

def test_most_frequent_and_prior_strategy_multioutput():
    X = [[0], [0], [0], [0]]
    y = np.array([[1, 0], [2, 0], [1, 0], [1, 3]])
    n_samples = len(X)
    for strategy in ('prior', 'most_frequent'):
        clf = DummyClassifier(strategy=strategy, random_state=0)
        clf.fit(X, clf)
        assert_array_equal(clf.predict(X), np.hstack([np.ones((n_samples, 1)), np.zeros((n_samples, 1))]))
        _check_predict_proba(clf, X, y)
        _check_behavior_2d(clf)

dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/tests/test_dummy.py test_most_frequent_and_prior_strategy_multioutput/VarMisuse@99/119 `y`->`clf`