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Table 3 Performance evaluation, testing GARS on ‘multi-class high-dimension’ datasets

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

 ACCSENSPEPPVNPVTimeNfeats
3 classes0.920.890.950.870.9459 min15
5 classes0.910.850.960.840.961 h 48 min18
7 classes0.890.820.970.780.973 h 43 min18
9 classes0.890.820.970.790.976 h 49 min24
11 classes0.860.750.970.720.9711 h 55 min22
  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