def test_fit_linear_multi():
for data in (mult_dense, mult_sparse):
clf = LinearSVC(random_state=0)
clf.fit(data, mult_target)
y_pred = clf.predict(data)
acc = np.mean(y_pred == mult_target)
assert_greater(acc, 0.85)
def test_fit_linear_multi():
for data in (mult_dense, mult_sparse):
clf = LinearSVC(random_state=0)
clf.fit(data, mult_target)
y_pred = clf.predict(data)
acc = np.mean(y_pred == mult_target)
assert_greater(acc, 0.85)
def test_fit_linear_multi(data, request):
X, y = request.getfixturevalue(data)
clf = LinearSVC(random_state=0)
clf.fit(X, y)
assert list(clf.classes_) == [0, 1, 2]
y_pred = clf.predict(X)
acc = np.mean(y_pred == y)
assert acc > 0.85
def test_fit_linear_multi():
for data in (mult_dense, mult_sparse):
clf = LinearSVC(random_state=0)
clf.fit(data, mult_target)
assert list(clf.classes_) == [0, 1, 2]
y_pred = clf.predict(data)
acc = np.mean(y_pred == mult_target)
assert acc > 0.85
