LinearTrendTransform

class LinearTrendTransform(in_column: str, poly_degree: int = 1, **regression_params)

Bases: etna.transforms.base.PerSegmentWrapper

Transform that uses sklearn.linear_model.LinearRegression to find linear or polynomial trend in data.

Warning

This transform can suffer from look-ahead bias. For transforming data at some timestamp it uses information from the whole train part.

Create instance of LinearTrendTransform.

Parameters

• in_column (str) – name of processed column

• poly_degree (int) – degree of polynomial to fit trend on

• regression_params – params that should be used to init sklearn.linear_model.LinearRegression

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.