a2a7810d41524ee038baf5508ef374e1bc970fd3,lightning/impl/tests/test_sag.py,,test_l1_regularized_saga,#,252

Before Change

    saga = SAGAClassifier(eta=1e-3, alpha=0.0, beta=beta, max_iter=10,
                          penalty="l1", random_state=0)
    pysaga.fit(X_bin, y_bin)
    saga.fit(X_bin, y_bin)
    np.testing.assert_array_almost_equal(pysaga.coef_, saga.coef_)


def test_l2_regularized_saga():

After Change

    y_sparse = np.random.randint(0, high=2, size=100)

    for (X, y) in ((X_bin, y_bin), (X_sparse, y_sparse)):
        for beta in np.logspace(-3, 3, 10):
            pysaga = PySAGAClassifier(eta=1e-3, alpha=0.0, beta=beta,
                                      max_iter=5, penalty="l1", random_state=0)
            saga = SAGAClassifier(eta=1e-3, alpha=0.0, beta=beta, max_iter=5,

Instances