Space distortion and monotone admissibility in agglomerative clustering
AbstractThis 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. --
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Bibliographic InfoPaper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 2001,78.
Date of creation: 2001
Date of revision:
monotonicity; admissibility; AHCA (agglomerative hierarchical clustering algorithm); space distortion;
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- Vladimir Batagelj, 1981. "Note on ultrametric hierarchical clustering algorithms," Psychometrika, Springer, vol. 46(3), pages 351-352, September.
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