, 62) | 0.0116735 | 0.899327 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00587826 | 0.946957 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 63) | 0.00207603 | 0.911924 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.0011058 | 0.953295 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 64) | 0.000689676 | 0.91331 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.000139088 | 0.954262 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 65) | 0.014441 | 0.900559 | 0.915 | [0.016 0.084 0.001 0.899] | 0.00718125 | 0.947678 | 0.954859 | [0.017 0.983] | 0.915 |
+| (0.9, 66) | 0.0176499 | 0.89435 | 0.912 | [0.013 0.087 0.001 0.899] | 0.00954539 | 0.943795 | 0.95334 | [0.014 0.986] | 0.912 |
+| (0.9, 67) | 0.00501621 | 0.908984 | 0.914 | [0.014 0.086 0. 0.9 ] | 0.00243601 | 0.951965 | 0.954401 | [0.014 0.986] | 0.914 |
+| (0.9, 68) | 0.00606039 | 0.90894 | 0.915 | [0.015 0.085 0. 0.9 ] | 0.00265232 | 0.952255 | 0.954907 | [0.015 0.985] | 0.915 |
+| (0.9, 69) | 0.0197135 | 0.898286 | 0.918 | [0.021 0.079 0.003 0.897] | 0.0098805 | 0.946409 | 0.95629 | [0.024 0.976] | 0.918 |
+| (0.9, 70) | 0.0116814 | 0.900319 | 0.912 | [0.012 0.088 0. 0.9 ] | 0.00584883 | 0.947541 | 0.95339 | [0.012 0.988] | 0.912 |
+| (0.9, 71) | 0.00793232 | 0.899068 | 0.907 | [0.008 0.092 0.001 0.899] | 0.00400617 | 0.946813 | 0.95082 | [0.009 0.991] | 0.907 |
+| (0.9, 72) | 0.00787936 | 0.909121 | 0.917 | [0.018 0.082 0.001 0.899] | 0.00347757 | 0.952397 | 0.955875 | [0.019 0.981] | 0.917 |
+| (0.9, 73) | 0.0128338 | 0.901166 | 0.914 | [0.015 0.085 0.001 0.899] | 0.00633845 | 0.948014 | 0.954352 | [0.016 0.984] | 0.914 |
+| (0.9, 74) | 0.000822019 | 0.912822 | 0.912 | [0.013 0.087 0.001 0.899] | 0.00056394 | 0.953904 | 0.95334 | [0.014 0.986] | 0.912 |
+| (0.9, 75) | 0.00670409 | 0.917704 | 0.911 | [0.011 0.089 0. 0.9 ] | 0.00386719 | 0.956752 | 0.952885 | [0.011 0.989] | 0.911 |
+| (0.9, 76) | 0.0180635 | 0.894936 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00958846 | 0.944258 | 0.953846 | [0.015 0.985] | 0.913 |
+| (0.9, 77) | 0.0148393 | 0.900161 | 0.915 | [0.017 0.083 0.002 0.898] | 0.00809086 | 0.94672 | 0.954811 | [0.019 0.981] | 0.915 |
+| (0.9, 78) | 0.00479696 | 0.903203 | 0.908 | [0.01 0.09 0.002 0.898] | 0.00213129 | 0.94914 | 0.951271 | [0.012 0.988] | 0.908 |
+| (0.9, 79) | 0.00734862 | 0.903651 | 0.911 | [0.012 0.088 0.001 0.899] | 0.00346162 | 0.949374 | 0.952835 | [0.013 0.987] | 0.911 |
+| (0.9, 80) | 0.00871425 | 0.906286 | 0.915 | [0.015 0.085 0. 0.9 ] | 0.00469793 | 0.950209 | 0.954907 | [0.015 0.985] | 0.915 |
+| (0.9, 81) | 0.0288783 | 0.884122 | 0.913 | [0.014 0.086 0.001 0.899] | 0.0153488 | 0.938497 | 0.953846 | [0.015 0.985] | 0.913 |
+| (0.9, 82) | 0.00636029 | 0.90364 | 0.91 | [0.011 0.089 0.001 0.899] | 0.00336515 | 0.948965 | 0.952331 | [0.012 0.988] | 0.91 |
+| (0.9, 83) | 0.0398032 | 0.876197 | 0.916 | [0.016 0.084 0. 0.9 ] | 0.0216551 | 0.933759 | 0.955414 | [0.016 0.984] | 0.916 |
+| (0.9, 84) | 0.00975212 | 0.903248 | 0.913 | [0.015 0.085 0.002 0.898] | 0.00525826 | 0.948539 | 0.953797 | [0.017 0.983] | 0.913 |
+| (0.9, 85) | 0.00793273 | 0.920933 | 0.913 | [0.014 0.086 0.001 0.899] | 0.00455126 | 0.958397 | 0.953846 | [0.015 0.985] | 0.913 |
+| (0.9, 86) | 0.0174908 | 0.886509 | 0.904 | [0.006 0.094 0.002 0.898] | 0.00949516 | 0.939765 | 0.94926 | [0.008 0.992] | 0.904 |
+| (0.9, 87) | 0.0180295 | 0.893971 | 0.912 | [0.014 0.086 0.002 0.898] | 0.00968631 | 0.943605 | 0.953291 | [0.016 0.984] | 0.912 |
+| (0.9, 88) | 0.00443638 | 0.909564 | 0.914 | [0.017 0.083 0.003 0.897] | 0.00168449 | 0.952571 | 0.954255 | [0.02 0.98] | 0.914 |
+| (0.9, 89) | 0.0109881 | 0.907012 | 0.918 | [0.019 0.081 0.001 0.899] | 0.00541001 | 0.950973 | 0.956383 | [0.02 0.98] | 0.918 |
+| (0.9, 90) | 0.00504521 | 0.910045 | 0.905 | [0.006 0.094 0.001 0.899] | 0.00289806 | 0.952713 | 0.949815 | [0.007 0.993] | 0.905 |
+| (0.9, 91) | 0.00880224 | 0.910198 | 0.919 | [0.02 0.08 0.001 0.899] | 0.00480602 | 0.952086 | 0.956892 | [0.021 0.979] | 0.919 |
+| (0.9, 92) | 0.00684515 | 0.916155 | 0.923 | [0.023 0.077 0. 0.9 ] | 0.00299495 | 0.955982 | 0.958977 | [0.023 0.977] | 0.923 |
+| (0.9, 93) | 0.00277936 | 0.916221 | 0.919 | [0.019 0.081 0. 0.9 ] | 0.00155942 | 0.955378 | 0.956938 | [0.019 0.981] | 0.919 |
+| (0.9, 94) | 0.00155124 | 0.907449 | 0.909 | [0.009 0.091 0. 0.9 ] | 0.000742878 | 0.951134 | 0.951877 | [0.009 0.991] | 0.909 |
+| (0.9, 95) | 0.0102061 | 0.926206 | 0.916 | [0.017 0.083 0.001 0.899] | 0.00570406 | 0.961071 | 0.955367 | [0.018 0.982] | 0.916 |
+| (0.9, 96) | 0.00659766 | 0.923598 | 0.917 | [0.018 0.082 0.001 0.899] | 0.0037311 | 0.959606 | 0.955875 | [0.019 0.981] | 0.917 |
+| (0.9, 97) | 0.0133374 | 0.903663 | 0.917 | [0.018 0.082 0.001 0.899] | 0.00714786 | 0.948727 | 0.955875 | [0.019 0.981] | 0.917 |
+| (0.9, 98) | 0.0268155 | 0.890185 | 0.917 | [0.019 0.081 0.002 0.898] | 0.0139259 | 0.941902 | 0.955828 | [0.021 0.979] | 0.917 |
+| (0.9, 99) | 0.0100532 | 0.893947 | 0.904 | [0.006 0.094 0.002 0.898] | 0.00525952 | 0.944001 | 0.94926 | [0.008 0.992] | 0.904 |
+| (0.95, 0) | 0.0130864 | 0.969086 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00681747 | 0.98416 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 1) | 0.0112369 | 0.945763 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00590501 | 0.971941 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 2) | 0.000913955 | 0.959086 | 0.96 | [0.01 0.04 0. 0.95] | 0.000476725 | 0.978905 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 3) | 0.00282916 | 0.957829 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00161856 | 0.978458 | 0.97684 | [0.007 0.993] | 0.955 |
+| (0.95, 4) | 0.00252074 | 0.956479 | 0.959 | [0.01 0.04 0.001 0.949] | 0.00124336 | 0.977612 | 0.978855 | [0.011 0.989] | 0.959 |
