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added max_train_instances to fetch_UCIMulticlassLabelledCollection

This commit is contained in:
Alejandro Moreo Fernandez 2024-04-12 18:24:12 +02:00
parent 4abec6629b
commit e0b80167b9
2 changed files with 21 additions and 5 deletions
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2
examples/ucimulti_experiments.py
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@ -29,7 +29,7 @@ def wrap_hyper(classifier_hyper_grid:dict):
METHODS = [
('PACC', PACC(newLR()), wrap_hyper(logreg_grid)),
('EMQ', EMQ(newLR()), wrap_hyper(logreg_grid)),
('KDEy-ML', KDEyML(newLR()), {**wrap_hyper(logreg_grid), **{'bandwidth': np.linspace(0.01, 0.2, 20)}}),
# ('KDEy-ML', KDEyML(newLR()), {**wrap_hyper(logreg_grid), **{'bandwidth': np.linspace(0.01, 0.2, 20)}}),
]

24
quapy/data/datasets.py
View File

@ -591,7 +591,13 @@ def fetch_UCIBinaryLabelledCollection(dataset_name, data_home=None, verbose=Fals
return data
def fetch_UCIMulticlassDataset(dataset_name, data_home=None, test_split=0.3, min_class_support=100, verbose=False) -> Dataset:
def fetch_UCIMulticlassDataset(
dataset_name,
data_home=None,
min_test_split=0.3,
max_train_instances=25000,
min_class_support=100,
verbose=False) -> Dataset:
"""
Loads a UCI multiclass dataset as an instance of :class:`quapy.data.base.Dataset`.
@ -613,14 +619,24 @@ def fetch_UCIMulticlassDataset(dataset_name, data_home=None, test_split=0.3, min
:param dataset_name: a dataset name
:param data_home: specify the quapy home directory where collections will be dumped (leave empty to use the default
~/quay_data/ directory)
:param test_split: proportion of documents to be included in the test set. The rest conforms the training set
:param min_test_split: minimum proportion of instances to be included in the test set. This value is interpreted
as a minimum proportion, meaning that the real proportion could be higher in case the training proportion
(1-`min_test_split`% of the instances) surpasses `max_train_instances`. In such case, only `max_train_instances`
are taken for training, and the rest (irrespective of `min_test_split`) is taken for test.
:param max_train_instances: maximum number of instances to keep for training (defaults to 25000)
:param min_class_support: minimum number of istances per class. Classes with fewer instances
are discarded (deafult is 100)
:param verbose: set to True (default is False) to get information (stats) about the dataset
:return: a :class:`quapy.data.base.Dataset` instance
"""
data = fetch_UCIMulticlassLabelledCollection(dataset_name, data_home, min_class_support, verbose=verbose)
return Dataset(*data.split_stratified(1 - test_split, random_state=0))
n = len(data)
train_prop = (1.-min_test_split)
n_train = int(n*train_prop)
if n_train > max_train_instances:
train_prop = (max_train_instances / n)
return Dataset(*data.split_stratified(train_prop, random_state=0))
def fetch_UCIMulticlassLabelledCollection(dataset_name, data_home=None, min_class_support=100, verbose=False) -> LabelledCollection:
@ -645,7 +661,7 @@ def fetch_UCIMulticlassLabelledCollection(dataset_name, data_home=None, min_clas
:param dataset_name: a dataset name
:param data_home: specify the quapy home directory where the dataset will be dumped (leave empty to use the default
~/quay_data/ directory)
:param test_split: proportion of documents to be included in the test set. The rest conforms the training set
:param test_split: proportion of instances to be included in the test set. The rest conforms the training set
:param min_class_support: minimum number of istances per class. Classes with fewer instances
are discarded (deafult is 100)
:param verbose: set to True (default is False) to get information (stats) about the dataset