SklearnClassifierPipeline

Pipeline of transformers and a classifier.

Quickstart

from sktime.classification.compose import SklearnClassifierPipeline

estimator = SklearnClassifierPipeline(classifier, transformers)

Parameters(2)

classifiersklearn classifier, i.e., inheriting from sklearn ClassifierMixin

this is a “blueprint” classifier, 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.neighbors import KNeighborsClassifier
>>> from sktime.transformations.exponent import ExponentTransformer
>>> from sktime.transformations.summarize import SummaryTransformer
>>> from sktime.datasets import load_unit_test
>>> from sktime.classification.compose import SklearnClassifierPipeline
>>> X_train, y_train = load_unit_test (split = "train")
>>> X_test, y_test = load_unit_test (split = "test")
>>> t1 = ExponentTransformer ()
>>> t2 = SummaryTransformer ()
>>> pipeline = SklearnClassifierPipeline (KNeighborsClassifier (), [t1, t2 ])
>>> pipeline = pipeline. fit (X_train, y_train)
>>> y_pred = pipeline. predict (X_test) Alternative construction via dunder method:
>>> pipeline = t1 * t2 * KNeighborsClassifier ()