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 |