Table 3.

Results of unsupervised learning algorithms on stress recognition in automobile drivers dataset.

Datasets	Classifiers	Feature	Test-train split	Classification accuracy	Precision	Recall	F1-score
Stress recognition in automobile drivers dataset	Affinity propagation	Heart rate and respiratory rate		63.8%	0.65	0.64	0.62
	BIRCH			54.9%	0.62	0.57	0.50
	DBSCAN			53.8%	0.56	0.54	0.41
	K-mean			55.7%	0.62	0.56	0.52
	Mini-batch K-mean			53.0%	0.28	0.53	0.37
	Mean shift			53.0%	0.28	0.53	0.37
	OPTICS			54.1%	0.54	0.54	0.53
Stress recognition in automobile drivers dataset	Affinity propagation	Heart rate		59.7%	0.60	0.82	0.69
	BIRCH			49.1%	0.66	0.49	0.38
	DBSCAN			54.7%	0.30	0.55	0.39
	K-mean		70-30 %	55.5%	0.61	0.55	0.53
	Mini-batch K-mean			54.8%	0.61	0.55	0.52
	Mean shift			54.7%	0.30	0.55	0.39
	OPTICS			51.6%	0.51	0.52	0.51
Stress recognition in automobile drivers dataset	Affinity propagation	Respiratory rate		65.0%	0.77	0.65	0.57
	BIRCH			57.4%	0.33	0.57	0.42
	DBSCAN			60.6%	0.62	0.61	0.53
	K-mean			59.8%	0.63	0.60	0.60
	Mini-batch K-mean			60.3%	0.6	0.60	0.60
	Mean shift			57.4%	0.33	0.57	0.42
	OPTICS			54.6%	0.49	0.55	0.46