_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)

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.
load(path)	Load an object.
save(path)	Save the object.
to_dict()	Collect all information about etna object in dict.
transform(df)	Add column with trend, got from the detrend_model.

inverse_transform(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame

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

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