_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)[source]

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.

transform(df)

Apply transform to each segment separately.