Table 10 Performance evaluation results of the models utilized in the study.
From: Evaluating machine learning efficiency and accuracy for real time flash flood mapping
Model | RMSE | R² | MAE | Accuracy | AUC |
|---|---|---|---|---|---|
Random forest (RF) | 0.12 | 0.94 | 0.11 | 0.95 | 0.89 |
CatBoost | 0.41 | 0.6 | 0.36 | 0.8 | 0.67 |
AdaBoost | 0.43 | 0.58 | 0.38 | 0.76 | 0.6 |
XGBoost | 0.39 | 0.65 | 0.34 | 0.82 | 0.67 |
H2O | 0.25 | 0.77 | 0.2 | 0.85 | 0.74 |
LightGBM | 0.4 | 0.53 | 0.35 | 0.78 | 0.6 |
