Table 6.

5-fold and 10-fold cross-validation for two-class classification using different classifiers

Method	Classifier	Mean accuracy	SD	Sensitivity	Specificity	FPR	NPV	PPV
5-fold cross validation for two-class classification	Logistic regression	90.344	0.00793	94.872	86.441	13.55	86.44	94.87
	Linear SVM	88.809	0.00980	95.59	78.407	21.59	87.05	92.13
	Weighted KNN	85.772	0.01041	94.231	69.492	30.50	82	89.09
	Simple tree	82.772	0.02041	98.718	83.051	16.94	96.07	93.90
10-fold cross validation for two-class classification	Logistic regression	90.372	0.00618	94.872	86.441	13.559	86.441	94.872
	Linear SVM	89.06	0.00769	95.622	78.407	21.593	87.142	92.133
	Weighted KNN	86.181	0.00823	94.231	69.492	30.508	82	89.091
	Simple tree	83.823	0.01455	98.718	83.051	16.949	96.078	93.902

SD – Standard deviation; PPV – Positive predictive value; NPV – Negative predictive value; FPR – False predictive rate; SVM – Support vector machine; KNN – K-nearest neighbor