pacc added to methods
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@ -2,7 +2,7 @@ import inspect
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from functools import wraps
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from functools import wraps
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import numpy as np
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import numpy as np
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from quapy.method.aggregative import SLD
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from quapy.method.aggregative import PACC, SLD
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from quapy.protocol import UPP, AbstractProtocol
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from quapy.protocol import UPP, AbstractProtocol
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from sklearn.linear_model import LogisticRegression
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from sklearn.linear_model import LogisticRegression
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@ -127,3 +127,66 @@ def mul_sld_gs(c_model, validation, protocol) -> EvaluationReport:
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estimator=est,
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estimator=est,
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protocol=protocol,
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protocol=protocol,
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)
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)
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@method
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def bin_pacc(c_model, validation, protocol) -> EvaluationReport:
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est = BQAE(c_model, PACC(LogisticRegression(), recalib="bcts"))
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est.fit(validation)
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return evaluation_report(
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estimator=est,
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protocol=protocol,
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)
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@method
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def mul_pacc(c_model, validation, protocol) -> EvaluationReport:
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est = MCAE(c_model, PACC(LogisticRegression(), recalib="bcts"))
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est.fit(validation)
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return evaluation_report(
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estimator=est,
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protocol=protocol,
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)
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@method
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def bin_pacc_gs(c_model, validation, protocol) -> EvaluationReport:
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v_train, v_val = validation.split_stratified(0.6, random_state=0)
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model = BQAE(c_model, PACC(LogisticRegression()))
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est = GridSearchAE(
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model=model,
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param_grid={
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"q__classifier__C": np.logspace(-3, 3, 7),
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"q__classifier__class_weight": [None, "balanced"],
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"q__recalib": [None, "bcts", "vs"],
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},
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refit=False,
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protocol=UPP(v_val, repeats=100),
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verbose=False,
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).fit(v_train)
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return evaluation_report(
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estimator=est,
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protocol=protocol,
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)
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@method
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def mul_pacc_gs(c_model, validation, protocol) -> EvaluationReport:
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v_train, v_val = validation.split_stratified(0.6, random_state=0)
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model = MCAE(c_model, PACC(LogisticRegression()))
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est = GridSearchAE(
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model=model,
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param_grid={
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"q__classifier__C": np.logspace(-3, 3, 7),
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"q__classifier__class_weight": [None, "balanced"],
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"q__recalib": [None, "bcts", "vs"],
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},
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refit=False,
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protocol=UPP(v_val, repeats=100),
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verbose=False,
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).fit(v_train)
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return evaluation_report(
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estimator=est,
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protocol=protocol,
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method_name="bin_sld_gs",
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)
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