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Exclusion/Inclusion Fuzzy Classification Network

  • Andrzej Bargiela
  • Witold Pedrycz
  • Masahiro Tanaka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2773)

Abstract

The paper introduces an exclusion/inclusion fuzzy classification neural network. The network is based on our GFMM [3] and it allows for two distinct types of hyperboxes to be created: inclusion hyperboxes that correspond directly to those considered in GFMM, and exclusion hyperboxes that represent contentious areas of the pattern space. The subtraction of the exclusion hyperboxes from the inclusion hyperboxes, implemented by EFC, provides for a more efficient coverage of complex topologies of data clusters.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Andrzej Bargiela
    • 1
  • Witold Pedrycz
    • 2
    • 3
  • Masahiro Tanaka
    • 4
  1. 1.The Nottingham Trent UniversityNottinghamUK
  2. 2.University of AlbertaEdmontonCanada
  3. 3.Systems Research InstitutePolish Academy of SciencesPoland
  4. 4.Konan UniversityKobeJapan

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