Research Article
Feature Selection and Classification of Clinical Datasets Using Bioinspired Algorithms and Super Learner
Table 9
Performance of FCSO, FKH, and FBFO classifiers and super learner on WDBC dataset.
| Feature selection algorithm | Size of feature subset | TN | FP | FN | TP | Accuracy | Sensitivity | Specificity | Precision | -score |
| CSO | 15 | 137 | 4 | 6 | 165 | 96.79 | 96.49 | 97.16 | 97.63 | 0.97 | KH | 17 | 139 | 2 | 5 | 166 | 97.76 | 97.08 | 98.58 | 98.81 | 0.98 | BFO | 18 | 139 | 2 | 8 | 163 | 96.79 | 95.32 | 98.58 | 98.79 | 0.97 | Super learner | ā | 22 | 0 | 2 | 39 | 96.83 | 95.12 | 100.00 | 100.00 | 0.98 |
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