def test_classification_kmeans(self):
iris = datasets.load_iris()
X, y = iris.data, iris.target
clr = ClassifierAfterKMeans()
clr.fit(X, y)
acc = clr.score(X, y)
self.assertGreater(acc, 0)
prob = clr.predict_proba(X)
self.assertEqual(prob.shape[1], 3)
dec = clr.decision_function(X)
self.assertEqual(prob.shape, dec.shape)
def test_classification_kmeans(self):
iris = datasets.load_iris()
X, y = iris.data, iris.target
clr = ClassifierAfterKMeans()
try:
clr.fit(X, y)
except AttributeError as e:
if compare_module_version(sklver, "0.24") < 0:
return
raise e
acc = clr.score(X, y)
self.assertGreater(acc, 0)
prob = clr.predict_proba(X)
self.assertEqual(prob.shape[1], 3)
dec = clr.decision_function(X)
self.assertEqual(prob.shape, dec.shape)