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Table 1 Performance evaluation, testing FS methods on the ‘binary low-dimension’ dataset

From: GARS: Genetic Algorithm for the identification of a Robust Subset of features in high-dimensional datasets

 

ACC

SEN

SPE

PPV

NPV

AUC

Time

Nfeats

GARS

1

1

1

1

1

1

4 min

14

RFE

0.75

0.75

0.75

0.75

0.75

0.94

1 s

5

SBF

1

1

1

1

1

1

15 s

74

rfGA

1

1

1

1

1

1

1 h 33 min

84

svmGA

1

1

1

1

1

1

13 h 2 min

23

LASSO

1

1

1

1

1

1

1 s

14

  1. ACC Accuracy, SEN Sensitivity, SPE Specificity, PPV Positive Predictive Value, NPV Negative Predictive Value, AUC Area Under ROC Curve, Time average learning time for each cross-validation fold, Nfeats n. of selected features
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BMC Bioinformatics

ISSN: 1471-2105

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