Table 2.

Validated predictive performance of best classifiers.

	Method	Accuracy	Sensitivity	Specificity	PPV	NPV	AUC
Dataset 1	LOOCV	0.75 ± 0.04	0.74 ± 0.05	0.76 ± 0.05	0.76 ± 0.04	0.75 ± 0.04	0.76 ± 0.02
	2-Fold	0.59 ± 0.1	0.63 ± 0.14	0.43 ± 0.2	0.81 ± 0.04	0.24 ± 0.12	0.56 ± 0.1
	4-Fold	0.62 ± 0.07	0.63 ± 0.1	0.58 ± 0.12	0.85 ± 0.03	0.3 ± 0.06	0.65 ± 0.06
	6-Fold	0.64 ± 0.05	0.66 ± 0.05	0.58 ± 0.13	0.85 ± 0.04	0.31 ± 0.06	0.67 ± 0.06
	8-Fold	0.7 ± 0.04	0.7 ± 0.04	0.71 ± 0.06	0.9 ± 0.02	0.39 ± 0.04	0.72 ± 0.03
Dataset 2	LOOCV	0.66 ± 0.06	0.95 ± 0.05	0.37 ± 0.1	0.6 ± 0.04	0.88 ± 0.1	0.89 ± 0.05
	2-Fold	0.72 ± 0.07	0.95 ± 0.06	0.13 ± 0.22	0.74 ± 0.05	0.42 ± 0.41	0.68 ± 0.16
	4-Fold	0.78 ± 0.04	0.95 ± 0.05	0.34 ± 0.15	0.79 ± 0.03	0.81 ± 0.2	0.86 ± 0.06
Datasets 1 & 2	LOOCV	0.69 ± 0.05	0.62 ± 0.09	0.75 ± 0.09	0.72 ± 0.07	0.67 ± 0.05	0.78 ± 0.04
	2-Fold	0.64 ± 0.13	0.6 ± 0.17	0.75 ± 0.12	0.87 ± 0.09	0.38 ± 0.08	0.73 ± 0.11
	4-Fold	0.69 ± 0.01	0.67 ± 0.02	0.77 ± 0.01	0.91 ± 0.01	0.41 ± 0.01	0.77 ± 0.04
	6-Fold	0.7 ± 0.02	0.68 ± 0.02	0.77 ± 0.01	0.91 ± 0.01	0.42 ± 0.02	0.79 ± 0.02
	8-Fold	0.7 ± 0.01	0.68 ± 0.02	0.77 ± 0.01	0.91 ± 0.01	0.42 ± 0.02	0.79 ± 0.02
	10-Fold	0.7 ± 0.01	0.68 ± 0.02	0.77 ± 0.01	0.91 ± 0.01	0.42 ± 0.01	0.8 ± 0.02
	12-Fold	0.69 ± 0.01	0.67 ± 0.02	0.77 ± 0.01	0.91 ± 0.01	0.41 ± 0.01	0.79 ± 0.01

PPV: Positive Predictive Value. NPV: Negative Predictive value. AUC: Area under curve.