Table 3.

Comparison between evaluation metrics of XGBoost (XGB), Random Forest (RF), and Support Vector Machine (SVM) classifiers.

	ACC	F1	PREC	AUC ROC	AUPRC
XGB	0.652 (0.017)	0.567 (0.022)	0.613 (0.022)	0.701 (0.015)	0.639 (0.021)
RF	0.673 (0.015)	0.507 (0.030)	0.729 (0.038)	0.699 (0.011)	0.668 (0.016)
SVM	0.633 (0.025)	0.478 (0.091)	0.613 (0.032)	0.663 (0.036)	0.597 (0.037)

The mean values accompanied by the standard deviation are shown. The highest values for each metric are indicated in bold, and the second-highest values are underscored.