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()
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()