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18 lines
449 B
Python
18 lines
449 B
Python
from sklearn.datasets import make_classification
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def load_dataset(random_state=0, n_classes=2, n_features=3, n_samples=1500):
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X, y = make_classification(
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n_samples=n_samples,
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n_features=n_features,
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n_informative=3,
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n_redundant=0,
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n_repeated=0,
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n_classes=n_classes,
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n_clusters_per_class=2,
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class_sep=1.5,
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flip_y=0,
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random_state=random_state,
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)
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return X, y
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