Table 10.

Other performance metrics and their 95% confidence intervals for binary classifiers on the validation data set

Model	AUC	Accuracy (%)	Sensitivity (%)	Specificity (%)	Positive predictive value (%)	Negative predictive value (%)
PLR	0.5846 (0.4523–0.7169)	72.22 (62.78–80.41)	86.75 (77.52–93.19)	24.00 (9.36–45.13)	79.12 (69.33–86.94)	35.29 (14.21–61.67)
SVM	0.639 (0.5085–0.7696)	75 (65.75–0.82.83)	87.95 (78.96–94.07)	32.00 (14.95–53.5)	81.11 (71.49–88.59)	44.44 (21.53–69.24)
RF	0.6733 (0.5508–0.7957)	78.7 (69.78–86)	97.59 (91.57–99.71)	16.00 (4.54–36.08)	79.41 (70.27–86.78)	66.67 (22.28–95.67)

PLR = penalized logistic regression; SVM = support vector machine; RF = random Forest; AUC = area under the curve.