_CatBoostAdapter¶

class _CatBoostAdapter(iterations: Optional[int] = None, depth: Optional[int] = None, learning_rate: Optional[float] = None, logging_level: Optional[str] = 'Silent', l2_leaf_reg: Optional[float] = None, thread_count: Optional[int] = None, **kwargs)[source]¶

Bases: etna.models.base.BaseAdapter

Inherited-members

Parameters

iterations (Optional[int]) –
depth (Optional[int]) –
learning_rate (Optional[float]) –
logging_level (Optional[str]) –
l2_leaf_reg (Optional[float]) –
thread_count (Optional[int]) –

Methods

`fit`(df, regressors)	Fit Catboost model.
`forecast_components`(df)	Estimate forecast components.
`get_model`()	Get internal catboost.CatBoostRegressor model that is used inside etna class.
`predict`(df)	Compute predictions from a Catboost model.
`predict_components`(df)	Estimate prediction components.

fit(df: pandas.core.frame.DataFrame, regressors: List[str]) → etna.models.catboost._CatBoostAdapter[source]¶

Fit Catboost model.

Parameters

df (pandas.core.frame.DataFrame) – Features dataframe
regressors (List[str]) – List of the columns with regressors(ignored in this model)

Returns

Fitted model

Return type

etna.models.catboost._CatBoostAdapter

forecast_components(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]¶

Estimate forecast components.

Parameters: df (pandas.core.frame.DataFrame) – features dataframe
Returns: dataframe with forecast components
Return type: pandas.core.frame.DataFrame

get_model() → catboost.core.CatBoostRegressor[source]¶

Get internal catboost.CatBoostRegressor model that is used inside etna class.

Returns: Internal model
Return type: result

predict(df: pandas.core.frame.DataFrame) → numpy.ndarray[source]¶

Compute predictions from a Catboost model.

Parameters: df (pandas.core.frame.DataFrame) – Features dataframe
Returns: Array with predictions
Return type: numpy.ndarray

predict_components(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]¶

Estimate prediction components.

Parameters: df (pandas.core.frame.DataFrame) – features dataframe
Returns: dataframe with prediction components
Return type: pandas.core.frame.DataFrame