59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
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# Fabian Pedregosa <fabian.pedregosa@inria.fr>
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#
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# License: BSD Style.
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import numpy as np
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from sklearn.utils.testing import assert_array_equal
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from sklearn.utils.testing import SkipTest
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from sklearn.linear_model.bayes import BayesianRidge, ARDRegression
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from sklearn import datasets
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def test_bayesian_on_diabetes():
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"""
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Test BayesianRidge on diabetes
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"""
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raise SkipTest("XFailed Test")
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diabetes = datasets.load_diabetes()
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X, y = diabetes.data, diabetes.target
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clf = BayesianRidge(compute_score=True)
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# Test with more samples than features
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clf.fit(X, y)
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# Test that scores are increasing at each iteration
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assert_array_equal(np.diff(clf.scores_) > 0, True)
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# Test with more features than samples
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X = X[:5, :]
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y = y[:5]
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clf.fit(X, y)
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# Test that scores are increasing at each iteration
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assert_array_equal(np.diff(clf.scores_) > 0, True)
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def test_toy_bayesian_ridge_object():
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"""
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Test BayesianRidge on toy
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"""
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X = np.array([[1], [2], [6], [8], [10]])
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Y = np.array([1, 2, 6, 8, 10])
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clf = BayesianRidge(compute_score=True)
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clf.fit(X, Y)
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X_test = [[1], [3], [4]]
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assert(np.abs(clf.predict(X_test) - [1, 3, 4]).sum() < 1.e-2) # identity
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def test_toy_ard_object():
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"""
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Test BayesianRegression ARD classifier
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"""
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X = np.array([[1], [2], [3]])
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Y = np.array([1, 2, 3])
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clf = ARDRegression(compute_score=True)
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clf.fit(X, Y)
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test = [[1], [3], [4]]
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assert(np.abs(clf.predict(test) - [1, 3, 4]).sum() < 1.e-3) # identity
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