UPGMA and the normalized equidistant minimum evolution problem

Moulton, Vincent, Spillner, Andreas and Wu, Taoyang (2018) UPGMA and the normalized equidistant minimum evolution problem. Theoretical Computer Science, 721. pp. 1-15. ISSN 0304-3975

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Abstract

UPGMA (Unweighted Pair Group Method with Arithmetic Mean) is a widely used clustering method. Here we show that UPGMA is a greedy heuristic for the normalized equidistant minimum evolution (NEME) problem, that is, finding a rooted tree that minimizes the minimum evolution score relative to the dissimilarity matrix among all rooted trees with the same leaf-set in which all leaves have the same distance to the root. We prove that the NEME problem is NP-hard. In addition, we present some heuristic and approximation algorithms for solving the NEME problem, including a polynomial time algorithm that yields a binary, rooted tree whose NEME score is within O(log2n) of the optimum.

Item Type: Article
Uncontrolled Keywords: upgma,minimum evolution,balanced minimum evolution,hierarchical clustering
Faculty \ School: Faculty of Science > School of Computing Sciences
Depositing User: Pure Connector
Date Deposited: 25 Jan 2018 15:30
Last Modified: 24 Mar 2020 01:44
URI: https://ueaeprints.uea.ac.uk/id/eprint/66076
DOI: 10.1016/j.tcs.2018.01.022

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