Transformer

ClaSPTransformer

ClaSP (Classification Score Profile) Transformer.

Implementation of the Classification Score Profile of a time series. ClaSP hierarchically splits a TS into two parts, where each split point is determined by training a binary TS classifier for each possible split point and selecting the one with highest accuracy, i.e., the one that is best at identifying subsequences to be from either of the partitions.

Schnellstart

python

from sktime.transformations.clasp import ClaSPTransformer

estimator = ClaSPTransformer(window_length=10, scoring_metric='ROC_AUC', exclusion_radius=0.05)

Parameter(3)

window_lengthint, default = 10: size of window for sliding.
scoring_metricstring, default = ROC_AUC: the scoring metric to use in ClaSP - choose from ROC_AUC or F1
exclusion_radiusint: Exclusion Radius for change points to be non-trivial matches

Beispiele

>>> from sktime.transformations.clasp import ClaSPTransformer
>>> from sktime.detection.clasp import find_dominant_window_sizes
>>> from sktime.datasets import load_electric_devices_segmentation
>>> X, true_period_size, true_cps = load_electric_devices_segmentation ()
>>> dominant_period_size = find_dominant_window_sizes (X)
>>> clasp = ClaSPTransformer (window_length = dominant_period_size)
>>> clasp. fit (X)
>>> profile = clasp. transform (X)