class AgglomerativeAverageGroupEuclideanTestSuite(unittest.TestCase):
"""Agglomerative Average-Group with Euclidean Distance test cases."""
@classmethod
def setUpClass(self):
self.filename = './tests/models/agglo-avg-group_euclidean.model'
self.agg = Agglomerative(
linkage="average-group", affinity="euclidean", n_clusters=3)
self.agg.fit_predict(iris_data)
def test_agglo_return_labels_with_type_numpy_array(self):
self.assertIsInstance(self.agg.labels_, ndarray)
print_in_test("Agglomerative (Distance=Euclidean, Linkage=Average-group): %f" %
purity_score(iris_target, self.agg.labels_))
class AgglomerativeSingleManhattanTestSuite(unittest.TestCase):
"""Agglomerative Single with Manhattan Distance test cases."""
@classmethod
def setUpClass(self):
self.filename = './tests/models/agglo-single_manhattan.model'
self.agg = Agglomerative(linkage="single",
affinity="manhattan",
n_clusters=3)
self.agg.fit_predict(iris_data)
def test_agglo_return_labels_with_type_numpy_array(self):
self.assertIsInstance(self.agg.labels_, ndarray)
print_in_test(
"Agglomerative (Distance=Manhattan, Linkage=Single): %f" %
purity_score(iris_target, self.agg.labels_))
def setUpClass(self):
self.filename = './tests/models/agglo-avg-group_euclidean.model'
self.agg = Agglomerative(
linkage="average-group", affinity="euclidean", n_clusters=3)
self.agg.fit_predict(iris_data)
def setUpClass(self):
self.filename = './tests/models/agglo-single_manhattan.model'
self.agg = Agglomerative(linkage="single",
affinity="manhattan",
n_clusters=3)
self.agg.fit_predict(iris_data)