Skip to main content

Table 3 Lung cancer data classification performance

From: Greedy feature selection for glycan chromatography data with the generalized Dirichlet distribution

  Cross-validation error Kappa Sensitivity AUC
GDFS 0.255 0.493 0.680 0.830
CFS 0.315 0.378 0.600 0.757
rpart 0.266 0.478 0.610 0.562
  1. Evaluation of classification performance from feature selection in the lung cancer dataset (control vs. cancer 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 4) for the statistical classifications from each method.