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19 lines
646 B
19 lines
646 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.linalg import norm
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from miplearn.classifiers.counting import CountingClassifier
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E = 0.1
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def test_counting():
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clf = CountingClassifier()
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clf.fit(np.zeros((8, 25)), [0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0])
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expected_proba = np.array([[0.375, 0.625], [0.375, 0.625]])
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actual_proba = clf.predict_proba(np.zeros((2, 25)))
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assert norm(actual_proba - expected_proba) < E
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