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Two Methods of Fuzzy c-Means and Classification Functions

  • Sadaaki Miyamoto
  • Kazutaka Umayahara
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

A regularization method using an entropy function is studied and contrasted with the ordinary fuzzy c-means. The way in which two algorithms lead to similar formulas is discussed. Classification functions derived from the two methods, which are naturally obtained when the algorithm of clustering is convergent, are compared. Theoretical properties of the two classification functions are studied.

Keywords

Fuzzy c-means Regularization Entropy Classification Rule 

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References

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Sadaaki Miyamoto
    • 1
  • Kazutaka Umayahara
    • 1
  1. 1.Institute of Information Sciences and ElectronicsUniversity of TsukubaIbaraki 305Japan

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