+| (0.95, 5) | 0.00253113 | 0.957469 | 0.96 | [0.01 0.04 0. 0.95] | 0.00138245 | 0.977999 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 6) | 0.00451495 | 0.951485 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00222678 | 0.975139 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 7) | 0.00417619 | 0.955824 | 0.96 | [0.01 0.04 0. 0.95] | 0.00218906 | 0.977192 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 8) | 0.00512566 | 0.950874 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00255172 | 0.974815 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 9) | 0.00543415 | 0.946566 | 0.952 | [0.005 0.045 0.003 0.947] | 0.00273372 | 0.972549 | 0.975283 | [0.008 0.992] | 0.952 |
+| (0.95, 10) | 0.00479567 | 0.960796 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00253629 | 0.979879 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 11) | 0.0059848 | 0.953015 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00308922 | 0.975788 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 12) | 0.0142771 | 0.971277 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00746109 | 0.98533 | 0.977869 | [0.007 0.993] | 0.957 |
+| (0.95, 13) | 0.00276339 | 0.956237 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00140162 | 0.977475 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 14) | 0.00478025 | 0.95022 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00252338 | 0.974317 | 0.97684 | [0.007 0.993] | 0.955 |
+| (0.95, 15) | 0.0046799 | 0.94932 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00238639 | 0.973951 | 0.976337 | [0.006 0.994] | 0.954 |
+| (0.95, 16) | 0.00442474 | 0.955425 | 0.951 | [0.003 0.047 0.002 0.948] | 0.00232928 | 0.977136 | 0.974807 | [0.005 0.995] | 0.951 |
+| (0.95, 17) | 0.0114726 | 0.945527 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00597459 | 0.971872 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 18) | 0.00567983 | 0.95132 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00293726 | 0.974909 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 19) | 0.0147145 | 0.939286 | 0.954 | [0.004 0.046 0. 0.95 ] | 0.0076719 | 0.96869 | 0.976362 | [0.004 0.996] | 0.954 |
+| (0.95, 20) | 0.0086796 | 0.94732 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00446135 | 0.972905 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 21) | 0.00869415 | 0.951306 | 0.96 | [0.011 0.039 0.001 0.949] | 0.00446133 | 0.974899 | 0.97936 | [0.012 0.988] | 0.96 |
+| (0.95, 22) | 0.00115897 | 0.956159 | 0.955 | [0.005 0.045 0. 0.95 ] | 0.000685432 | 0.977549 | 0.976864 | [0.005 0.995] | 0.955 |
+| (0.95, 23) | 0.0135314 | 0.950469 | 0.964 | [0.014 0.036 0. 0.95 ] | 0.00711114 | 0.974294 | 0.981405 | [0.014 0.986] | 0.964 |
+| (0.95, 24) | 0.000263541 | 0.955736 | 0.956 | [0.007 0.043 0.001 0.949] | 2.1201e-05 | 0.977364 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 25) | 0.0147964 | 0.942204 | 0.957 | [0.01 0.04 0.003 0.947] | 0.00755989 | 0.970241 | 0.977801 | [0.013 0.987] | 0.957 |
+| (0.95, 26) | 0.00568312 | 0.951317 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00294096 | 0.974928 | 0.977869 | [0.007 0.993] | 0.957 |
+| (0.95, 27) | 0.00402375 | 0.954976 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00190956 | 0.976967 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 28) | 0.00112943 | 0.957129 | 0.956 | [0.008 0.042 0.002 0.948] | 0.000543759 | 0.977863 | 0.97732 | [0.01 0.99] | 0.956 |
+| (0.95, 29) | 0.0129274 | 0.950073 | 0.963 | [0.014 0.036 0.001 0.949] | 0.00676198 | 0.974117 | 0.980879 | [0.015 0.985] | 0.963 |
+| (0.95, 30) | 0.00401177 | 0.962012 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00225901 | 0.980632 | 0.978373 | [0.008 0.992] | 0.958 |
+| (0.95, 31) | 0.0084593 | 0.948541 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00432719 | 0.973519 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 32) | 0.00247352 | 0.959474 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00135301 | 0.979199 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 33) | 0.00287278 | 0.957127 | 0.96 | [0.01 0.04 0. 0.95] | 0.00148084 | 0.977901 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 34) | 0.00586271 | 0.951137 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00297376 | 0.974896 | 0.977869 | [0.007 0.993] | 0.957 |
+| (0.95, 35) | 0.00212307 | 0.953877 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00111809 | 0.976225 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 36) | 0.00105894 | 0.961059 | 0.96 | [0.01 0.04 0. 0.95] | 0.000574108 | 0.979956 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 37) | 0.0105679 | 0.943432 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00545768 | 0.97088 | 0.976337 | [0.006 0.994] | 0.954 |
+| (0.95, 38) | 0.005027 | 0.963027 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00259891 | 0.980972 | 0.978373 | [0.008 0.992] | 0.958 |
+| (0.95, 39) | 0.00677662 | 0.950223 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00342102 | 0.974448 | 0.977869 | [0.007 0.993] | 0.957 |
+| (0.95, 40) | 0.0132115 | 0.968212 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00686927 | 0.983709 | 0.97684 | [0.007 0.993] | 0.955 |
+| (0.95, 41) | 0.012049 | 0.944951 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00625242 | 0.971594 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 42) | 0.00143589 | 0.960436 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.000937985 | 0.979815 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 43) | 0.00898241 | 0.952018 | 0.961 | [0.011 0.039 0. 0.95 ] | 0.00471306 | 0.975173 | 0.979887 | [0.011 0.989] | 0.961 |
+| (0.95, 44) | 0.00919265 | 0.947807 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.00470138 | 0.973168 | 0.977869 | [0.007 0.993] | 0.957 |
+| (0.95, 45) | 0.00175008 | 0.95325 | 0.955 | [0.01 0.04 0.005 0.945] | 0.000737709 | 0.976006 | 0.976744 | [0.015 0.985] | 0.955 |
