Table 4 Summary of 10-fold cross-validation using a random forest (RF) model for rigid and flexible vegetation.
From: Artificial intelligence evaluation of nature based flood resilience in hilly terrain
Fold | RF (RV) | RF (FV) | ||||||
|---|---|---|---|---|---|---|---|---|
RMSE | MAE | NSE | KGE | RMSE | MAE | NSE | KGE | |
1 | 6.268 | 4.551 | 0.933 | 0.880 | 4.977 | 3.455 | 0.930 | 0.893 |
2 | 3.261 | 2.789 | 0.967 | 0.947 | 2.962 | 2.418 | 0.953 | 0.973 |
3 | 5.143 | 4.124 | 0.943 | 0.920 | 8.951 | 6.208 | 0.828 | 0.709 |
4 | 5.585 | 4.053 | 0.911 | 0.913 | 6.110 | 4.911 | 0.808 | 0.870 |
5 | 5.497 | 4.413 | 0.924 | 0.962 | 6.930 | 5.070 | 0.803 | 0.898 |
6 | 4.475 | 3.520 | 0.935 | 0.869 | 7.743 | 5.277 | 0.851 | 0.870 |
7 | 7.380 | 5.210 | 0.898 | 0.904 | 6.606 | 3.613 | 0.872 | 0.929 |
8 | 6.408 | 4.637 | 0.918 | 0.846 | 9.481 | 4.316 | 0.650 | 0.624 |
9 | 5.713 | 3.859 | 0.912 | 0.929 | 4.418 | 2.865 | 0.915 | 0.928 |
10 | 3.669 | 2.291 | 0.968 | 0.954 | 4.093 | 2.548 | 0.962 | 0.915 |
