ClassifierPipeline

Pipeline of transformers and a classifier.

Quickstart

from sktime.classification.compose import ClassifierPipeline

estimator = ClassifierPipeline(classifier, transformers)

Parameters(2)

classifiersktime classifier, i.e., estimator inheriting from BaseClassifier

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 sktime.transformations.pca import PCATransformer
>>> from sktime.classification.interval_based import TimeSeriesForestClassifier
>>> from sktime.datasets import load_unit_test
>>> from sktime.classification.compose import ClassifierPipeline
>>> X_train, y_train = load_unit_test (split = "train")
>>> X_test, y_test = load_unit_test (split = "test")
>>> pipeline = ClassifierPipeline (
... TimeSeriesForestClassifier (n_estimators = 5), [PCATransformer ()]
... )
>>> pipeline. fit (X_train, y_train) ClassifierPipeline(
... )
>>> y_pred = pipeline. predict (X_test) Alternative construction via dunder method:
>>> pipeline = PCATransformer () * TimeSeriesForestClassifier (n_estimators = 5)