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)