Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free

Ming-Chang Lee, Jia-Chun Lin, Volker Stolz

2024

Abstract

Despite the widespread use of k-means time series clustering in various domains, there exists a gap in the literature regarding its comprehensive evaluation with different time series preprocessing approaches. This paper seeks to fill this gap by conducting a thorough performance evaluation of k-means time series clustering on real-world open-source time series datasets. The evaluation focuses on two distinct techniques: z-normalization and NP-Free. The former is one of the most commonly used approaches for normalizing time series, and the latter is a real-time time series representation approach. The primary objective of this paper is to assess the impact of these two techniques on k-means time series clustering in terms of its clustering quality. The experiments employ the silhouette score, a well-established metric for evaluating the quality of clusters in a dataset. By systematically investigating the performance of k-means time series clustering with these two preprocessing techniques, this paper addresses the current gap in k-means time series clustering evaluation and contributes valuable insights to the development of time series clustering.

Paper Citation

in Harvard Style

Lee M., Lin J. and Stolz V. (2024). Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-684-2, SciTePress, pages 469-477. DOI: 10.5220/0012547200003654

in Bibtex Style

@conference{icpram24,
author={Ming-Chang Lee and Jia-Chun Lin and Volker Stolz},
title={Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2024},
pages={469-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012547200003654},
isbn={978-989-758-684-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free
SN - 978-989-758-684-2
AU - Lee M.
AU - Lin J.
AU - Stolz V.
PY - 2024
SP - 469
EP - 477
DO - 10.5220/0012547200003654
PB - SciTePress