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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

 ACCSENSPEPPVNPVAUCTimeNfeats
GARS1111114 min14
RFE0.750.750.750.750.750.941 s5
SBF11111115 s74
rfGA1111111 h 33 min84
svmGA11111113 h 2 min23
LASSO1111111 s14
  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