- Optimize
This checkbox enables the Bayesian hyperparameter optimization, which tweaks the learning rate, as well as the number of iterations and leaves, to find the best model's configuration in terms of metrics.
Be aware that this process is time-consuming.
- Disallow negative predictions
This checkbox forces the model to round up negative values to be equal to 0.
- Brick frozen
This parameter enables the frozen run for this brick. It means that the trained model will be saved and will skip the training process during future runs, which may be useful after pipeline deployment.
This option appears only after successful regular run.
Note that frozen run will not be executed if the data structure is changed.