TransformedTargetForecaster

Meta-estimator for forecasting transformed time series.

Quickstart

from sktime.forecasting.compose import TransformedTargetForecaster

estimator = TransformedTargetForecaster(steps)

Parameters(1)

stepslist of sktime transformers and forecasters, or

list of tuples (str, estimator) of sktime transformers or forecasters. The list must contain exactly one forecaster. These are “blueprint” transformers resp forecasters, forecaster/transformer states do not change when fit is called.

Examples

>>> from sktime.datasets import load_airline
>>> from sktime.forecasting.naive import NaiveForecaster
>>> from sktime.forecasting.compose import TransformedTargetForecaster
>>> from sktime.transformations.impute import Imputer
>>> from sktime.transformations.detrend import Detrender
>>> from sktime.transformations.exponent import ExponentTransformer
>>> y = load_airline () Example 1: string/estimator pairs
>>> pipe = TransformedTargetForecaster (steps = [
... ("imputer", Imputer (method = "mean")),
... ("detrender", Detrender ()),
... ("forecaster", NaiveForecaster (strategy = "drift")),
... ])
>>> pipe. fit (y) TransformedTargetForecaster(
... )
>>> y_pred = pipe. predict (fh = [1, 2, 3 ]) Example 2: without strings
>>> pipe = TransformedTargetForecaster ([
... Imputer (method = "mean"),
... Detrender (),
... NaiveForecaster (strategy = "drift"),
... ExponentTransformer (),
... ]) Example 3: using the dunder method
>>> forecaster = NaiveForecaster (strategy = "drift")
>>> imputer = Imputer (method = "mean")
>>> pipe = imputer * Detrender () * forecaster * ExponentTransformer ()