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Hyperellipsoidal Clustering

  • Yoshiteru Nakamori
  • Mina Ryoke
Part of the International Series in Intelligent Technologies book series (ISIT, volume 7)

Abstract

We present a hyperellipsoidal clustering method that becomes the focal point of the fuzzy modeling procedure. The aim of developing a clustering algorithm is to control the shapes of clusters flexibly. This is achieved to a great extent by introducing design and tuning parameters. We propose a simple clustering algorithm which combines hierarchical and non-hierarchical procedures, and dose not require a priori assumption on the number, centroids, and volumes of clusters.

Keywords

Membership Function Fuzzy Model Fuzzy Cluster Conditional Variable Initial Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Yoshiteru Nakamori
    • 1
  • Mina Ryoke
    • 1
  1. 1.Department of Applied MathematicsKonan UniversityHigashinada-ku, KobeJapan

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