Table 2.

Evaluation assessment between our proposed ensemble method and individual classifiers based on an independent test set.

Method	MCC	ACC	SN	SP	AUC	p-Value
4mCpred-EL	0.596 ± 0.022	0.798 ± 0.011	0.804 ± 0.012	0.792 ± 0.028	0.897 ± 0.008	—
RF	0.562 ± 0.010	0.780 ± 0.005	0.736 ± 0.008	0.824 ± 0.014	0.862 ± 0.002	0.179
ERT	0.552 ± 0.012	0.775 ± 0.006	0.736 ± 0.008	0.814 ± 0.008	0.862 ± 0.011	0.179
SVM	0.544 ± 0.014	0.772 ± 0.007	0.742 ± 0.014	0.801 ± 0.009	0.870 ± 0.007	0.293
GB	0.544 ± 0.011	0.772 ± 0.005	0.743 ± 0.011	0.800 ± 0.020	0.862 ± 0.004	0.179
LR	0.536 ± 0.013	0.768 ± 0.006	0.753 ± 0.005	0.783 ± 0.010	0.863 ± 0.003	0.191
AB	0.524 ± 0.009	0.762 ± 0.005	0.747 ± 0.006	0.776 ± 0.008	0.793 ± 0.017	0.000371
KNN	0.508 ± 0.017	0.747 ± 0.008	0.625 ± 0.006	0.868 ± 0.012	0.826 ± 0.005	0.010668

Note: p < 0.05 shows a statistically significant difference between 4mCpred-EL and other method that is depicted in bold. Values are expressed as mean ± standard deviation.