test_model_selection.py 文件源码

def test_w_prep_fit():
    """[Model Selection] Test run with preprocessing, single step."""
    evl = Evaluator(mape_scorer, cv=5, shuffle=False, random_state=100,
                    verbose=True)

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

        evl.fit(X, y,
                estimators=[OLS()],
                param_dicts={'ols': {'offset': randint(1, 10)}},
                preprocessing={'pr': [Scale()], 'no': []},
                n_iter=3)

    np.testing.assert_approx_equal(
            evl.results['test_score-m']['no.ols'],
            -24.903229451043195)

    np.testing.assert_approx_equal(
            evl.results['test_score-m']['pr.ols'],
            -26.510708862278072, 1)

    assert evl.results['params']['no.ols']['offset'] == 4
    assert evl.results['params']['pr.ols']['offset'] == 4