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An Evolutionary Clustering Algorithm

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

There are many heuristic algorithms for clustering, from which the most important are the hierarchical methods of agglomeration, especially the Ward’s method. Among the iterative methods the most universally used is the C–means method and it’s generalizations. These methods have many advantages, but they are more or less dependent on the distribution of points in space and the shape of clusters. In this paper the problem of clustering is treated as a problem of optimization of a certain quality index. For that problem the author proposes two solutions: a hierarchical partitioning algorithm and an evolutionary algorithm.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Systems, Technical University of Szczecin, Zolnierska Street 49, Pl-71210, Szczecin, Poland

    Marcin Korzeń

Authors
  1. Marcin Korzeń
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Korzeń, M. (2004). An Evolutionary Clustering Algorithm. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_62

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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