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Dynamic Determination of Mixing Parameters in Fuzzy Clustering

  • Mina Ryoke
  • Yoshiteru Nakamori
  • Hiroyuki Tamura
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

This paper considers the simultaneous determination of data classification and linear regression models. The clustering criterion introduced in this paper includes two types of mixing parameters to make a balance between two objectives of clustering: the minimization of variances within clusters and the minimization of regression errors. The paper proposes an idea on dynamic determination of those parameters in the clustering process.

Key words

Fuzzy clustering fuzzy modeling mixing parameters 

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References

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Mina Ryoke
    • 1
  • Yoshiteru Nakamori
    • 1
  • Hiroyuki Tamura
    • 2
  1. 1.Japan Advanced Institute of Science and TechnologyTatsunokuchi, IshikawaJapan
  2. 2.Osaka UniversityToyonakaJapan

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