test_mlp.py 文件源码

def test_partial_fit_regression():
    # Test partial_fit on regression.
    # `partial_fit` should yield the same results as 'fit' for regression.
    X = Xboston
    y = yboston

    for momentum in [0, .9]:
        mlp = MLPRegressor(algorithm='sgd', max_iter=100, activation='relu',
                           random_state=1, learning_rate_init=0.01,
                           batch_size=X.shape[0], momentum=momentum)
        with warnings.catch_warnings(record=True):
            # catch convergence warning
            mlp.fit(X, y)
        pred1 = mlp.predict(X)
        mlp = MLPRegressor(algorithm='sgd', activation='relu',
                           learning_rate_init=0.01, random_state=1,
                           batch_size=X.shape[0], momentum=momentum)
        for i in range(100):
            mlp.partial_fit(X, y)

        pred2 = mlp.predict(X)
        assert_almost_equal(pred1, pred2, decimal=2)
        score = mlp.score(X, y)
        assert_greater(score, 0.75)