Research Article
Angle Modulated Artificial Bee Colony Algorithms for Feature Selection
Table 3
Classification accuracy of each ABC algorithm on the tested datasets by using SVM as an induction algorithm.
| | | SN | SR | IS | DE | HC | AN |
| Without feature selection | Accuracy (%) | 91.20 ± 0.24 | 86.15 ± 0.87 | 87.09 ± 0.48 | 94.64 ± 0.39 | 79.10 ± 1.21 | 99.13 ± 0.11 | Average number of features | 35 | 60 | 34 | 34 | 22 | 38 |
| CABC | Accuracy (%) | 85.35 ± 0.720 | 70.67 ± 0.93 | 94.30 ± 1.45 | 97.26 ± 5.22 | 85.86 ± 1.37 | 97.77 ± 0.15 | Average number of features | 12.3 | 17.6 | 9.2 | 13.6 | 4.5 | 8.4 |
| EABC | Accuracy (%) | 85.94 ± 0.52 | 73.07 ± 0.01 | 94.01 ± 0.36 | 97.26 ± 0.08 | 85.86 ± 0.5 | 97.77 ± 0.21 | Average number of features | 7.8 | 10.2 | 8.9 | 13.4 | 4.1 | 7.9 |
| GABC | Accuracy (%) | 85.51 ± 0.31 | 72.11 ± 1.23 | 94.30 ± 0.55 | 96.45 ± 0.88 | 86.14 ± 0.1 | 97.77 ± 0.23 | Average number of features | 9.1 | 18.0 | 6.7 | 8.3 | 5.6 | 13.7 |
| GDABC | Accuracy (%) | 85.36 ± 0.59 | 73.55 ± 1.03 | 94.30 ± 0.18 | 96.72 ± 0.17 | 85.86 ± 0.93 | 97.77 ± 0.08 | Average number of features | 9.4 | 22.2 | 11.8 | 8.9 | 4.2 | 15.8 |
| MABC | Accuracy (%) | 86.67 ± 0.62 | 75.96 ± 1.22 | 95.16 ± 0.46 | 98.63 ± 0.68 | 86.41 ± 0.27 | 97.77 ± 0.01 | Average number of features | 12.3 | 8.5 | 7.4 | 8.5 | 3.9 | 10.0 |
| OABC | Accuracy (%) | 84.77 ± 0.65 | 73.08 ± 0.61 | 94.30 ± 0.47 | 96.99 ± 0.30 | 85.87 ± 1.35 | 97.77 ± 0.35 | Average number of features | 5.8 | 10.3 | 5.7 | 4.9 | 5.9 | 15.7 |
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