|
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.