+| (0.95, 46) | 0.00710272 | 0.958103 | 0.951 | [0.005 0.045 0.004 0.946] | 0.00365538 | 0.978411 | 0.974755 | [0.009 0.991] | 0.951 |
+| (0.95, 47) | 0.00418356 | 0.955816 | 0.96 | [0.01 0.04 0. 0.95] | 0.00214877 | 0.977233 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 48) | 0.00453778 | 0.960538 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.0023711 | 0.979737 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 49) | 0.0149231 | 0.972923 | 0.958 | [0.009 0.041 0.001 0.949] | 0.00778307 | 0.986134 | 0.978351 | [0.01 0.99] | 0.958 |
+| (0.95, 50) | 7.40124e-05 | 0.954926 | 0.955 | [0.005 0.045 0. 0.95 ] | 7.84744e-05 | 0.976942 | 0.976864 | [0.005 0.995] | 0.955 |
+| (0.95, 51) | 0.003751 | 0.955751 | 0.952 | [0.002 0.048 0. 0.95 ] | 0.00201513 | 0.977374 | 0.975359 | [0.002 0.998] | 0.952 |
+| (0.95, 52) | 0.00456641 | 0.947434 | 0.952 | [0.005 0.045 0.003 0.947] | 0.00227595 | 0.973007 | 0.975283 | [0.008 0.992] | 0.952 |
+| (0.95, 53) | 0.00276139 | 0.955239 | 0.958 | [0.009 0.041 0.001 0.949] | 0.00132328 | 0.977027 | 0.978351 | [0.01 0.99] | 0.958 |
+| (0.95, 54) | 0.0164937 | 0.941506 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00857274 | 0.9698 | 0.978373 | [0.008 0.992] | 0.958 |
+| (0.95, 55) | 0.00856963 | 0.94243 | 0.951 | [0.002 0.048 0.001 0.949] | 0.00451159 | 0.970321 | 0.974833 | [0.003 0.997] | 0.951 |
+| (0.95, 56) | 0.00327117 | 0.958271 | 0.955 | [0.005 0.045 0. 0.95 ] | 0.00173844 | 0.978602 | 0.976864 | [0.005 0.995] | 0.955 |
+| (0.95, 57) | 0.007871 | 0.944129 | 0.952 | [0.002 0.048 0. 0.95 ] | 0.00409843 | 0.971261 | 0.975359 | [0.002 0.998] | 0.952 |
+| (0.95, 58) | 0.000601234 | 0.956601 | 0.956 | [0.008 0.042 0.002 0.948] | 0.000499576 | 0.977819 | 0.97732 | [0.01 0.99] | 0.956 |
+| (0.95, 59) | 0.0032114 | 0.959211 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00173182 | 0.979075 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 60) | 0.0155299 | 0.93947 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00804949 | 0.96879 | 0.97684 | [0.007 0.993] | 0.955 |
+| (0.95, 61) | 0.0318797 | 0.92512 | 0.957 | [0.009 0.041 0.002 0.948] | 0.0168799 | 0.960944 | 0.977824 | [0.011 0.989] | 0.957 |
+| (0.95, 62) | 0.00587987 | 0.96288 | 0.957 | [0.009 0.041 0.002 0.948] | 0.0030603 | 0.980884 | 0.977824 | [0.011 0.989] | 0.957 |
+| (0.95, 63) | 0.00842203 | 0.947578 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00443652 | 0.97293 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 64) | 0.00752341 | 0.967523 | 0.96 | [0.01 0.04 0. 0.95] | 0.00394008 | 0.983322 | 0.979381 | [0.01 0.99] | 0.96 |
+| (0.95, 65) | 0.000204061 | 0.950204 | 0.95 | [0.005 0.045 0.005 0.945] | 0.000158767 | 0.974386 | 0.974227 | [0.01 0.99] | 0.95 |
+| (0.95, 66) | 0.0121659 | 0.945834 | 0.958 | [0.01 0.04 0.002 0.948] | 0.00618715 | 0.972141 | 0.978328 | [0.012 0.988] | 0.958 |
+| (0.95, 67) | 0.00567601 | 0.952324 | 0.958 | [0.009 0.041 0.001 0.949] | 0.00277065 | 0.97558 | 0.978351 | [0.01 0.99] | 0.958 |
+| (0.95, 68) | 0.000954144 | 0.958046 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.000375038 | 0.978502 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 69) | 0.00060172 | 0.957398 | 0.958 | [0.009 0.041 0.001 0.949] | 0.000289562 | 0.978061 | 0.978351 | [0.01 0.99] | 0.958 |
+| (0.95, 70) | 0.00426978 | 0.96327 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00227676 | 0.981154 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 71) | 0.019713 | 0.937287 | 0.957 | [0.009 0.041 0.002 0.948] | 0.0104357 | 0.967388 | 0.977824 | [0.011 0.989] | 0.957 |
+| (0.95, 72) | 0.00756189 | 0.949438 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00387345 | 0.973973 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 73) | 0.00469595 | 0.951304 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00241727 | 0.974926 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 74) | 0.00317693 | 0.956177 | 0.953 | [0.005 0.045 0.002 0.948] | 0.00168466 | 0.977495 | 0.975811 | [0.007 0.993] | 0.953 |
+| (0.95, 75) | 0.00994606 | 0.968946 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.0053118 | 0.984189 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 76) | 0.00516192 | 0.959162 | 0.954 | [0.006 0.044 0.002 0.948] | 0.00269651 | 0.97901 | 0.976313 | [0.008 0.992] | 0.954 |
+| (0.95, 77) | 0.000941681 | 0.955058 | 0.956 | [0.007 0.043 0.001 0.949] | 0.000330332 | 0.977013 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 78) | 0.0185866 | 0.980587 | 0.962 | [0.014 0.036 0.002 0.948] | 0.00965988 | 0.990011 | 0.980352 | [0.016 0.984] | 0.962 |
+| (0.95, 79) | 0.00133473 | 0.959335 | 0.958 | [0.009 0.041 0.001 0.949] | 0.000654896 | 0.979005 | 0.978351 | [0.01 0.99] | 0.958 |
+| (0.95, 80) | 0.00956923 | 0.944431 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00491612 | 0.971421 | 0.976337 | [0.006 0.994] | 0.954 |
+| (0.95, 81) | 0.00636464 | 0.950635 | 0.957 | [0.008 0.042 0.001 0.949] | 0.00326916 | 0.974577 | 0.977846 | [0.009 0.991] | 0.957 |
+| (0.95, 82) | 0.000789837 | 0.95721 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00023548 | 0.978137 | 0.978373 | [0.008 0.992] | 0.958 |
+| (0.95, 83) | 0.0029409 | 0.961941 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.00171311 | 0.98059 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 84) | 0.00884236 | 0.946158 | 0.955 | [0.005 0.045 0. 0.95 ] | 0.00453154 | 0.972332 | 0.976864 | [0.005 0.995] | 0.955 |
+| (0.95, 85) | 0.000941489 | 0.958941 | 0.958 | [0.01 0.04 0.002 0.948] | 0.000520676 | 0.978849 | 0.978328 | [0.012 0.988] | 0.958 |
+| (0.95, 86) | 0.0140395 | 0.93996 | 0.954 | [0.006 0.044 0.002 0.948] | 0.00744394 | 0.968869 | 0.976313 | [0.008 0.992] | 0.954 |
