test_gradient_boosting.py 文件源码

def test_probability_log():
    # Predict probabilities.
    clf = GradientBoostingClassifier(n_estimators=100, random_state=1)

    assert_raises(ValueError, clf.predict_proba, T)

    clf.fit(X, y)
    assert_array_equal(clf.predict(T), true_result)

    # check if probabilities are in [0, 1].
    y_proba = clf.predict_proba(T)
    assert_true(np.all(y_proba >= 0.0))
    assert_true(np.all(y_proba <= 1.0))

    # derive predictions from probabilities
    y_pred = clf.classes_.take(y_proba.argmax(axis=1), axis=0)
    assert_array_equal(y_pred, true_result)