Table 2.

A comparison of the proposed predictor with other ML-based methods on training dataset.

Methods	MCC	ACC	Sensitivity	Specificity	AUC	P-value
PVP-SVM	0.695	0.870	0.737	0.933	0.900
PVPred	NA	0.850	0.758	0.894	0.899	0.974
RF	0.600	0.831	0.657	0.914	0.877	0.476
ERT	0.614	0.837	0.636	0.933	0.883	0.594

The first column represents the method name employed in this study. The second, the third, the fourth and the fifth respectively represent the MCC, accuracy, sensitivity, and specificity. The sixth column and the seventh represent the AUC and pairwise comparison of ROC area under curves (AUCs) between PVP-SVM and the other methods using a two-tailed t-test.