Open Access
Table B.2.
Final set of hyper-parameters for each algorithm and each sample, selected by the best F1-Score from GridSearch.
| Hyper-parameters | ||||
|---|---|---|---|---|
| Algorithm | Sample | n_estimators | learning_rate | max_depth |
| LightGBM | Sample 1 | 750 | 0.075 | 5 |
| Sample 2 | 100 | 0.3 | 7 | |
| Sample 3 | 50 | 0.1 | 8 | |
| Sample 4 | 500 | 0.05 | 8 | |
| Sample 5 | 250 | 0.1 | 7 | |
| XGBoost | Sample 1 | 250 | 0.1 | 6 |
| Sample 2 | 250 | 0.3 | 8 | |
| Sample 3 | 100 | 0.5 | 6 | |
| Sample 4 | 1500 | 0.01 | 7 | |
| Sample 5 | 250 | 0.075 | 4 | |
| CatBoost | Sample 1 | 1500 | 0.05 | 4 |
| Sample 2 | 2000 | 0.1 | 5 | |
| Sample 3 | 1000 | 0.075 | 5 | |
| Sample 4 | 100 | 0.05 | 5 | |
| Sample 5 | 250 | 0.1 | 6 | |
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