Unfolding preprocessing for meaningful time series clustering.

Geoffroy Simon; John A Lee; Michel Verleysen

doi:10.1016/j.neunet.2006.05.020

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Unfolding preprocessing for meaningful time series clustering.

Geoffroy Simon·John A Lee·Michel Verleysen

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Abstract

Clustering methods are commonly applied to time series, either as a preprocessing stage for other methods or in their own right. In this paper it is explained why time series clustering may sometimes be considered as meaningless. This problematic situation is illustrated for various raw time series. The unfolding preprocessing methodology is then introduced. The usefulness of unfolding preprocessing is illustrated for various time series. The experimental results show the meaningfulness of the clustering when applied on adequately unfolded time series.

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Cluster Analysis Data Interpretation, Statistical Humans Nonlinear Dynamics Signal Processing, Computer-Assisted Time Factors Comparative Study Journal Article Research Support, Non-U.S. Gov't

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Geoffroy Simon, John A Lee, Michel Verleysen. 2006-07-03. Unfolding preprocessing for meaningful time series clustering.. https://doi.org/10.1016/j.neunet.2006.05.020

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