CatBoost

class CatBoost(params=None)

Purpose

Training and applying models.

Parameters

Parameter Possible types Description Default value
params dict

The list of parameters to start training with.

If omitted, default values are used.

Note. Some parameters duplicate the ones specified for the fit method. In these cases the values specified for the fit method take precedence.
None
Parameter Possible types Description Default value
params dict

The list of parameters to start training with.

If omitted, default values are used.

Note. Some parameters duplicate the ones specified for the fit method. In these cases the values specified for the fit method take precedence.
None

Attributes

Attribute Description
tree_count_

Return the number of trees in the model.

feature_importances_
Return the calculated feature importances. The output data depends on the type of the model's loss function:
random_seed_

The random seed used for training.

learning_rate_

The learning rate used for training.

feature_names_

The names of features in the dataset.

evals_result_

Return the values of metrics calculated during the training.

best_score_

Return the best result for each metric calculated on each validation dataset.

best_iteration_

Return the identifier of the iteration with the best result of the evaluation metric or loss function on the last validation set.

classes_

Return the names of classes for classification models. An empty list is returned for all other models.

The order of classes in this list corresponds to the order of classes in resulting predictions.

Attribute Description
tree_count_

Return the number of trees in the model.

feature_importances_
Return the calculated feature importances. The output data depends on the type of the model's loss function:
random_seed_

The random seed used for training.

learning_rate_

The learning rate used for training.