+| (0.95, 87) | 0.00377863 | 0.961779 | 0.958 | [0.008 0.042 0. 0.95 ] | 0.00200204 | 0.980375 | 0.978373 | [0.008 0.992] | 0.958 |
+| (0.95, 88) | 0.000211864 | 0.959212 | 0.959 | [0.009 0.041 0. 0.95 ] | 0.000207292 | 0.979084 | 0.978877 | [0.009 0.991] | 0.959 |
+| (0.95, 89) | 0.0037105 | 0.952289 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00180449 | 0.975562 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 90) | 0.000369451 | 0.955631 | 0.956 | [0.006 0.044 0. 0.95 ] | 5.4309e-05 | 0.977312 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 91) | 0.00221093 | 0.958211 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00129289 | 0.978659 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 92) | 0.00325314 | 0.958253 | 0.955 | [0.006 0.044 0.001 0.949] | 0.00182254 | 0.978662 | 0.97684 | [0.007 0.993] | 0.955 |
+| (0.95, 93) | 0.0021091 | 0.959109 | 0.957 | [0.007 0.043 0. 0.95 ] | 0.0011343 | 0.979004 | 0.977869 | [0.007 0.993] | 0.957 |
+| (0.95, 94) | 0.0031392 | 0.952861 | 0.956 | [0.006 0.044 0. 0.95 ] | 0.00151907 | 0.975847 | 0.977366 | [0.006 0.994] | 0.956 |
+| (0.95, 95) | 0.0117605 | 0.965761 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00613714 | 0.982475 | 0.976337 | [0.006 0.994] | 0.954 |
+| (0.95, 96) | 0.0128302 | 0.94117 | 0.954 | [0.005 0.045 0.001 0.949] | 0.00671104 | 0.969626 | 0.976337 | [0.006 0.994] | 0.954 |
+| (0.95, 97) | 0.00541577 | 0.955584 | 0.961 | [0.011 0.039 0. 0.95 ] | 0.00261709 | 0.977269 | 0.979887 | [0.011 0.989] | 0.961 |
+| (0.95, 98) | 0.0028626 | 0.953137 | 0.956 | [0.007 0.043 0.001 0.949] | 0.00149962 | 0.975843 | 0.977343 | [0.008 0.992] | 0.956 |
+| (0.95, 99) | 0.00686275 | 0.949137 | 0.956 | [0.007 0.043 0.001 0.949] | 0.0035354 | 0.973808 | 0.977343 | [0.008 0.992] | 0.956 |
+| (1.0, 0) | 0.00038766 | 0.999612 | 1 | [0. 0. 0. 1.] | 0.000193868 | 0.999806 | 1 | [0. 1.] | 1 |
+| (1.0, 1) | 0.000768513 | 0.997231 | 0.998 | [0. 0. 0.002 0.998] | 0.000387314 | 0.998612 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 2) | 0.0110783 | 0.985922 | 0.997 | [0. 0. 0.003 0.997] | 0.00558684 | 0.992911 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 3) | 0.00656081 | 0.990439 | 0.997 | [0. 0. 0.003 0.997] | 0.00330234 | 0.995195 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 4) | 0.00261978 | 0.99538 | 0.998 | [0. 0. 0.002 0.998] | 0.00131429 | 0.997685 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 5) | 0.00163194 | 0.998368 | 1 | [0. 0. 0. 1.] | 0.000816636 | 0.999183 | 1 | [0. 1.] | 1 |
+| (1.0, 6) | 0.00407542 | 0.995925 | 1 | [0. 0. 0. 1.] | 0.00204187 | 0.997958 | 1 | [0. 1.] | 1 |
+| (1.0, 7) | 0.010548 | 0.987452 | 0.998 | [0. 0. 0.002 0.998] | 0.0053126 | 0.993686 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 8) | 0.00242359 | 0.996576 | 0.999 | [0. 0. 0.001 0.999] | 0.00121665 | 0.998283 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 9) | 0.00321056 | 0.995789 | 0.999 | [0. 0. 0.001 0.999] | 0.00160947 | 0.99789 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 10) | 0.00323781 | 0.996762 | 1 | [0. 0. 0. 1.] | 0.00162153 | 0.998378 | 1 | [0. 1.] | 1 |
+| (1.0, 11) | 0.000783789 | 0.999216 | 1 | [0. 0. 0. 1.] | 0.000392048 | 0.999608 | 1 | [0. 1.] | 1 |
+| (1.0, 12) | 0.00695127 | 0.993049 | 1 | [0. 0. 0. 1.] | 0.00348776 | 0.996512 | 1 | [0. 1.] | 1 |
+| (1.0, 13) | 0.00228645 | 0.995714 | 0.998 | [0. 0. 0.002 0.998] | 0.00114683 | 0.997852 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 14) | 0.0112308 | 0.988769 | 1 | [0. 0. 0. 1.] | 0.00564713 | 0.994353 | 1 | [0. 1.] | 1 |
+| (1.0, 15) | 0.012585 | 0.984415 | 0.997 | [0. 0. 0.003 0.997] | 0.00635148 | 0.992146 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 16) | 0.00115313 | 0.998847 | 1 | [0. 0. 0. 1.] | 0.000576897 | 0.999423 | 1 | [0. 1.] | 1 |
+| (1.0, 17) | 0.00564588 | 0.993354 | 0.999 | [0. 0. 0.001 0.999] | 0.00283377 | 0.996666 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 18) | 0.00350382 | 0.995496 | 0.999 | [0. 0. 0.001 0.999] | 0.00175679 | 0.997743 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 19) | 0.00979927 | 0.990201 | 1 | [0. 0. 0. 1.] | 0.00492376 | 0.995076 | 1 | [0. 1.] | 1 |
+| (1.0, 20) | 0.00602819 | 0.991972 | 0.998 | [0. 0. 0.002 0.998] | 0.00302928 | 0.99597 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 21) | 0.00330174 | 0.995698 | 0.999 | [0. 0. 0.001 0.999] | 0.00165551 | 0.997844 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 22) | 0.00237333 | 0.996627 | 0.999 | [0. 0. 0.001 0.999] | 0.00118927 | 0.99831 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 23) | 0.00497561 | 0.994024 | 0.999 | [0. 0. 0.001 0.999] | 0.00249651 | 0.997003 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 24) | 0.0045159 | 0.995484 | 1 | [0. 0. 0. 1.] | 0.00226306 | 0.997737 | 1 | [0. 1.] | 1 |
+| (1.0, 25) | 0.00159816 | 0.999598 | 0.998 | [0. 0. 0.002 0.998] | 0.000799555 | 0.999799 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 26) | 0.00282877 | 0.996171 | 0.999 | [0. 0. 0.001 0.999] | 0.00142084 | 0.998079 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 27) | 0.0055852 | 0.992415 | 0.998 | [0. 0. 0.002 0.998] | 0.00280651 | 0.996192 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 28) | 0.00522598 | 0.994774 | 1 | [0. 0. 0. 1.] | 0.00261984 | 0.99738 | 1 | [0. 1.] | 1 |
+| (1.0, 29) | 0.00351762 | 0.995482 | 0.999 | [0. 0. 0.001 0.999] | 0.00176397 | 0.997736 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 30) | 0.00530586 | 0.993694 | 0.999 | [0. 0. 0.001 0.999] | 0.00266265 | 0.996837 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 31) | 3.04145e-05 | 0.99897 | 0.999 | [0. 0. 0.001 0.999] | 1.59575e-05 | 0.999484 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 32) | 0.00892355 | 0.990076 | 0.999 | [0. 0. 0.001 0.999] | 0.00448628 | 0.995013 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 33) | 0.00909471 | 0.990905 | 1 | [0. 0. 0. 1.] | 0.00456814 | 0.995432 | 1 | [0. 1.] | 1 |
