make_pipeline

make_pipeline(*steps)

Create a pipeline from estimators of any type.

Parameters:

stepstuple of sktime estimators

in same order as used for pipeline construction

Returns:

pipesktime pipeline containing steps, in order

always a descendant of BaseObject, precise object determined by scitype equivalent to result of step[0] * step[1] * … * step[-1]

Examples

Example 1: forecaster pipeline

>>> from sktime.pipeline import make_pipeline
>>> from sktime.transformations.series.exponent import ExponentTransformer
>>> from sktime.forecasting.trend import PolynomialTrendForecaster
>>> pipe = make_pipeline(ExponentTransformer(), PolynomialTrendForecaster())
>>> type(pipe).__name__
'TransformedTargetForecaster'

Example 2: classifier pipeline

>>> from sktime.pipeline import make_pipeline
>>> from sktime.transformations.series.exponent import ExponentTransformer
>>> from sktime.classification.distance_based import KNeighborsTimeSeriesClassifier
>>> pipe = make_pipeline(ExponentTransformer(), KNeighborsTimeSeriesClassifier())
>>> type(pipe).__name__
'ClassifierPipeline'

Example 3: transformer pipeline

>>> from sktime.pipeline import make_pipeline
>>> from sktime.transformations.series.exponent import ExponentTransformer
>>> pipe = make_pipeline(ExponentTransformer(), ExponentTransformer())
>>> type(pipe).__name__
'TransformerPipeline'