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Performance comparison of different ML models when applying feature selection with the Jellyfish algorithm.
| Model with JF | Sensitivity (%) | Specificity (%) | Accuracy (%) | AUC (%) |
|---|---|---|---|---|
| ANN with JF | 98.22 | 98.89 | 97.99 | 79.33 |
| DT with JF | 98.07 | 98.34 | 97.55 | 81.98 |
| AdaBoost with JF | 98.12 | 98.07 | 98.24 | 84.92 |
| SVM with JF | 98.56 | 98.37 | 98.47 | 94.48 |
