Table 5

Generic feature selection (gene-level)

# Method

# Selected Genes

Accuracy

Avg Subrank

Median

Avg

σ

Iqr


IG

22

90.2

81.5

18.1

30.7

15.0

IG

228

89.8

82.0

17.9

30.3

14.5

SVM-RFE

228

88.3

82.3

16.7

28.5

16.4

SVM-RFE

22

88.0

82.1

17.2

30.4

16.2


Performance of the baseline classification method equipped with a feature-selection step prior to learning. Features (genes) are ranked by the information gain and SVM-RFE heuristics. The number of selected top-ranking genes (22 and 228, respectively) corresponds to the mean number of unique genes acting in gene sets selected in the 1 and 1:10 (respectively) alternatives of the set-level workflow.

Holec et al. BMC Bioinformatics 2012 13(Suppl 10):S15   doi:10.1186/1471-2105-13-S10-S15

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