+| (1.0, 34) | 0.00174823 | 0.997252 | 0.999 | [0. 0. 0.001 0.999] | 0.000876536 | 0.998623 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 35) | 0.00144624 | 0.996554 | 0.998 | [0. 0. 0.002 0.998] | 0.000725097 | 0.998274 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 36) | 0.0104275 | 0.989573 | 1 | [0. 0. 0. 1.] | 0.00524108 | 0.994759 | 1 | [0. 1.] | 1 |
+| (1.0, 37) | 0.00680342 | 0.992197 | 0.999 | [0. 0. 0.001 0.999] | 0.00341675 | 0.996083 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 38) | 0.0005654 | 0.998565 | 0.998 | [0. 0. 0.002 0.998] | 0.000281429 | 0.99928 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 39) | 0.0103369 | 0.988663 | 0.999 | [0. 0. 0.001 0.999] | 0.0052012 | 0.994299 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 40) | 0.00464786 | 0.994352 | 0.999 | [0. 0. 0.001 0.999] | 0.00233173 | 0.997168 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 41) | 0.00555467 | 0.993445 | 0.999 | [0. 0. 0.001 0.999] | 0.00278786 | 0.996712 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 42) | 0.000538905 | 0.999461 | 1 | [0. 0. 0. 1.] | 0.000269525 | 0.99973 | 1 | [0. 1.] | 1 |
+| (1.0, 43) | 0.000103208 | 0.999897 | 1 | [0. 0. 0. 1.] | 5.16066e-05 | 0.999948 | 1 | [0. 1.] | 1 |
+| (1.0, 44) | 0.000659831 | 0.99834 | 0.999 | [0. 0. 0.001 0.999] | 0.00033133 | 0.999168 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 45) | 0.00772108 | 0.991279 | 0.999 | [0. 0. 0.001 0.999] | 0.00388279 | 0.995617 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 46) | 0.0105663 | 0.986434 | 0.997 | [0. 0. 0.003 0.997] | 0.00532721 | 0.993171 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 47) | 0.00475672 | 0.995243 | 1 | [0. 0. 0. 1.] | 0.00238403 | 0.997616 | 1 | [0. 1.] | 1 |
+| (1.0, 48) | 0.00098032 | 0.99902 | 1 | [0. 0. 0. 1.] | 0.0004904 | 0.99951 | 1 | [0. 1.] | 1 |
+| (1.0, 49) | 0.00485684 | 0.995143 | 1 | [0. 0. 0. 1.] | 0.00243433 | 0.997566 | 1 | [0. 1.] | 1 |
+| (1.0, 50) | 0.000364171 | 0.999636 | 1 | [0. 0. 0. 1.] | 0.000182119 | 0.999818 | 1 | [0. 1.] | 1 |
+| (1.0, 51) | 0.00901725 | 0.989983 | 0.999 | [0. 0. 0.001 0.999] | 0.00453359 | 0.994966 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 52) | 0.00401398 | 0.995986 | 1 | [0. 0. 0. 1.] | 0.00201102 | 0.997989 | 1 | [0. 1.] | 1 |
+| (1.0, 53) | 6.02743e-05 | 0.99994 | 1 | [0. 0. 0. 1.] | 3.0138e-05 | 0.99997 | 1 | [0. 1.] | 1 |
+| (1.0, 54) | 0.00525217 | 0.993748 | 0.999 | [0. 0. 0.001 0.999] | 0.00263592 | 0.996864 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 55) | 0.00586705 | 0.992133 | 0.998 | [0. 0. 0.002 0.998] | 0.00294815 | 0.996051 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 56) | 0.0047068 | 0.993293 | 0.998 | [0. 0. 0.002 0.998] | 0.00236369 | 0.996635 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 57) | 0.000832389 | 0.999168 | 1 | [0. 0. 0. 1.] | 0.000416368 | 0.999584 | 1 | [0. 1.] | 1 |
+| (1.0, 58) | 0.00219301 | 0.997807 | 1 | [0. 0. 0. 1.] | 0.00109771 | 0.998902 | 1 | [0. 1.] | 1 |
+| (1.0, 59) | 0.00652092 | 0.991479 | 0.998 | [0. 0. 0.002 0.998] | 0.0032777 | 0.995721 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 60) | 0.00533726 | 0.991663 | 0.997 | [0. 0. 0.003 0.997] | 0.0026845 | 0.995813 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 61) | 0.00188364 | 0.997116 | 0.999 | [0. 0. 0.001 0.999] | 0.000945307 | 0.998554 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 62) | 0.00960516 | 0.990395 | 1 | [0. 0. 0. 1.] | 0.00482576 | 0.995174 | 1 | [0. 1.] | 1 |
+| (1.0, 63) | 0.000144585 | 0.999855 | 1 | [0. 0. 0. 1.] | 7.22978e-05 | 0.999928 | 1 | [0. 1.] | 1 |
+| (1.0, 64) | 0.0125929 | 0.984407 | 0.997 | [0. 0. 0.003 0.997] | 0.00635546 | 0.992142 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 65) | 0.00338717 | 0.995613 | 0.999 | [0. 0. 0.001 0.999] | 0.00169816 | 0.997802 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 66) | 0.00079801 | 0.998202 | 0.999 | [0. 0. 0.001 0.999] | 0.000401174 | 0.999099 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 67) | 0.00224744 | 0.997753 | 1 | [0. 0. 0. 1.] | 0.00112499 | 0.998875 | 1 | [0. 1.] | 1 |
+| (1.0, 68) | 0.00487772 | 0.995122 | 1 | [0. 0. 0. 1.] | 0.00244482 | 0.997555 | 1 | [0. 1.] | 1 |
+| (1.0, 69) | 0.000371242 | 0.999629 | 1 | [0. 0. 0. 1.] | 0.000185655 | 0.999814 | 1 | [0. 1.] | 1 |
+| (1.0, 70) | 0.00206798 | 0.997932 | 1 | [0. 0. 0. 1.] | 0.00103506 | 0.998965 | 1 | [0. 1.] | 1 |
+| (1.0, 71) | 0.000710046 | 0.99929 | 1 | [0. 0. 0. 1.] | 0.000355149 | 0.999645 | 1 | [0. 1.] | 1 |
+| (1.0, 72) | 0.00335647 | 0.993644 | 0.997 | [0. 0. 0.003 0.997] | 0.00168683 | 0.996811 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 73) | 0.00405536 | 0.994945 | 0.999 | [0. 0. 0.001 0.999] | 0.00203386 | 0.997466 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 74) | 0.00439108 | 0.995609 | 1 | [0. 0. 0. 1.] | 0.00220037 | 0.9978 | 1 | [0. 1.] | 1 |
+| (1.0, 75) | 0.000376378 | 0.999624 | 1 | [0. 0. 0. 1.] | 0.000188225 | 0.999812 | 1 | [0. 1.] | 1 |
+| (1.0, 76) | 2.2775e-05 | 0.999977 | 1 | [0. 0. 0. 1.] | 1.13876e-05 | 0.999989 | 1 | [0. 1.] | 1 |
+| (1.0, 77) | 0.000470373 | 0.99953 | 1 | [0. 0. 0. 1.] | 0.000235242 | 0.999765 | 1 | [0. 1.] | 1 |
+| (1.0, 78) | 0.000160133 | 0.99984 | 1 | [0. 0. 0. 1.] | 8.00731e-05 | 0.99992 | 1 | [0. 1.] | 1 |
+| (1.0, 79) | 0.00207087 | 0.997929 | 1 | [0. 0. 0. 1.] | 0.00103651 | 0.998963 | 1 | [0. 1.] | 1 |
+| (1.0, 80) | 0.00810417 | 0.989896 | 0.998 | [0. 0. 0.002 0.998] | 0.00407733 | 0.994922 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 81) | 0.00617284 | 0.993827 | 1 | [0. 0. 0. 1.] | 0.00309598 | 0.996904 | 1 | [0. 1.] | 1 |
+| (1.0, 82) | 0.000753367 | 0.999247 | 1 | [0. 0. 0. 1.] | 0.000376825 | 0.999623 | 1 | [0. 1.] | 1 |
