Probabilistic K-means with Local Alignment for Clustering and Motif Discovery in Functional Data

Marzia A. Cremona & Francesca Chiaromonte
We develop a new method to locally cluster curves and discover functional motifs, that is, typical shapes that may recur several times along and across the curves capturing important local characteristics. In order to identify these shared curve portions, our method leverages ideas from functional data analysis (joint clustering and alignment of curves), bioinformatics (local alignment through the extension of high similarity seeds) and fuzzy clustering (curves belonging to more than one cluster, if they...
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