Table 6.

The performed accuracy (ACC), precision (PRE), recall (REC), f1-score (F1S), the area under the curve (AUC), and Cohen's Kappa score (CKS) for the UCI dataset.

Feature sets	Classifiers	ACC	PRE	REC	F1S	AUC	CKS
All features	RF	0.9406	0.9523	0.9317	0.9443	0.9802	0.9074
	DT	0.9358	0.9357	0.9334	0.9341	0.9732	0.9005
	KNN	0.9467	0.9494	0.9447	0.9479	0.9870	0.9131
	RDKVT	0.9594	0.9618	0.9510	0.9588	0.9936	0.9192
	RDKST	0.9656	0.9624	0.9695	0.9674	0.9910	0.9526
UVS features	RF	0.9620	0.9704	0.9611	0.9658	0.9883	0.9293
	DT	0.9612	0.9573	0.9661	0.9633	0.9878	0.9210
	KNN	0.9646	0.9707	0.9611	0.9679	0.9886	0.9263
	RDKVT	0.9715	0.9823	0.9696	0.9777	0.9905	0.9394
	RDKST	0.9742	0.9749	0.9725	0.9765	0.9938	0.9486
IGS features	RF	0.9703	0.9781	0.9691	0.9710	0.9920	0.9526
	DT	0.9667	0.9614	0.9717	0.9686	0.9893	0.9488
	KNN	0.9711	0.9635	0.9820	0.9743	0.9911	0.9542
	RDKVT	0.9807	0.9888	0.9776	0.9839	0.9968	0.9610
	RDKST	0.9861	0.9839	0.9894	0.9843	0.9980	0.9732