Useful Clustering Outcomes from Meaningful Time Series Clustering
Clustering time series data using the popular subsequence (STS) technique has been widely used in the data mining and wider communities. Recently the conclusion was made that it is meaningless, based on the findings that it produces (a) clustering outcomes for distinct time series that are not distinguishable from one another, and (b) cluster centroids that are smoothed. More recent work has since showed that (a) could be solved by introducing a lag in the subsequence vector construction...[Show more]
|Collections||ANU Research Publications|
|Book Title:||Data Mining and Analytics 2007|
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