Hybrid Fuzzy Clustering Using LP Norms

  • Tomasz Przybyła
  • Janusz Jeżewski
  • Krzysztof Horoba
  • Dawid Roj
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6591)


The fuzzy clustering methods are useful in the data mining applications. This paper describes a new fuzzy clustering method in which each cluster prototype is calculated as a value that minimizes introducted generalized cost function. The generalized cost function utilizes the L p norm. The fuzzy meridian is a special case of cluster prototype for p = 2 as well as the fuzzy meridian for p = 1. A method for the norm selection is proposed. An example illustrating the performance of the proposed method is given.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tomasz Przybyła
    • 1
  • Janusz Jeżewski
    • 2
  • Krzysztof Horoba
    • 2
  • Dawid Roj
    • 2
  1. 1.Institute of ElectronicsSilesian University of TechnologyGliwicePoland
  2. 2.Biomedical Signal Processing DepartmentInstitute of Medical Technology and EquipmentZabrzePoland

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