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Cluster Ensembles

  • Conference paper
Classification — the Ubiquitous Challenge

Abstract

Cluster ensembles are collections of individual solutions to a given clustering problem which are useful or necessary to consider in a wide range of applications. Aggregating these to a “common” solution amounts to finding a consensus clustering, which can be characterized in a general optimization framework. We discuss recent conceptual and computational advances in this area, and indicate how these can be used for analyzing the structure in cluster ensembles by clustering its elements.

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Author information

Authors and Affiliations

  1. Institut für Statistik und Mathematik, Wirtschaftsuniversität Wien, Augasse 2-6, A-1090, Wien, Austria

    Kurt Hornik

Authors
  1. Kurt Hornik
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Editor information

Editors and Affiliations

  1. Fachbereich Statistik, Universität Dortmund, 44221, Dortmund

    Claus Weihs

  2. Institut für Entscheidungstheorie und Unternehmensforschung, Universität Karlsruhe (TH), 76128, Karlsruhe

    Wolfgang Gaul

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© 2005 Springer-Verlag Berlin · Heidelberg

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Hornik, K. (2005). Cluster Ensembles. In: Weihs, C., Gaul, W. (eds) Classification — the Ubiquitous Challenge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28084-7_6

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