ProximityStump

Schnellstart

from sktime.classification.distance_based import ProximityStump

estimator = ProximityStump(random_state=None, distance_measure=None, verbosity=0, n_jobs=1)

Parameter(4)

random_state: integer, the random state

distance_measure: ``None`` (default) or str; if str, one of

“euclidean”, “dtw”, “ddtw”, “wdtw”, “wddtw”, “msm”, “lcss”, “erp” distance measure to use if None, selects distances randomly from the list of available distances

verbosity: logging verbosity

n_jobs: number of jobs to run in parallel *across threads”

Beispiele

>>> from sktime.classification.distance_based import ProximityStump
>>> from sktime.datasets import load_unit_test
>>> X_train, y_train = load_unit_test (split = "train")
>>> X_test, y_test = load_unit_test (split = "test")
>>> clf = ProximityStump ()
>>> clf. fit (X_train, y_train) ProximityStump(
... )
>>> y_pred = clf. predict (X_test)