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Table 5 Ranks computed by the Wilcoxon test based on the MAUCs

From: Boosting methods for multi-class imbalanced data classification: an experimental review

Algorithms AdaBoost.MH SAMME CatBoost LogitBoost GradientBoost XGBoost MEBoost SMOTEBoost RUSBoost LightGBM AdaC1 AdaC2 AdaC3 AdaCost
AdaBoost.MH −  61 20.5 39.5 64 26 85 36 73 85 74 75 64 55
SAMME 44 −  14 31 57 35 65 23 76 75 86 83 62 57
CatBoost 99.5 106 −  76 95 79 106 79 109 101 107.5 107 95 90
LogitBoost 80.5 89 44 −  81 46 73 64 83 89 102 98 88 83
GradientBoost 56 63 25 39 −  45 64 43 75 62 76 64 73 53
XGBoost 94 85 41 74 75 −  87 58 81 85 105 96 80.05 80
MEBoost 35 55 14 32 56 33 −  32 62 85 72 60 52 51
SMOTEBoost 84 97 41 56 77 62 88 −  102 88 109 111 94 88
RUSBoost 47 44 11 37 45 39 58 18 −  68 70 64 43 47
LightGBM 35 45 19 31 58 35 35 32 52 −  58 43 42 41
AdaC1 46 34 12.5 18 44 15 48 11 50 62 −  43.5 41 25
AdaC2 45 37 13 22 65 24 60 9 56 77 76.5 −  43 40
AdaC3 56 58 25 32 47 39 68 26 77 78 79 77 −  52
AdaCost 65 63 30 37 67 40 69 32 73 79 80 80 68 −