FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification
Machine Learning
2023-11-27 v1 Machine Learning
Abstract
We introduce a pipeline for time series classification that extracts features based on the iterated-sums signature (ISS) and then applies a linear classifier. These features are intrinsically nonlinear, capture chronological information, and, under certain settings, are invariant to time-warping. We are competitive with state-of-the-art methods on the UCR archive, both in terms of accuracy and speed. We make our code available at \url{https://github.com/irkri/fruits}.
Cite
@article{arxiv.2311.14549,
title = {FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification},
author = {Joscha Diehl and Richard Krieg},
journal= {arXiv preprint arXiv:2311.14549},
year = {2023}
}