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

BMC Bioinformatics

Table 3 Lung cancer data classification performance

	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

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.

ISSN: 1471-2105