_OneSegmentTrendTransform¶

class _OneSegmentTrendTransform(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.decomposition.change_points_trend._OneSegmentChangePointsTrendTransform

_OneSegmentTrendTransform adds trend as a feature.

Init _OneSegmentTrendTransform.

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 from data
change_point_model_predict_params – params for change_point_model.predict method

Inherited-members

Methods

`fit`(df)	Fit OneSegmentChangePointsTransform: find trend change points in `df`, fit detrend models with data from intervals of stable trend.
`fit_transform`(df)	May be reimplemented.
`inverse_transform`(df)	Inverse transform dataframe.
`transform`(df)	Add column with trend, got from the detrend_model.

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

Inverse transform dataframe.

Parameters: df (pandas.core.frame.DataFrame) – one segment dataframe
Returns: given dataframe
Return type: pd.DataFrame

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

Add column with trend, got from the detrend_model.

Parameters: df (pandas.core.frame.DataFrame) – data to get trend from
Returns: df with trend column
Return type: pd.DataFrame