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Authors: Patrick Petersen ; Hanno Stage ; Philipp Reis ; Jonas Rauch and Eric Sax

Affiliation: FZI Research Center for Information Technology, 76131 Karlsruhe, Germany

Keyword(s): Pattern Recognition, Dimension Reduction, Motif Discovery, Time Series Data Mining.

Abstract: Large volumes of time series data are frequently analyzed using unsupervised algorithms to identify patterns. Multivariate time series’s time and space complexity poses challenges in this context. Dimensionality reduction, a common technique in data science, provides a viable solution to improve time and space complexity. Nevertheless, a crucial question arises concerning how the time advantage compares to the information loss. This paper compares dimension reduction methods within unsupervised time series pattern recognition, including rule-based, spectral, probabilistic, and unsupervised learning-based approaches. The comparison involves both synthetic and real-world datasets for a comprehensive evaluation. The findings reveal the potential to accelerate pattern recognition algorithms by 90 %, with only 18 % information loss in the sense of the F1 score.

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Paper citation in several formats:
Petersen, P., Stage, H., Reis, P., Rauch, J. and Sax, E. (2024). Comparison of Dimension Reduction Methods for Multivariate Time Series Pattern Recognition. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-684-2; ISSN 2184-4313, SciTePress, pages 809-816. DOI: 10.5220/0012428900003654

@conference{icpram24,
author={Patrick Petersen and Hanno Stage and Philipp Reis and Jonas Rauch and Eric Sax},
title={Comparison of Dimension Reduction Methods for Multivariate Time Series Pattern Recognition},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2024},
pages={809-816},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012428900003654},
isbn={978-989-758-684-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Comparison of Dimension Reduction Methods for Multivariate Time Series Pattern Recognition
SN - 978-989-758-684-2
IS - 2184-4313
AU - Petersen, P.
AU - Stage, H.
AU - Reis, P.
AU - Rauch, J.
AU - Sax, E.
PY - 2024
SP - 809
EP - 816
DO - 10.5220/0012428900003654
PB - SciTePress

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