Table 2

The performance evaluation of the feature subsets selected by different filter feature selection methods

IG

CHI

ReliefF

CFS


Peformance

200

300

200

300

200

300

200

300


Specificity

0.759

0.759

0.755

0.76

0.751

0.772

0.733

0.746

Sensitivity

0.704

0.718

0.707

0.704

0.718

0.743

0.727

0.731

F-measure

0.73

0.738

0.73

0.731

0.734

0.757

0.73

0.738

ROC score

0.74

0.745

0.738

0.741

0.74

0.762

0.731

0.741


Based on the feature subsets selected by four filter feature selection methods, we respectively build SVM classifiers and compare the performance of these classifiers.

Gan et al. BMC Bioinformatics 2012 13:4   doi:10.1186/1471-2105-13-4

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