sklearn.feature_selection.GenericUnivariateSelect.fit

Here are the examples of the python api sklearn.feature_selection.GenericUnivariateSelect.fit taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

2 Examples 7

Example 1

Project: scikit-learn Source File: test_feature_select.py
def test_invalid_percentile():
    X, y = make_regression(n_samples=10, n_features=20,
                           n_informative=2, shuffle=False, random_state=0)

    assert_raises(ValueError, SelectPercentile(percentile=-1).fit, X, y)
    assert_raises(ValueError, SelectPercentile(percentile=101).fit, X, y)
    assert_raises(ValueError, GenericUnivariateSelect(mode='percentile',
                                                      param=-1).fit, X, y)
    assert_raises(ValueError, GenericUnivariateSelect(mode='percentile',
                                                      param=101).fit, X, y)

Example 2

Project: scikit-learn Source File: test_feature_select.py
def test_invalid_k():
    X = [[0, 1, 0], [0, -1, -1], [0, .5, .5]]
    y = [1, 0, 1]

    assert_raises(ValueError, SelectKBest(k=-1).fit, X, y)
    assert_raises(ValueError, SelectKBest(k=4).fit, X, y)
    assert_raises(ValueError,
                  GenericUnivariateSelect(mode='k_best', param=-1).fit, X, y)
    assert_raises(ValueError,
                  GenericUnivariateSelect(mode='k_best', param=4).fit, X, y)