+| (1.0, 83) | 0.00409922 | 0.995901 | 1 | [0. 0. 0. 1.] | 0.00205382 | 0.997946 | 1 | [0. 1.] | 1 |
+| (1.0, 84) | 0.00782572 | 0.990174 | 0.998 | [0. 0. 0.002 0.998] | 0.00393612 | 0.995063 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 85) | 0.0045099 | 0.99349 | 0.998 | [0. 0. 0.002 0.998] | 0.0022646 | 0.996734 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 86) | 0.00363821 | 0.994362 | 0.998 | [0. 0. 0.002 0.998] | 0.00182623 | 0.997173 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 87) | 0.00481349 | 0.995187 | 1 | [0. 0. 0. 1.] | 0.00241255 | 0.997587 | 1 | [0. 1.] | 1 |
+| (1.0, 88) | 0.00433078 | 0.995669 | 1 | [0. 0. 0. 1.] | 0.00217009 | 0.99783 | 1 | [0. 1.] | 1 |
+| (1.0, 89) | 0.00589255 | 0.992107 | 0.998 | [0. 0. 0.002 0.998] | 0.00296091 | 0.996038 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 90) | 0.000687943 | 0.999312 | 1 | [0. 0. 0. 1.] | 0.00034409 | 0.999656 | 1 | [0. 1.] | 1 |
+| (1.0, 91) | 0.00126096 | 0.998261 | 0.997 | [0. 0. 0.003 0.997] | 0.000629455 | 0.999127 | 0.998498 | [0.003 0.997] | 0.997 |
+| (1.0, 92) | 0.0047099 | 0.99429 | 0.999 | [0. 0. 0.001 0.999] | 0.00236294 | 0.997137 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 93) | 0.00124108 | 0.997759 | 0.999 | [0. 0. 0.001 0.999] | 0.000621546 | 0.998878 | 0.9995 | [0.001 0.999] | 0.999 |
+| (1.0, 94) | 0.00111707 | 0.996883 | 0.998 | [0. 0. 0.002 0.998] | 0.00055997 | 0.998439 | 0.998999 | [0.002 0.998] | 0.998 |
+| (1.0, 95) | 2.16117e-05 | 0.999978 | 1 | [0. 0. 0. 1.] | 1.0806e-05 | 0.999989 | 1 | [0. 1.] | 1 |
+| (1.0, 96) | 0.00580863 | 0.994191 | 1 | [0. 0. 0. 1.] | 0.00291278 | 0.997087 | 1 | [0. 1.] | 1 |
+| (1.0, 97) | 0.00636452 | 0.993635 | 1 | [0. 0. 0. 1.] | 0.00319242 | 0.996808 | 1 | [0. 1.] | 1 |
+| (1.0, 98) | 0.00321332 | 0.996787 | 1 | [0. 0. 0. 1.] | 0.00160925 | 0.998391 | 1 | [0. 1.] | 1 |
| (1.0, 99) | 0.00562354 | 0.992376 | 0.998 | [0. 0. 0.002 0.998] | 0.00282537 | 0.996174 | 0.998999 | [0.002 0.998] | 0.998 |
\ No newline at end of file
diff --git a/tests/test_data.py b/tests/test_data.py
index d8e6b3c..53c6d30 100644
--- a/tests/test_data.py
+++ b/tests/test_data.py
@@ -1,225 +1,225 @@
-import pytest
-from quacc.data import ExClassManager as ECM, ExtendedCollection
-import numpy as np
-import scipy.sparse as sp
-
-
-class TestExClassManager:
- @pytest.mark.parametrize(
- "true_class,pred_class,result",
- [
- (0, 0, 0),
- (0, 1, 1),
- (1, 0, 2),
- (1, 1, 3),
- ],
- )
- def test_get_ex(self, true_class, pred_class, result):
- ncl = 2
- assert ECM.get_ex(ncl, true_class, pred_class) == result
-
- @pytest.mark.parametrize(
- "ex_class,result",
- [
- (0, 0),
- (1, 1),
- (2, 0),
- (3, 1),
- ],
- )
- def test_get_pred(self, ex_class, result):
- ncl = 2
- assert ECM.get_pred(ncl, ex_class) == result
-
- @pytest.mark.parametrize(
- "ex_class,result",
- [
- (0, 0),
- (1, 0),
- (2, 1),
- (3, 1),
- ],
- )
- def test_get_true(self, ex_class, result):
- ncl = 2
- assert ECM.get_true(ncl, ex_class) == result
-
-
-class TestExtendedCollection:
- @pytest.mark.parametrize(
- "instances,result",
- [
- (
- np.asarray(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- [np.asarray([1, 3]), np.asarray([0, 2])],
- ),
- (
- sp.csr_matrix(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- [np.asarray([1, 3]), np.asarray([0, 2])],
- ),
- (
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- [np.asarray([], dtype=int), np.asarray([0, 1])],
- ),
- (
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- [np.asarray([], dtype=int), np.asarray([0, 1])],
- ),
- (
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- [np.asarray([0, 1]), np.asarray([], dtype=int)],
- ),
- (
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- [np.asarray([0, 1]), np.asarray([], dtype=int)],
- ),
- ],
- )
- def test__split_index_by_pred(self, instances, result):
- ncl = 2
- assert all(
- np.array_equal(a, b)
- for (a, b) in zip(
- ExtendedCollection._split_index_by_pred(ncl, instances),
- result,
- )
- )
-
- @pytest.mark.parametrize(
- "instances,s_inst,norms",
- [
- (
- np.asarray(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- [
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- ],
- [0.5, 0.5],
- ),
- (
- sp.csr_matrix(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- [
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- ],
- [0.5, 0.5],
- ),
- (
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- [
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([], dtype=int),
- ],
- [1.0, 0.0],
- ),
- (
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- [
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- sp.csr_matrix([], dtype=int),
- ],
- [1.0, 0.0],
- ),
- (
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- [
- np.asarray([], dtype=int),
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- ],
- [0.0, 1.0],
- ),
- (
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- [
- sp.csr_matrix([], dtype=int),
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- ],
- [0.0, 1.0],
- ),
- ],
- )
- def test_split_inst_by_pred(self, instances, s_inst, norms):
- ncl = 2
- _s_inst, _norms = ExtendedCollection.split_inst_by_pred(ncl, instances)
- if isinstance(s_inst, np.ndarray):
- assert all(np.array_equal(a, b) for (a, b) in zip(_s_inst, s_inst))
- if isinstance(s_inst, sp.csr_matrix):
- assert all((a != b).nnz == 0 for (a, b) in zip(_s_inst, s_inst))
- assert all(a == b for (a, b) in zip(_norms, norms))
-
- @pytest.mark.parametrize(
- "instances,labels,inst0,lbl0,inst1,lbl1",
- [
- (
- np.asarray(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- np.asarray([3, 0, 1, 2]),
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0, 1]),
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([1, 0]),
- ),
- (
- sp.csr_matrix(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- np.asarray([3, 0, 1, 2]),
