test_ridge.py 文件源码

def test_ridge_fit_intercept_sparse():
    X, y = make_regression(n_samples=1000, n_features=2, n_informative=2,
                           bias=10., random_state=42)
    X_csr = sp.csr_matrix(X)

    dense = Ridge(alpha=1., tol=1.e-15, solver='sag', fit_intercept=True)
    sparse = Ridge(alpha=1., tol=1.e-15, solver='sag', fit_intercept=True)
    dense.fit(X, y)
    sparse.fit(X_csr, y)
    assert_almost_equal(dense.intercept_, sparse.intercept_)
    assert_array_almost_equal(dense.coef_, sparse.coef_)

    # test the solver switch and the corresponding warning
    sparse = Ridge(alpha=1., tol=1.e-15, solver='lsqr', fit_intercept=True)
    assert_warns(UserWarning, sparse.fit, X_csr, y)
    assert_almost_equal(dense.intercept_, sparse.intercept_)
    assert_array_almost_equal(dense.coef_, sparse.coef_)