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A benchmark calculation for the fuzzy c-means clustering algorithm: initial memberships

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Abstract

We report a benchmark calculation for the fuzzy c-means clustering algorithm that can be used as a reference in theoretical and practical studies related to classification methodologies. A full exploration of the hard-initialization space is done for all possible different groupings on a simple fifteen-pattern system to describe their stationary points. Numerical problems associated with the stopping criteria are discussed in relation with the calculation of some validity indexes. All necessary information to assure an easy reproduction of the obtained results is clearly reported.

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Authors and Affiliations

  1. Department d’Enginyeria Química, Universitat Politècnica de Catalunya (UPC), ETS d’Enginyeria Industrial, Av. Diagonal 647, 08028, Barcelona, Spain

    Alex Rodriguez

  2. Sec. Matemàtiques i Informàtica ETSAB, Universitat Politècnica de Catalunya (UPC), ETS d’Arquitectura, Av. Diagonal 649, 08028, Barcelona, Spain

    M. Santos Tomas

  3. Dept. de Química Física, Universitat de Barcelona (UB) and the Institut de Recerca en Química Teòrica i Computacional (IQTCUB), Martí i Franqués 1, 08028, Barcelona, Spain

    Jaime Rubio-Martinez

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  1. Alex Rodriguez
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  2. M. Santos Tomas
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  3. Jaime Rubio-Martinez
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Correspondence to Jaime Rubio-Martinez.

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Rodriguez, A., Tomas, M.S. & Rubio-Martinez, J. A benchmark calculation for the fuzzy c-means clustering algorithm: initial memberships. J Math Chem 50, 2703–2715 (2012). https://doi.org/10.1007/s10910-012-0059-x

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  • DOI: https://doi.org/10.1007/s10910-012-0059-x

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