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Space distortion and monotone admissibility in agglomerative clustering

Author

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  • Takeuchi, Akinobu
  • Yadohisa, Hiroshi
  • Inada, Koichi

Abstract

This paper discusses the admissibility of agglomerative hierarchical clustering algorithms with respect to space distortion and monotonicity, as defined by Yadohisa et al. and Batagelj, respectively. Several admissibilities and their properties are given for selecting a clustering algorithm. Necessary and sufficient conditions for an updating formula, as introduced by Lance and Williams, are provided for the proposed admissibility criteria. A detailed explanation of the admissibility of eight popular algorithms is also given.

Suggested Citation

  • Takeuchi, Akinobu & Yadohisa, Hiroshi & Inada, Koichi, 2001. "Space distortion and monotone admissibility in agglomerative clustering," SFB 373 Discussion Papers 2001,78, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:200178
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    References listed on IDEAS

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    1. Vladimir Batagelj, 1981. "Note on ultrametric hierarchical clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 46(3), pages 351-352, September.
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