Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform.

This study develops a new clustering method for high-dimensional zero-inflated time series data. The proposed method is based on thick-pen transform (TPT), in which the basic idea is to draw along the data with a pen of a given thickness. Since TPT is a multi-scale visualization technique, it provides some information on the temporal tendency of neighborhood values. We introduce a modified TPT, termed 'ensemble TPT (e-TPT)', to enhance the temporal resolution of zero-inflated time series data that is crucial for clustering them efficiently. Furthermore, this study defines a modified similarity measure for zero-inflated time series data considering e-TPT and proposes an efficient iterative clustering algorithm suitable for the proposed measure. Finally, the effectiveness of the proposed method is demonstrated by simulation experiments and two real datasets: step count data and newly confirmed COVID-19 case data. © The Author(s) 2023.

Citation

Minji Kim, Hee-Seok Oh, Yaeji Lim. Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform. Journal of classification. 2023 Jun 12:1-25

PMID: 37359508

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