test_model_selection_sklearn.py 文件源码

def test_search_cv_results_none_param():
    X, y = [[1], [2], [3], [4], [5]], [0, 0, 0, 0, 1]
    estimators = (DecisionTreeRegressor(), DecisionTreeClassifier())
    est_parameters = {"random_state": [0, None]}
    cv = KFold(random_state=0)

    for est in estimators:
        grid_search = dcv.GridSearchCV(est, est_parameters, cv=cv).fit(X, y)
        assert_array_equal(grid_search.cv_results_['param_random_state'],
                           [0, None])