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0, 1]),
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([1, 0]),
- ),
- (
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([3, 1]),
- np.asarray([], dtype=int),
- np.asarray([], dtype=int),
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([1, 0]),
- ),
- (
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([3, 1]),
- sp.csr_matrix(np.empty((0, 0), dtype=int)),
- np.asarray([], dtype=int),
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([1, 0]),
- ),
- (
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0, 2]),
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0, 1]),
- np.asarray([], dtype=int),
- np.asarray([], dtype=int),
- ),
- (
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0, 2]),
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0, 1]),
- sp.csr_matrix(np.empty((0, 0), dtype=int)),
- np.asarray([], dtype=int),
- ),
- ],
- )
- def test_split_by_pred(self, instances, labels, inst0, lbl0, inst1, lbl1):
- ec = ExtendedCollection(instances, labels, classes=range(0, 4))
- [ec0, ec1] = ec.split_by_pred()
- if isinstance(instances, np.ndarray):
- assert np.array_equal(ec0.X, inst0)
- assert np.array_equal(ec1.X, inst1)
- if isinstance(instances, sp.csr_matrix):
- assert (ec0.X != inst0).nnz == 0
- assert (ec1.X != inst1).nnz == 0
- assert np.array_equal(ec0.y, lbl0)
- assert np.array_equal(ec1.y, lbl1)
+import pytest
+from quacc.data import ExClassManager as ECM, ExtendedCollection
+import numpy as np
+import scipy.sparse as sp
+
+
+class TestExClassManager:
+ @pytest.mark.parametrize(
+ "true_class,pred_class,result",
+ [
+ (0, 0, 0),
+ (0, 1, 1),
+ (1, 0, 2),
+ (1, 1, 3),
+ ],
+ )
+ def test_get_ex(self, true_class, pred_class, result):
+ ncl = 2
+ assert ECM.get_ex(ncl, true_class, pred_class) == result
+
+ @pytest.mark.parametrize(
+ "ex_class,result",
+ [
+ (0, 0),
+ (1, 1),
+ (2, 0),
+ (3, 1),
+ ],
+ )
+ def test_get_pred(self, ex_class, result):
+ ncl = 2
+ assert ECM.get_pred(ncl, ex_class) == result
+
+ @pytest.mark.parametrize(
+ "ex_class,result",
+ [
+ (0, 0),
+ (1, 0),
+ (2, 1),
+ (3, 1),
+ ],
+ )
+ def test_get_true(self, ex_class, result):
+ ncl = 2
+ assert ECM.get_true(ncl, ex_class) == result
+
+
+class TestExtendedCollection:
+ @pytest.mark.parametrize(
+ "instances,result",
+ [
+ (
+ np.asarray(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ [np.asarray([1, 3]), np.asarray([0, 2])],
+ ),
+ (
+ sp.csr_matrix(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ [np.asarray([1, 3]), np.asarray([0, 2])],
+ ),
+ (
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ [np.asarray([], dtype=int), np.asarray([0, 1])],
+ ),
+ (
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ [np.asarray([], dtype=int), np.asarray([0, 1])],
+ ),
+ (
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ [np.asarray([0, 1]), np.asarray([], dtype=int)],
+ ),
+ (
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ [np.asarray([0, 1]), np.asarray([], dtype=int)],
+ ),
+ ],
+ )
+ def test__split_index_by_pred(self, instances, result):
+ ncl = 2
+ assert all(
+ np.array_equal(a, b)
+ for (a, b) in zip(
+ ExtendedCollection._split_index_by_pred(ncl, instances),
+ result,
+ )
+ )
+
+ @pytest.mark.parametrize(
+ "instances,s_inst,norms",
+ [
+ (
+ np.asarray(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ [
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ ],
+ [0.5, 0.5],
+ ),
+ (
+ sp.csr_matrix(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ [
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ ],
+ [0.5, 0.5],
+ ),
+ (
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ [
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([], dtype=int),
+ ],
+ [1.0, 0.0],
+ ),
+ (
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ [
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ sp.csr_matrix([], dtype=int),
+ ],
+ [1.0, 0.0],
+ ),
+ (
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ [
+ np.asarray([], dtype=int),
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ ],
+ [0.0, 1.0],
+ ),
+ (
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ [
+ sp.csr_matrix([], dtype=int),
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ ],
+ [0.0, 1.0],
+ ),
+ ],
+ )
+ def test_split_inst_by_pred(self, instances, s_inst, norms):
+ ncl = 2
+ _s_inst, _norms = ExtendedCollection.split_inst_by_pred(ncl, instances)
+ if isinstance(s_inst, np.ndarray):
+ assert all(np.array_equal(a, b) for (a, b) in zip(_s_inst, s_inst))
+ if isinstance(s_inst, sp.csr_matrix):
+ assert all((a != b).nnz == 0 for (a, b) in zip(_s_inst, s_inst))
+ assert all(a == b for (a, b) in zip(_norms, norms))
+
+ @pytest.mark.parametrize(
+ "instances,labels,inst0,lbl0,inst1,lbl1",
+ [
+ (
+ np.asarray(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ np.asarray([3, 0, 1, 2]),
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0, 1]),
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([1, 0]),
+ ),
+ (
+ sp.csr_matrix(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ np.asarray([3, 0, 1, 2]),
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0, 1]),
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([1, 0]),
+ ),
+ (
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([3, 1]),
+ np.asarray([], dtype=int),
+ np.asarray([], dtype=int),
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([1, 0]),
+ ),
+ (
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([3, 1]),
+ sp.csr_matrix(np.empty((0, 0), dtype=int)),
+ np.asarray([], dtype=int),
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([1, 0]),
+ ),
+ (
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0, 2]),
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0, 1]),
+ np.asarray([], dtype=int),
+ np.asarray([], dtype=int),
+ ),
+ (
