Table 6.

Prostate cancer data classification performance (prostate cancer vs. BPH)

	Cross-validation error	Kappa	Sensitivity	AUC
GDFS	0.532	-0.298	0.618	0.274
rpart	0.553	-0.037	0.412	0.371

Evaluation of classification performance from feature selection in the prostate cancer dataset (prostate cancer vs. BPH cases) for the proposed GDFS method (GDFS), correlation-based feature selection (CFS), and recursive partitioning (rpart). Reported are the cross-validation error (misclassification rate), Cohen’s kappa statistic, sensitivity, and AUC (corresponding to ROC curves in Figure 8) for the statistical classifications from each method.