def test_simple(self):
km = ClusterKMeans(self.user_ink_data,
min_cluster_size=10)
clustered_data = km.clustered_data()
chmm = ClassifierHMM()
chmm.train(clustered_data)
accuracy,_,_ = chmm.test(self.label_ink_pairs)
self.assertGreater(accuracy, 94.0)
def test_specific_target(self):
km = ClusterKMeans(self.user_ink_data,
target_user_id='user_1',
min_cluster_size=10)
clustered_data = km.clustered_data()
chmm = ClassifierHMM()
chmm.train(clustered_data)
accuracy,_,_ = chmm.test(self.label_ink_pairs)
self.assertGreater(accuracy, 95.0)
def test_optimize(self):
km = ClusterKMeans(self.user_ink_data,
min_cluster_size=10)
km.optimize_cluster_num(self.label_ink_pairs, verbose=False)
clustered_data = km.clustered_data()
chmm = ClassifierHMM()
chmm.train(clustered_data)
accuracy,_,_ = chmm.test(self.label_ink_pairs)
self.assertGreater(accuracy, 94.0)
def test_simple(self):
cHMM = ClassifierHMM(min_cluster_size=10)
cHMM.train(self.clustered_data)
accuracy,_,_ = cHMM.test(self.label_ink_pairs)
if VERBOSE: print accuracy, 92
self.assertGreater(accuracy, 92.0)
