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21 lines
759 B
21 lines
759 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 miplearn.classifiers.evaluator import ClassifierEvaluator
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from sklearn.neighbors import KNeighborsClassifier
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def test_evaluator():
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clf_a = KNeighborsClassifier(n_neighbors=1)
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clf_b = KNeighborsClassifier(n_neighbors=2)
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x_train = np.array([[0, 0], [1, 0]])
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y_train = np.array([0, 1])
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clf_a.fit(x_train, y_train)
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clf_b.fit(x_train, y_train)
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ev = ClassifierEvaluator()
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assert ev.evaluate(clf_a, x_train, y_train) == 1.0
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assert ev.evaluate(clf_b, x_train, y_train) == 0.5
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