evalml.pipelines.components.CatBoostRegressor

class evalml.pipelines.components.CatBoostRegressor(n_estimators=10, eta=0.03, max_depth=6, bootstrap_type=None, silent=False, allow_writing_files=False, random_state=None, random_seed=0, **kwargs)[source]

CatBoost Regressor, a regressor that uses gradient-boosting on decision trees. CatBoost is an open-source library and natively supports categorical features.

For more information, check out https://catboost.ai/

name = 'CatBoost Regressor'
model_family = 'catboost'
supported_problem_types = [<ProblemTypes.REGRESSION: 'regression'>, <ProblemTypes.TIME_SERIES_REGRESSION: 'time series regression'>]
hyperparameter_ranges = {'eta': Real(low=1e-06, high=1, prior='uniform', transform='identity'), 'max_depth': Integer(low=4, high=10, prior='uniform', transform='identity'), 'n_estimators': Integer(low=4, high=100, prior='uniform', transform='identity')}
default_parameters = {'allow_writing_files': False, 'bootstrap_type': None, 'eta': 0.03, 'max_depth': 6, 'n_estimators': 10, 'silent': False}
predict_uses_y = False

Instance attributes

feature_importance

Return an attribute of instance, which is of type owner.

needs_fitting

parameters

Returns the parameters which were used to initialize the component

Methods:

__init__

Initialize self.

clone

Constructs a new component with the same parameters and random state.

describe

Describe a component and its parameters

fit

Fits component to data

load

Loads component at file path

predict

Make predictions using selected features.

predict_proba

Make probability estimates for labels.

save

Saves component at file path

Class Inheritance

Inheritance diagram of CatBoostRegressor