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Table 18:
Comparison of the performance of instance and feature selection methods in terms of G-mean and storage requirements for class-imbalanced datasets. The table shows the win/loss record of each algorithm in the column against the algorithm in the row, the p-value of a two-tailed sign test on the win/loss record, ps, and the p-value of the Wilcoxon test, pw. Significant differences at a confidence level of 95% are marked with a tick (✓).
Compared MethodMemetic IS+FS
G-mean   
 CHC IS+FS win/loss 32/8 
 ps 0.0002 ✓ 
 R+/R 154.0/666.0 
 pw 0.0005 ✓ 
Storage requirements   
 CHC IS+FS win/loss 37/3 
 ps 0.0000 ✓ 
 R+/R 18.0/802.0 
 pw 0.0000 ✓ 
Compared MethodMemetic IS+FS
G-mean   
 CHC IS+FS win/loss 32/8 
 ps 0.0002 ✓ 
 R+/R 154.0/666.0 
 pw 0.0005 ✓ 
Storage requirements   
 CHC IS+FS win/loss 37/3 
 ps 0.0000 ✓ 
 R+/R 18.0/802.0 
 pw 0.0000 ✓ 
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