Fig. 5:

Balanced accuracy on the synthetic datasets corrupted by different ratios of noise. With the gradual increase in noise (in both samples and features), the proposed techniques more robustly classify the data, compared to ${\text{JFSS}}_{{\ell }_1}$ [53], ${\text{LR}}_{{\ell }_0}$[62], and FSSVM.