Table 9.

Classification Report of Feature Selection with different k values and Oversampling.

Model	k	Accuracy	Precision	F1 Score	TPR	TNR	auROC	auPR	MCC
SVM	20	88.86	88.75	0.888	0.64	0.93	0.877	0.665	0.5747
	15	88.61	89.07	0.8882	0.61	0.94	0.869	0.67	0.5769
	10	88.21	88.88	0.885	0.6	0.94	0.854	0.641	0.5756
RF	20	89.48	89.72	0.8959	0.65	0.94	0.933	0.737	0.6069
	15	89.13	89.67	0.8936	0.63	0.94	0.93	0.722	0.6072
	10	88.51	89.31	0.8884	0.61	0.94	0.923	0.701	0.6069
MLP	20	87.92	88.28	0.8808	0.6	0.93	0.881	0.611	0.5347
	15	86.32	88.68	0.8715	0.54	0.95	0.892	0.624	0.5542
	10	87.32	88.27	0.8766	0.47	0.94	0.863	0.647	0.576
DT	20	87.29	90.15	0.882	0.56	0.96	0.919	0.705	0.6009
	15	88.38	89.68	0.8887	0.6	0.95	0.921	0.699	0.6059
	10	89.16	90.32	0.8959	0.62	0.95	0.922	0.693	0.6046
XGBoost	20	90.32	89.82	0.8998	0.72	0.93	0.937	0.754	0.6269
	15	90.21	89.97	0.9008	0.7	0.94	0.935	0.754	0.6069
	10	89.86	89.72	0.8979	0.68	0.94	0.933	0.734	0.6029