test_ch3.py 文件源码

def test_least_square_model(prostate_data):
    from esl_model.ch3.models import LeastSquareModel
    train_x, train_y, test_x, test_y, features = prostate_data
    lsm = LeastSquareModel(train_x=train_x, train_y=train_y, features_name=features)
    lsm.pre_processing()

    lsm.train()

    print(lsm.beta_hat)
    print('rss:',lsm.rss)
    print('F-statistic', lsm.F_statistic(remove_cols=['age', 'lcp', 'gleason', 'pgg45']))
    print('z-score', lsm.z_score)

    result = lsm.test(test_x, test_y)

    print('test error: ', result.mse)

    from sklearn.linear_model import LinearRegression

    lr = LinearRegression()

    lr.fit(train_x, train_y)
    print('std error', result.std_error)
    assert np.isclose(result.mse, np.mean(((lr.predict(test_x)) - test_y) **2))