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 |
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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 May 2022 12:44 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/66076 |
DOI: | 10.1016/j.tcs.2018.01.022 |
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