Table 3.

SVM Classification Performance of Selected Feature Subsets With Different Methods.

Method of Feature Selection	Number of Selected Features	Cross-Validation Cohort (5-Fold Cross-Validation With 100 Bootstrapping Repetitions)			Independent Validation Cohort
		AUC (95% CI)	SEN	SPEC	AUC	SEN	SPEC
WRST	17	0.658 (0.653-0.663)	0.605	0.644	0.736	0.593	0.727
Relief	21	0.644 (0.639-0.648)	0.612	0.625	0.679	0.630	0.636
Logistic regression	20	0.628 (0.624-0.633)	0.621	0.564	0.667	0.630	0.576
χ2 Test	16	0.667 (0.663-0.670)	0.573	0.671	0.733	0.630	0.697
LASSO	22	0.767 (0.763-0.770)	0.686	0.709	0.837	0.667	0.818

Abbreviations: AUC, area under the ROC curve; LASSO, least absolute shrinkage selection operator; SEN, sensitivity; SPEC, specificity; WRST, Wilcoxon rank-sum test.