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Table 6 Prostate cancer data classification performance (prostate cancer vs. BPH)

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

  Cross-validation error Kappa Sensitivity AUC
GDFS 0.532 -0.298 0.618 0.274
rpart 0.553 -0.037 0.412 0.371
  1. 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.
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BMC Bioinformatics

ISSN: 1471-2105

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