_TrendTransform

class _TrendTransform(in_column: str, out_column: str, change_point_model: ruptures.base.BaseEstimator, detrend_model: Type[sklearn.base.RegressorMixin], **change_point_model_predict_params)

Bases: etna.transforms.base.PerSegmentWrapper

_TrendTransform adds trend as a feature. Creates column ‘<in_column>_trend’.

Init _TrendTransform.

Parameters

• in_column (str) – name of column to apply transform to

• out_column (str) – name of added column

• change_point_model (ruptures.base.BaseEstimator) – model to get trend change points

• detrend_model (Type[sklearn.base.RegressorMixin]) – model to get trend in data

• change_point_model_predict_params – params for change_point_model.predict method

Inherited-members

Methods

fit(df)	Fit transform on each segment.
fit_transform(df)	May be reimplemented.
inverse_transform(df)	Apply inverse_transform to each segment.
load(path)	Load an object.
save(path)	Save the object.
to_dict()	Collect all information about etna object in dict.
transform(df)	Apply transform to each segment separately.