(preprocessedTrainPool, preprocessedEvalPools, ctrsContext)
Additional variant of fit
method that accepts CatBoost's Pool s and allows to specify additional
datasets for computing evaluation metrics and overfitting detection similarily to CatBoost's other APIs.
Additional variant of fit
method that accepts CatBoost's Pool s and allows to specify additional
datasets for computing evaluation metrics and overfitting detection similarily to CatBoost's other APIs.
The input training dataset.
The validation datasets used for the following processes:
trained model
override in descendants if necessary
override in descendants if necessary
(preprocessedTrainPool, preprocessedEvalPools, catBoostTrainingContext)
Class to train CatBoostRegressionModel The default optimized loss function is
RMSE
Examples
Basic example.
Example with alternative loss function.
Serialization
Supports standard Spark MLLib serialization. Data can be saved to distributed filesystem like HDFS or local files.
Examples:
Save:
Load: