Table 1.

Performance of various machine learning classifiers on benchmark dataset.

Classifier	Sensitivity	Specificity	Accuracy	AUROC	MCC
DT	74.49	87.14	82.77	0.808	0.62
RF	92.04	91.57	91.73	0.977	0.82
XGB	91.90	92.14	92.06	0.980	0.83
KNN	90.15	91.79	91.22	0.958	0.81
GNB	88.66	88.71	88.70	0.955	0.76
SVM	97.44	97.36	97.38	0.996	0.94

The values in the tables are in bold to represent the best performing classifier or method.