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arXiv · 2504.12841

ALT: A Python Package for Lightweight Feature Representation in Time Series Classification

Balázs P. Halmos·Balázs Hajós·Vince Á. Molnár·Marcell T. Kurbucz·Antal Jakovác
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Abstract

We introduce ALT, an open-source Python package created for efficient and accurate time series classification (TSC). The package implements the adaptive law-based transformation (ALT) algorithm, which transforms raw time series data into a linearly separable feature space using variable-length shifted time windows. This adaptive approach enhances its predecessor, the linear law-based transformation (LLT), by effectively capturing patterns of varying temporal scales. The software is implemented for scalability, interpretability, and ease of use, achieving state-of-the-art performance with minimal computational overhead. Extensive benchmarking on real-world datasets demonstrates the utility of ALT for diverse TSC tasks in physics and related domains.

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BibTeXRIS

Balázs P. Halmos, Balázs Hajós, Vince Á. Molnár, Marcell T. Kurbucz, Antal Jakovác. 2025-04-17. ALT: A Python Package for Lightweight Feature Representation in Time Series Classification. https://doi.org/10.1088/2632-2153%2Fae3e4f

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