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Weighted mean of a pair of clusterings

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Abstract

In this paper, we introduce the weighted mean of a pair of clusterings. Given two clusterings C 1 and C 2, the weighted mean of C 1 and C 2 is a clustering C w that has distances d(C 1, C w ) and d(C w , C 2) to C 1 and C 2, respectively, such that d(C 1, C w ) + d(C w , C 2) = d(C 1, C 2) holds for some clustering distance function d. C w is defined such that the sum of the distances d(C 1, C w ) and d(C w , C 2) is equal to the distance between C 1 and C 2. An algorithm for its computation will be presented. Experimental results on both synthetic and real data will be shown to illustrate the usefulness of the weighted mean concept. In particular, it gives a tool for the cluster ensemble techniques.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Münster, Münster, Germany

    Lucas Franek & Xiaoyi Jiang

  2. School of Business Administration, Sichuan University, Chengdu, China

    Changzheng He

Authors
  1. Lucas Franek
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  2. Xiaoyi Jiang
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  3. Changzheng He
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Correspondence to Lucas Franek.

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Franek, L., Jiang, X. & He, C. Weighted mean of a pair of clusterings. Pattern Anal Applic 17, 153–166 (2014). https://doi.org/10.1007/s10044-012-0304-8

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  • DOI: https://doi.org/10.1007/s10044-012-0304-8

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