Table 9.
Comparison of our ensemble models with other state-of-the-art ensembles.
| Model Metrics | Accuracy | Precision | Recall | F-score | AUC |
|---|---|---|---|---|---|
| Ens_DT [11] | 92 | 92 | 94.4 | 89.8 | 96.9 |
| Ens_SVM [11] | 94 | 93.5 | 90.4 | 97.8 | 95.3 |
| Ens_NN [11] | 99.5 | 99.5 | 99.6 | 99.6 | 99.8 |
| Ensemble Bagging [75] | 99.7 | 99.7 | 99.8 | 99.8 | - |
| Ensemble Boosting [75] | 99.8 | 99.8 | 99.9 | 99.9 | - |
| Ensemble Stacking [75] | 99.9 | 99.9 | 99.9 | 99.9 | - |
| DNN [74] | 98.4 | 92 | 89 | 87.6 | - |
| LSTM [74] | 99.1 | 100 | 92 | 95 | - |
| Ensemble DL Stacking [74] | 99.7 | 100 | 95 | 98 | - |
| En_DT | 97.8 | 97.8 | 97.5 | 98.0 | 98.6 |
| Ens_LGBM | 99.7 | 99.6 | 99.8 | 99.9 | 99.5 |
| Ens_XGB | 99.0 | 99.1 | 98.9 | 99.0 | 99.6 |
| Ens_HMV | 99.99 | 100 | 100 | 100 | 99.99 |
| BoostedEnsML Proposed | 100 | 100 | 100 | 100 | 100 |