refit_trainval
refit_trainval: (false (default) | true) (Optional)
Description
Specifies whether to refit the best AutoML model (fitted on train+validation data) to new training values. After we complete all the requested experiments by training on the train split and using the validation split for early stopping, Kumo will take the best-performing model and retrain it using both the training and validation data splits. This allows us the final model used to generate predictions to use as much and as recent data as possible while avoiding leakage in AutoML.
Supported Task Types
- All
Default Values
| run_mode | Default Value |
|---|---|
| FAST | false |
| NORMAL | false |
| BEST | false |
refit_trainval
refit_trainval: (false (default) | true) (Optional)
Description
Specifies whether to refit the best AutoML model (fitted on train+validation data) to new training values. After we complete all the requested experiments by training on the train split and using the validation split for early stopping, Kumo will take the best-performing model and retrain it using both the training and validation data splits. This allows us the final model used to generate predictions to use as much and as recent data as possible while avoiding leakage in AutoML.
Supported Task Types
- All
Default Values
| run_mode | Default Value |
|---|---|
| FAST | false |
| NORMAL | false |
| BEST | false |