mlsanityData to 14 Oct 2026

FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification

arXiv 2311.14549 ↗First posted 24 Nov 2023stat.ML cs.LGcited by 1

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Abstract (arXiv)

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 urlhttps://github.com/irkri/fruits.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 28 of its 53 references that are in the map. First posted on arXiv 24 Nov 2023.

Builds on

28 of 53 references.

References · 28

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16 more
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  16. 2019Making the Dynamic Time Warping Distance Warping-Invariantcited by 2

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Citing papers per year: 2025: 1.

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  1. 2025Tensor-to-Tensor Models with Fast Iterated Sum Featurescited by 0