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Medical Discriminant Analysis by Modular Fuzzy Model

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 15)

Abstract

Since the number of rules of the single input rule modules connected fuzzy inference method (SIRMs method) is limited as compared to the conventional fuzzy inference method, inference results gained by the SIRMs method are simple in general. From this reason, Watanabe et al. have proposed a modular fuzzy model which extends the SIRMs method, and shown that this model can obtain good results for reinforcement learning. In this paper, this model is compared with the conventional fuzzy inference method by applying to discriminant analysis of a medical data.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Kwansei Gakuin UniversitySanda-shiJapan
  2. 2.Osaka Electro-Communication UniversityNeyagawa-shiJapan

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