test_svm.py 文件源码

def test_decision_function_shape_two_class():
    for n_classes in [2, 3]:
        X, y = make_blobs(centers=n_classes, random_state=0)
        for estimator in [svm.SVC, svm.NuSVC]:
            clf = OneVsRestClassifier(estimator(
                decision_function_shape="ovr")).fit(X, y)
            assert_equal(len(clf.predict(X)), len(y))