Transformer (Pairwise Panel)

LuckyDtwDist

Lucky dynamic time warping distance.

Implements lucky dynamic time warping distance [1]_. Uses Euclidean distance for multivariate data.

Based on code by Krisztian A Buza’s research group.

Schnellstart

python

from sktime.dists_kernels.lucky import LuckyDtwDist

estimator = LuckyDtwDist(window=None)

Parameter(1)

window: int, optional (default=None): Maximum distance between indices of aligned series, aka warping window. If None, defaults to max(len(ts1), len(ts2)), i.e., no warping window.

Beispiele

>>> from sktime.dists_kernels.lucky import LuckyDtwDist
>>> from sktime.datasets import load_unit_test
>>> 
>>> dist = LuckyDtwDist (window = 2)
>>> X, _ = load_unit_test (return_type = "pd-multiindex")
>>> dist_mat = dist. transform (X)

Referenzen

..[1] Stephan Spiegel, Brijnesh-Johannes Jain, and Sahin Albayrak.: Fast time series classification under lucky time warping distance. Proceedings of the 29th Annual ACM Symposium on Applied Computing. 2014.