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 |