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41 lines
956 B
41 lines
956 B
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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import numpy as np
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from numpy.testing import assert_array_equal
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from sklearn.neighbors import KNeighborsClassifier
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from miplearn import ScikitLearnClassifier
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def test_constant_prediction():
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x_train = np.array(
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[
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[0.0, 1.0],
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[1.0, 0.0],
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]
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)
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y_train = np.array(
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[
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[True, False],
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[True, False],
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]
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)
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clf = ScikitLearnClassifier(
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KNeighborsClassifier(
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n_neighbors=1,
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)
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)
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clf.fit(x_train, y_train)
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proba = clf.predict_proba(x_train)
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assert_array_equal(
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proba,
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np.array(
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[
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[1.0, 0.0],
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[1.0, 0.0],
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]
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),
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)
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