uncertainty_tests.py 文件源码

def test_score_uncertainty():
    np.random.seed(0)

    df_boston_train, df_boston_test = utils.get_boston_regression_dataset()

    column_descriptions = {
        'MEDV': 'output'
        , 'CHAS': 'categorical'
    }

    df_boston_train, uncertainty_data = train_test_split(df_boston_train, test_size=0.5)

    ml_predictor = Predictor(type_of_estimator='regressor', column_descriptions=column_descriptions)

    ml_predictor.train(df_boston_train, perform_feature_selection=True, train_uncertainty_model=True, uncertainty_data=uncertainty_data)

    uncertainty_score = ml_predictor.score_uncertainty(df_boston_test, df_boston_test.MEDV)

    print('uncertainty_score')
    print(uncertainty_score)

    assert uncertainty_score > -0.2