test_model_selection.py 文件源码

def test_w_prep_list_fit():
    """[Model Selection] Test run with preprocessing as list."""
    evl = Evaluator(
        mape_scorer, cv=5, shuffle=False, random_state=100, verbose=2)

    with open(os.devnull, 'w') as f, redirect_stdout(f):

        evl.fit(X, y,
                estimators=[OLS()],
                param_dicts={'ols': {'offset': randint(1, 10)}},
                preprocessing=[Scale()], n_iter=3)

    np.testing.assert_approx_equal(
            evl.results['test_score-m']['pr.ols'],
            -26.510708862278072)

    assert evl.results['params']['pr.ols']['offset'] == 4