test_model_selection_sklearn.py 文件源码

def test_no_refit_multiple_metrics():
    clf = DecisionTreeClassifier()
    scoring = {'score_1': 'accuracy', 'score_2': 'accuracy'}

    gs = dcv.GridSearchCV(clf, {'max_depth': [1, 2, 3]}, refit=False,
                          scoring=scoring)
    gs.fit(da_X, da_y)
    assert not hasattr(gs, "best_estimator_")
    assert not hasattr(gs, "best_index_")
    assert not hasattr(gs, "best_score_")
    assert not hasattr(gs, "best_params_")

    for fn_name in ('predict', 'predict_proba', 'predict_log_proba'):
        with pytest.raises(NotFittedError) as exc:
            getattr(gs, fn_name)(X)
        assert (('refit=False. %s is available only after refitting on the '
                 'best parameters' % fn_name) in str(exc.value))