| 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.