Table 4.
Average classification accuracy (%) obtained by 30 runs for all compared classifiers.
| Dataset | Orig | RENN | FaLKNR | AdaBoost | MultiBoost | IEMLP | Mr2DNM | |
|---|---|---|---|---|---|---|---|---|
| WBCD | Accuracy (%) | 95.28 | 96.14 | 96.28 | 94.99 | 95.85 | 96.62 | 96.80 |
| Rank | 6 | 4 | 3 | 7 | 5 | 2 | 1 | |
| BUPA | Accuracy (%) | 71.59 | 71.88 | 71.01 | 71.88 | 71.59 | 71.59 | 72.66 |
| Rank | 5 | 2.5 | 7 | 2.5 | 5 | 5 | 1 | |
| IONO | Accuracy (%) | 91.17 | 86.61 | 86.61 | 91.17 | 91.74 | 89.23 | 90.73 |
| Rank | 2.5 | 6.5 | 6.5 | 2.5 | 1 | 5 | 4 | |
| PIMA | Accuracy (%) | 75.39 | 76.69 | 75.91 | 75.26 | 75.13 | 78.07 | 76.80 |
| Rank | 5 | 3 | 4 | 6 | 7 | 1 | 2 | |
| VOTE | Accuracy (%) | 94.71 | 94.71 | 96.55 | 94.48 | 94.48 | 95.95 | 96.57 |
| Rank | 4.5 | 4.5 | 2 | 6.5 | 6.5 | 3 | 1 | |
| A.Rank | 4.6 | 4.1 | 4.5 | 4.9 | 4.9 | 3.2 | 1.8 |