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0, 2]),
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0, 1]),
+ sp.csr_matrix(np.empty((0, 0), dtype=int)),
+ np.asarray([], dtype=int),
+ ),
+ ],
+ )
+ def test_split_by_pred(self, instances, labels, inst0, lbl0, inst1, lbl1):
+ ec = ExtendedCollection(instances, labels, classes=range(0, 4))
+ [ec0, ec1] = ec.split_by_pred()
+ if isinstance(instances, np.ndarray):
+ assert np.array_equal(ec0.X, inst0)
+ assert np.array_equal(ec1.X, inst1)
+ if isinstance(instances, sp.csr_matrix):
+ assert (ec0.X != inst0).nnz == 0
+ assert (ec1.X != inst1).nnz == 0
+ assert np.array_equal(ec0.y, lbl0)
+ assert np.array_equal(ec1.y, lbl1)
diff --git a/tests/test_dataset.py b/tests/test_dataset.py
index b3ffda5..9b2a72a 100644
--- a/tests/test_dataset.py
+++ b/tests/test_dataset.py
@@ -1,3 +1,3 @@
-
-class TestDataset:
+
+class TestDataset:
pass
\ No newline at end of file
diff --git a/tests/test_evaluation/test_baseline.py b/tests/test_evaluation/test_baseline.py
index 20fac98..eab79c2 100644
--- a/tests/test_evaluation/test_baseline.py
+++ b/tests/test_evaluation/test_baseline.py
@@ -1,12 +1,12 @@
-from sklearn.linear_model import LogisticRegression
-
-from quacc.dataset import Dataset
-from quacc.evaluation.baseline import kfcv
-
-
-class TestBaseline:
- def test_kfcv(self):
- spambase = Dataset("spambase", n_prevalences=1).get_raw()
- c_model = LogisticRegression()
- c_model.fit(spambase.train.X, spambase.train.y)
- assert "f1_score" in kfcv(c_model, spambase.validation)
+from sklearn.linear_model import LogisticRegression
+
+from quacc.dataset import Dataset
+from quacc.evaluation.baseline import kfcv
+
+
+class TestBaseline:
+ def test_kfcv(self):
+ spambase = Dataset("spambase", n_prevalences=1).get_raw()
+ c_model = LogisticRegression()
+ c_model.fit(spambase.train.X, spambase.train.y)
+ assert "f1_score" in kfcv(c_model, spambase.validation)
diff --git a/tests/test_method/test_base/test_BQAE.py b/tests/test_method/test_base/test_BQAE.py
index f28c71b..426b08f 100644
--- a/tests/test_method/test_base/test_BQAE.py
+++ b/tests/test_method/test_base/test_BQAE.py
@@ -1,66 +1,66 @@
-import numpy as np
-import pytest
-import scipy.sparse as sp
-from sklearn.linear_model import LogisticRegression
-
-from quacc.method.base import BinaryQuantifierAccuracyEstimator
-
-
-class TestBQAE:
- @pytest.mark.parametrize(
- "instances,preds0,preds1,result",
- [
- (
- np.asarray(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- np.asarray([0.3, 0.7]),
- np.asarray([0.4, 0.6]),
- np.asarray([0.15, 0.2, 0.35, 0.3]),
- ),
- (
- sp.csr_matrix(
- [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
- ),
- np.asarray([0.3, 0.7]),
- np.asarray([0.4, 0.6]),
- np.asarray([0.15, 0.2, 0.35, 0.3]),
- ),
- (
- np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([0.3, 0.7]),
- np.asarray([0.4, 0.6]),
- np.asarray([0.0, 0.4, 0.0, 0.6]),
- ),
- (
- sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
- np.asarray([0.3, 0.7]),
- np.asarray([0.4, 0.6]),
- np.asarray([0.0, 0.4, 0.0, 0.6]),
- ),
- (
- np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0.3, 0.7]),
- np.asarray([0.4, 0.6]),
- np.asarray([0.3, 0.0, 0.7, 0.0]),
- ),
- (
- sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
- np.asarray([0.3, 0.7]),
- np.asarray([0.4, 0.6]),
- np.asarray([0.3, 0.0, 0.7, 0.0]),
- ),
- ],
- )
- def test_estimate_ndarray(self, mocker, instances, preds0, preds1, result):
- estimator = BinaryQuantifierAccuracyEstimator(LogisticRegression())
- estimator.n_classes = 4
- with mocker.patch.object(estimator.q_model_0, "quantify"), mocker.patch.object(
- estimator.q_model_1, "quantify"
- ):
- estimator.q_model_0.quantify.return_value = preds0
- estimator.q_model_1.quantify.return_value = preds1
- assert np.array_equal(
- estimator.estimate(instances, ext=True),
- result,
- )
+import numpy as np
+import pytest
+import scipy.sparse as sp
+from sklearn.linear_model import LogisticRegression
+
+from quacc.method.base import BinaryQuantifierAccuracyEstimator
+
+
+class TestBQAE:
+ @pytest.mark.parametrize(
+ "instances,preds0,preds1,result",
+ [
+ (
+ np.asarray(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ np.asarray([0.3, 0.7]),
+ np.asarray([0.4, 0.6]),
+ np.asarray([0.15, 0.2, 0.35, 0.3]),
+ ),
+ (
+ sp.csr_matrix(
+ [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+ ),
+ np.asarray([0.3, 0.7]),
+ np.asarray([0.4, 0.6]),
+ np.asarray([0.15, 0.2, 0.35, 0.3]),
+ ),
+ (
+ np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([0.3, 0.7]),
+ np.asarray([0.4, 0.6]),
+ np.asarray([0.0, 0.4, 0.0, 0.6]),
+ ),
+ (
+ sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+ np.asarray([0.3, 0.7]),
+ np.asarray([0.4, 0.6]),
+ np.asarray([0.0, 0.4, 0.0, 0.6]),
+ ),
+ (
+ np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0.3, 0.7]),
+ np.asarray([0.4, 0.6]),
+ np.asarray([0.3, 0.0, 0.7, 0.0]),
+ ),
+ (
+ sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+ np.asarray([0.3, 0.7]),
+ np.asarray([0.4, 0.6]),
+ np.asarray([0.3, 0.0, 0.7, 0.0]),
+ ),
+ ],
+ )
+ def test_estimate_ndarray(self, mocker, instances, preds0, preds1, result):
+ estimator = BinaryQuantifierAccuracyEstimator(LogisticRegression())
+ estimator.n_classes = 4
+ with mocker.patch.object(estimator.q_model_0, "quantify"), mocker.patch.object(
+ estimator.q_model_1, "quantify"
+ ):
+ estimator.q_model_0.quantify.return_value = preds0
+ estimator.q_model_1.quantify.return_value = preds1
+ assert np.array_equal(
+ estimator.estimate(instances, ext=True),
+ result,
+ )
diff --git a/tests/test_method/test_base/test_MCAE.py b/tests/test_method/test_base/test_MCAE.py
index b0784a2..a6cae5e 100644
--- a/tests/test_method/test_base/test_MCAE.py
+++ b/tests/test_method/test_base/test_MCAE.py
@@ -1,2 +1,2 @@
-class TestMCAE:
- pass
+class TestMCAE:
+ pass