TransformByLevel

Transform by instance or panel.

Quickstart

from sktime.transformations.compose import TransformByLevel

estimator = TransformByLevel(transformer, groupby='local', raise_warnings=True)

Parameters(3)

transformersktime transformer used in TransformByLevel

A “blueprint” transformer, state does not change when fit is called.

groupbystr, one of [“local”, “global”, “panel”], optional, default=”local”

level on which data are grouped to fit clones of transformer “local” = unit/instance level, one reduced model per lowest hierarchy level “global” = top level, one reduced model overall, on pooled data ignoring levels “panel” = second lowest level, one reduced model per panel level (-2) if there are 2 or less levels, “global” and “panel” result in the same if there is only 1 level (single time series), all three settings agree

raise_warningsbool, optional, default=True

whether to warn the user if transformer is instance-wise in this case wrapping the transformer om TransformByLevel does not change the estimator logic, compared to not wrapping it. Wrapping this way can make sense in some cases of tuning, in which case warn=False can be set to suppress the warning raised.

Examples

>>> from sktime.transformations.compose import TransformByLevel
>>> from sktime.transformations.hierarchical.reconcile import Reconciler
>>> from sktime.utils._testing.hierarchical import _make_hierarchical
>>> X = _make_hierarchical ()
>>> f = TransformByLevel (Reconciler (), groupby = "panel")
>>> f. fit (X) TransformByLevel(
... )