License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.STACS.2011.308
URN: urn:nbn:de:0030-drops-29942
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2011/2994/
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Ackermann, Marcel R. ; Bloemer, Johannes ; Kuntze, Daniel ; Sohler, Christian

Analysis of Agglomerative Clustering

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Abstract

The diameter k-clustering problem is the problem of partitioning a finite subset of R^d into k subsets called clusters such that the maximum diameter of the clusters is minimized. One early clustering algorithm that computes a hierarchy of approximate solutions to this problem for all values of k is the agglomerative clustering algorithm with the complete linkage strategy. For decades this algorithm has been widely used by practitioners. However, it is not well studied theoretically. In this paper we analyze the agglomerative complete linkage clustering algorithm. Assuming that the dimension dis a constant, we show that for any k the solution computed by this algorithm is an O(log k)-approximation to the diameter k-clustering problem. Moreover, our analysis does not only hold for the Euclidean distance but for any metric that is based on a norm.

BibTeX - Entry

@InProceedings{ackermann_et_al:LIPIcs:2011:2994,
  author =	{Marcel R. Ackermann and Johannes Bloemer and Daniel Kuntze and Christian Sohler},
  title =	{{Analysis of Agglomerative Clustering}},
  booktitle =	{28th International Symposium on Theoretical Aspects of Computer Science (STACS 2011) },
  pages =	{308--319},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-25-5},
  ISSN =	{1868-8969},
  year =	{2011},
  volume =	{9},
  editor =	{Thomas Schwentick and Christoph D{\"u}rr},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2011/2994},
  URN =		{urn:nbn:de:0030-drops-29942},
  doi =		{10.4230/LIPIcs.STACS.2011.308},
  annote =	{Keywords: agglomerative clustering, hierarchical clustering, complete linkage, approximation guarantees}
}

Keywords: agglomerative clustering, hierarchical clustering, complete linkage, approximation guarantees
Collection: 28th International Symposium on Theoretical Aspects of Computer Science (STACS 2011)
Issue Date: 2011
Date of publication: 11.03.2011


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