Esempio n. 1
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def test_digits_sqrt_lazy():
	model = FeatureBasedSelection(100, 'sqrt', optimizer='lazy')
	model.fit(X_digits)
	assert_array_equal(model.ranking, digits_sqrt_ranking)
	assert_array_almost_equal(model.gains, digits_sqrt_gains, 4)
	assert_array_almost_equal(model.subset, X_digits[model.ranking])
Esempio n. 2
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def test_digits_sigmoid_two_stage():
	model = FeatureBasedSelection(100, 'sigmoid', optimizer='two-stage')
	model.fit(X_digits)
	assert_array_equal(model.ranking, digits_sigmoid_ranking)
	assert_array_almost_equal(model.gains, digits_sigmoid_gains, 4)
	assert_array_almost_equal(model.subset, X_digits[model.ranking])
Esempio n. 3
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def test_digits_inverse_large_greedy():
    model = FeatureBasedSelection(100, 'inverse', 100)
    model.fit(X_digits)
    assert_array_equal(model.ranking, digits_inverse_ranking)
    assert_array_almost_equal(model.gains, digits_inverse_gains, 4)
Esempio n. 4
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def test_digits_sqrt_select_biggest_first():
    model = FeatureBasedSelection(10, 'sqrt', 10)
    model.fit(X_digits)
    assert_equal(model.ranking[0], int(X_digits.sum(axis=1).argmax()))
Esempio n. 5
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def test_digits_inverse_small_greedy():
    model = FeatureBasedSelection(10, 'inverse', 10)
    model.fit(X_digits)
    assert_array_equal(model.ranking, digits_inverse_ranking[:10])
    assert_array_almost_equal(model.gains, digits_inverse_gains[:10], 4)