Table 3.
Accuracy, precision, recall, and F1 score of tested models for survival prediction.
| Survival prediction | ||||
|---|---|---|---|---|
| Model | Accuracy (%) | Precision (%) | Recall (%) | F1 score |
| FTTransformer31 | 87.17 | 88.28 | 98.39 | 0.9302 |
| TabTransformer30 | 87.91 | 92.66 | 93.50 | 0.9307 |
| TabNet40 | 86.66 | 88.91 | 96.70 | 0.9263 |
| XGBoost32 | 92.30 | 94.92 | 96.28 | 0.9560 |
| LightGBM33 | 93.55 | 95.52 | 97.13 | 0.9631 |
| CatBoost34 | 93.55 | 94.20 | 98.64 | 0.9637 |
| Random forest39 | 87.03 | 87.00 | 100.0 | 0.9305 |
| Logistic regression37 | 87.32 | 88.86 | 97.63 | 0.9304 |
| XGBoost with22 tunning | 90.69 | 93.22 | 96.28 | 0.9472 |
| Random forest with22 tunning | 88.20 | 88.04 | 100.00 | 0.9363 |
Significant values are in bold.