Table 1.

Median values for each model and metric color coded by scale.

	AC	SVC	ADA	BNB	DL	KNN	RF
ACC	0.827	0.841	0.811	0.801	0.825	0.829	0.832
AUC	0.887	0.826	0.772	0.766	0.796	0.810	0.807
Cohen’s Kappa	0.627	0.643	0.557	0.540	0.597	0.617	0.616
MCC	0.636	0.646	0.563	0.544	0.604	0.619	0.620
Precision	0.782	0.796	0.775	0.750	0.778	0.765	0.795
Recall	0.833	0.817	0.732	0.730	0.773	0.810	0.775
Specificity	0.841	0.857	0.863	0.845	0.855	0.835	0.868
F1-Score	0.791	0.798	0.749	0.738	0.766	0.785	0.781

AC = Assay Central (Bayesian), rf = Random Forest, knn = k-Nearest Neighbors, svc = Support Vector Classification, bnb = Naïve Bayesian, ada = AdaBoosted Decision Trees, DL = Deep Learning.