Table 5.

Performance comparison of the best-trained model for all ML.

ML	DA	KNN	DT	SVM	ANN
No. of features	6	7	4	6	6
Setting	Type = Linear	k = 7	Split = 1	Kernel = Linear	HN1 = 9 HN2 = 13
Val MSE	0.4167	0.3077	0.4615	0.3333	0.1538
Val ACC	58.33	69.23	53.85	66.67	84.62
Test MSE	0.0909	0.0455	0.0455	0.0909	0.0455
Test SP	90.91	100.00	90.91	90.91	90.91
Test SN	90.91	90.91	100.00	90.91	100.00
Test ACC	90.91	95.45	95.45	90.91	95.45
AUC	0.9174	0.9752	0.9463	0.8926	0.9587

k, number of neighbors, Val, validation, HN, hidden nodes.