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CONVEX CLUSTERING FOR AUTOCORRELATED TIME SERIES

Max Revay, Victor Solo

DOI
10.17023/5s5v-0036
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    Length: 00:13:39
08 May 2022

While clustering in general is a heavily worked area, clustering of auto-correlated time series (CATS) has received relatively little attention. Here, we develop a convex clustering algorithm suited to auto-correlated time series and compare it with a state of the art method. We find the proposed algorithm is able to more accurately identify the true clusters.

Tags:
time series analysis
time series clustering
data mining
convex clustering
unsupervised learning

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