

def test_most_frequent_and_prior_strategy():
    X = [[0], [0], [0], [0]]
    y = [1, 2, 1, 1]
    for strategy in ('most_frequent', 'prior'):
        clf = DummyClassifier(strategy=strategy, random_state=0)
        clf.fit(X, y)
        assert_array_equal(clf.predict(X), np.ones(len(X)))
        _check_predict_proba(X, X, y)
        if (strategy == 'prior'):
            assert_array_equal(clf.predict_proba([X[0]]), clf.class_prior_.reshape((1, (- 1))))
        else:
            assert_array_equal(clf.predict_proba([X[0]]), (clf.class_prior_.reshape((1, (- 1))) > 0.5))

dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/tests/test_dummy.py test_most_frequent_and_prior_strategy/VarMisuse@96/119 `clf`->`X`