Table 8.
MAvA results.
| Patch Ensemble | A | B | C | D | E | F | G | H | I | G | K | L | M | N | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Times of the optimal MAvA | 7 | 1 | 3 | 8 | 1 | 1 | 3 | 2 | 4 | 3 | 7 | 8 | 8 | 7 | 5 |
| Times of the second MAvA | 7 | 3 | 8 | 3 | 8 | 1 | 4 | 3 | 6 | 2 | 5 | 4 | 3 | 5 | 1 |
| Times of the third MAvA | 7 | 1 | 12 | 1 | 4 | 4 | 7 | 4 | 6 | 4 | 2 | 2 | 3 | 2 | 1 |
| Total | 21 | 5 | 23 | 12 | 13 | 6 | 14 | 9 | 16 | 9 | 14 | 14 | 14 | 14 | 7 |
1. The 14 classical imbalanced classification algorithms are AdaBoostNC (A), AdaC2M1 (B), FuzzyImbECOC (C), MHDDTECOC (D), HDDTOVA (E), ImECOCdense (F), ImECOCOVA (G), ImECOCsparse (H), MCHDDT (I), MultiIMAO (J), MultiIMOAHO (K), MultiIMOVA (L), MultiIMOVO (M), and Piboost (N). 2. “Times of the optimal MAvA” in the table represents the times of best classification result of each algorithm in 56 datasets. “Times of the second MAvA” in the table represents the times of suboptimum classification result of each algorithm, and so on. 3. The bold number indicates that the classification result is equal to or better than that of the Patch Ensemble classifier.