Table 4 Optimized parameters of RF, GBR, and SVR
| Methods | Parameters | Parameter description | Terminal values |
|---|---|---|---|
| RF | n_estimators | The number of trees in the forest | 10 |
| max_depth | The depth of a tree | 7 | |
| GBR | max_depth | The depth of a tree | 7 |
| learning_rate | The learning rate | 0.19 | |
| n_estimators | The number of trees | 40 | |
| SV | C | The penalty parameter | 150 |
| ε | Insensitive loss coefficient | 0.08 | |
| γ | γ defines how much influence a single training example has. The larger the γ is, the closer other example must be to be affected. | 0.1 |