def test_specific_user(self): link = ClusterLinkage(self.user_ink_data, target_user_id='user_1') clustered_data = link.clustered_data() cdtw = ClassifierDTW() cdtw.train(clustered_data) accuracy,_,_ = cdtw.test(self.label_ink_pairs) self.assertGreater(accuracy, 91.0)
def test_simple(self): link = ClusterLinkage(self.user_ink_data) clustered_data = link.clustered_data() cdtw = ClassifierDTW() cdtw.train(clustered_data) accuracy,_,_ = cdtw.test(self.label_ink_pairs) self.assertGreater(accuracy, 92.0)
def test_state_reduction(self): cDTW = ClassifierDTW(alpha=0.5,min_cluster_size=10) cDTW.train(self.clustered_data,center_type='medoid', state_reduction=True) accuracy,_,_ = cDTW.test(self.label_ink_pairs) if VERBOSE: print accuracy, 87 self.assertGreater(accuracy, 87.0)
def test_simple(self): km = ClusterKMeans(self.user_ink_data,algorithm='dtw') clustered_data = km.clustered_data() cDTW = ClassifierDTW() cDTW.train(clustered_data, center_type='centroid') accuracy,_,_ = cDTW.test(self.label_ink_pairs) self.assertGreater(accuracy, 93.0)
def test_optimize(self): km = ClusterKMeans(self.user_ink_data,algorithm='dtw') km.optimize_cluster_num(self.label_ink_pairs, verbose=False) clustered_data = km.clustered_data() cDTW = ClassifierDTW() cDTW.train(clustered_data, center_type='centroid') accuracy,_,_ = cDTW.test(self.label_ink_pairs) self.assertGreater(accuracy, 93.0)