SklearnClustererPipeline

Pipeline of transformers and a clusterer.

Quickstart

from sktime.clustering.compose import SklearnClustererPipeline

estimator = SklearnClustererPipeline(clusterer, transformers)

Parameters(2)

clusterersklearn clusterer, i.e., inheriting from sklearn ClustererMixin

this is a “blueprint” clusterer, state does not change when fit is called

transformerslist of sktime transformers, or

list of tuples (str, transformer) of sktime transformers these are “blueprint” transformers, states do not change when fit is called

Examples

>>> from sklearn.cluster import KMeans
>>> from sktime.transformations.exponent import ExponentTransformer
>>> from sktime.transformations.summarize import SummaryTransformer
>>> from sktime.datasets import load_unit_test
>>> from sktime.clustering.compose import SklearnClustererPipeline
>>> X_train, y_train = load_unit_test (split = "train")
>>> X_test, y_test = load_unit_test (split = "test")
>>> t1 = ExponentTransformer ()
>>> t2 = SummaryTransformer ()
>>> pipeline = SklearnClustererPipeline (KMeans (), [t1, t2 ])
>>> pipeline = pipeline. fit (X_train, y_train)
>>> y_pred = pipeline. predict (X_test) Alternative construction via dunder method:
>>> pipeline = t1 * t2 * KMeans ()