Neuro-Fuzzy Classification

  • Detlef Nauck
  • Andreas Nürnberger
  • Rudolf Kruse
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


Neuro-fuzzy classification systems offer means to obtain fuzzy classification rules by a learning algorithm. It is usually possible to find a suitable fuzzy classifier by learning from data, but it can be hard to obtain a classifier that can be interpreted conveniently. However, the main reason for using fuzzy methods for classification is usually to obtain an interpretable classifier. In this paper we discuss the learning algorithms of NEFCLASS, a neuro-fuzzy approach for data analysis.


fuzzy classification neuro-fuzzy system 


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  1. H. R. Berenji and P. Khedkar (1992). Learning and Tuning Fuzzy Logic Controllers through Reinforcements. IEEE Trans. Neural Networks, 3: 724–740.Google Scholar
  2. J. J. Buckley and Y. Hayashi (1995). Neural Networks for Fuzzy Systems. Fuzzy Sets and Systems, 71: 265–276.Google Scholar
  3. D. Gustafson and W. Kessel (1979). Fuzzy Clustering with a Fuzzy Covariance Matrix. In Proc. IEEE CDC, pages 761–766, San Diego, CA.Google Scholar
  4. S. K. Halgamuge and M. Glesner (1994). Neural Networks in Designing Fuzzy Systems for Real World Applications. Fuzzy Sets and Systems, 65: 1–12.Google Scholar
  5. F. Klawonn and R. Kruse (1997). Constructing a Fuzzy Controller from Data. Fuzzy Sets and Systems, 85: 177–193.Google Scholar
  6. R. Kruse, J. Gebhardt and F. Klawonn (1994). Foundations of Fuzzy Systems. Wiley, Chichester.Google Scholar
  7. D. Nauck, F. Klawonn and R. Kruse (1997). Foundations of Neuro-Fuzzy Systems. Wiley, Chichester.Google Scholar
  8. D. Nauck and R. Kruse (1997a). A Neuro-Fuzzy Method to Learn Fuzzy Classification Rules from Data. Fuzzy Sets and Systems, 89: 277–288.Google Scholar
  9. D. Nauck and R. Kruse (1997b). New Learning Strategies for NEFCLASS. In Proc. Seventh International Fuzzy Systems Association World Congress IFSA’97, volume IV, pages 50-55, Prague.Google Scholar
  10. N. Tschichold-Giirman (1997). The Neural Network Model RuleNet and its Application to Mobile Robot Navigation. Fuzzy Sets and Systems, 85: 287–303.CrossRefGoogle Scholar
  11. W. Wolberg and O. Mangasarian (1990). Multisurface Method of Pattern Separation for Medical Diagnosis Applied to Breast Cytology. Proc. National Academy of Sciences, 87: 9193–9196.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Detlef Nauck
    • 1
  • Andreas Nürnberger
    • 1
  • Rudolf Kruse
    • 1
  1. 1.Faculty of Computer ScienceUniversity of MagdeburgMagdeburgGermany

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