def test_fit_linear_binary(): for data in (bin_dense, bin_csr): for loss in ("l1", "l2"): clf = LinearSVC(loss=loss, random_state=0, max_iter=10) clf.fit(data, bin_target) assert_equal(clf.score(data, bin_target), 1.0) y_pred = clf.decision_function(data).ravel()
def test_fit_linear_binary(data, loss, request): X, y = request.getfixturevalue(data) clf = LinearSVC(loss=loss, random_state=0, max_iter=10) clf.fit(X, y) assert list(clf.classes_) == [0, 1] assert clf.score(X, y) == 1.0 y_pred = clf.decision_function(X).ravel()