test_polynomial_network.py 文件源码

def check_improve(degree):
    y = _lifted_predict(U[:degree], X)

    common_settings = dict(degree=degree, n_components=n_components,
                           beta=1e-10, tol=0, random_state=0)

    est_5 = PolynomialNetworkRegressor(max_iter=5, **common_settings)
    est_10 = PolynomialNetworkRegressor(max_iter=10, **common_settings)

    with warnings.catch_warnings():
        warnings.simplefilter("ignore")
        est_5.fit(X, y)
        est_10.fit(X, y)

    y_pred_5 = est_5.predict(X)
    y_pred_10 = est_10.predict(X)

    assert_less_equal(mean_squared_error(y, y_pred_10),
                      mean_squared_error(y, y_pred_5),
                      msg="More iterations do not improve fit.")