BMC Bioinformatics

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

	ACC	SEN	SPE	PPV	NPV	Time	Nfeats
3 classes	0.92	0.89	0.95	0.87	0.94	59 min	15
5 classes	0.91	0.85	0.96	0.84	0.96	1 h 48 min	18
7 classes	0.89	0.82	0.97	0.78	0.97	3 h 43 min	18
9 classes	0.89	0.82	0.97	0.79	0.97	6 h 49 min	24
11 classes	0.86	0.75	0.97	0.72	0.97	11 h 55 min	22

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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