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Table 2 Average Kappa of different algorithms with different datasets

From: Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification

Kappa NN SMOTE-NN R-SMOTE-NN SRA-NN ASCB_DmSMOTE-NN
Thoraric Surgery 0.049 0.305 0.312 ± 0.48 0.670 ± 0.21 0.813 ± 0.11
Ecoli 0.502 0.807 0.723 ± 0.12 0.850 ± 0.05 0.848 ± 0.06
Sick Euthyroid 0.497 0.831 0.688 ± 0.13 0.824 ± 0.07 0.874 ± 0.05
Yeast_ML8 0.000 0.381 0.578 ± 0.23 0.968 ± 0.02 0.927 ± 0.04
Thyroid Sick 0.360 0.833 0.762 ± 0.12 0.906 ± 0.06 0.829 ± 0.11
Arrhythmia 0.068 0.761 0.826 ± 0.13 0.937 ± 0.04 0.966 ± 0.02
Mammography 0.436 0.794 0.729 ± 0.14 0.673 ± 0.16 0.932 ± 0.02
K_average 0.273 0.673 0.660 ± 0.22 0.833 ± 0.09 0.884 ± 0.06
  1. The italicized entries represent the best performance