Clustering Methods over the Tropical Projective Torus

David Barnhill and Ruriko Yoshida ()
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David Barnhill: Naval Postgraduate School, 1411 Cunningham Road, Monterey, CA 93943-5219, USA
Ruriko Yoshida: Naval Postgraduate School, 1411 Cunningham Road, Monterey, CA 93943-5219, USA

Mathematics, 2023, vol. 11, issue 15, 1-22

Abstract: In this paper, we propose clustering methods for use on data described as tropically convex. Our approach is similar to clustering methods used in the Euclidean space, where we identify groupings of similar observations using tropical analogs of K-means and hierarchical clustering in the Euclidean space. We provide results from computational experiments on generic simulated data as well as an application to phylogeny using ultrametrics, demonstrating the efficacy of these methods.

Keywords: convexity; phylogenetic trees; tropical geometry; unsupervised learning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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