Table 4A.

Results of supervised learning algorithms on SWELL-KW dataset.

Datasets	Classifiers	Feature	Test-train split	Classification accuracy	Precision	Recall	F1-score
SWELL-KW dataset	Logistic regression	Heart rate	70-30 %	70.2%	0.70	0.70	0.64
	Gaussian naive bayes			70.3%	0.70	0.70	0.64
	Decision tree			74.8%	0.74	0.75	0.73
	Random forest			74.8%	0.74	0.75	0.73
	AdaBoost			74.6%	0.75	0.75	0.71
	KNN = 5			71.8%	0.71	0.72	0.71
	KNN = 2			62.7%	0.68	0.63	0.64