sklearn.feature_selection.mutual_info_.mutual_info_regression

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1 Examples 7

Example 1

Project: scikit-learn Source File: test_mutual_info.py
Function: test_mutual_info_regression
def test_mutual_info_regression():
    # We generate sample from multivariate normal distribution, using
    # transformation from initially uncorrelated variables. The zero
    # variables after transformation is selected as the target vector,
    # it has the strongest correlation with the variable 2, and
    # the weakest correlation with the variable 1.
    T = np.array([
        [1, 0.5, 2, 1],
        [0, 1, 0.1, 0.0],
        [0, 0.1, 1, 0.1],
        [0, 0.1, 0.1, 1]
    ])
    cov = T.dot(T.T)
    mean = np.zeros(4)

    np.random.seed(0)
    Z = np.random.multivariate_normal(mean, cov, size=1000)
    X = Z[:, 1:]
    y = Z[:, 0]

    mi = mutual_info_regression(X, y, random_state=0)
    assert_array_equal(np.argsort(-mi), np.array([1, 2, 0]))