Skip to main content

Neuro-Fuzzy Systems for Explaining Data Sets

  • Chapter
Do Smart Adaptive Systems Exist?

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 173))

  • 604 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ben Azvine, Colin Ho, Stewart Kay, Detlef Nauck, and Martin Spott. Estimating travel times of field engineers. BT Technology Journal, 21(4): 33–38, October 2003.

    Article  Google Scholar 

  2. Ben Azvine, Detlef Nauck, and Colin Ho. Intelligent business analytics — a tool to build decision-support sytems for eBusinesses. BT Technology Journal, 21(4): 65–71, October 2003.

    Article  Google Scholar 

  3. Hugues Bersini, Gianluca Bontempi, and Mauro Birattari. Is readability compatible with accuracy? From neuro-fuzzy to lazy learning. In Fuzzy-Neuro Systems’ 98 — Computational Intelligence. Proc. 5th Int. Workshop Fuzzy-Neuro-Systems’ 98 (FNS’98) in Munich, Germany, volume 7 of Proceedings in Artifical Intelligence, pages 10–25, Sankt Augustin, 1998. infix.

    Google Scholar 

  4. J. Casillas, O. Cordon, F. Herrera, and L. Magdalena, editors. Trade-off between Accuracy and Interpretability in Fuzzy Rule-Based Modelling. Studies in Fuzziness and Soft Computing. Physica-Verlag, Heidelberg, 2002.

    Google Scholar 

  5. Colin Ho and Ben Azvine. Mining travel data with a visualiser. In Proc. International Workshop on Visual Data Mining at the 2nd European Conference on Machine Learning (ECML’01) and 5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD’01), Freiburg, 2001.

    Google Scholar 

  6. Colin Ho, Ben Azvine, Detlef Nauck, and Martin Spott. An intelligent travel time estimation and management tool. In Proc. 7th European Conference on Networks and Optical Communications (NOC 2002), pages 433–439, Darmstadt, 2002.

    Google Scholar 

  7. Cezary Z. Janikow. Fuzzy decision trees: Issues and methods. IEEE Trans. Systems, Man & Cybernetics. Part B: Cybernetics, 28(1): 1–14, 1998.

    Article  Google Scholar 

  8. Aljoscha Klose, Andreas Nürnberger, and Detlef Nauck. Some approaches to improve the interpretability of neuro-fuzzy classifiers. In Proc. Sixth European Congress on Intelligent Techniques and Soft Computing (EUFIT98), pages 629–633, Aachen, 1998.

    Google Scholar 

  9. I. Kononenko. On biases in estimating multi-valued attributes. In Proc. 1st International Conference on Knowledge Discovery and Data Mining, pages 1034–1040, Montreal, 1995.

    Google Scholar 

  10. Ludmilla I. Kuncheva. Fuzzy Classifier Design. Springer-Verlag, Heidelberg, 2000.

    Google Scholar 

  11. Detlef Nauck. NEFCLASS. Univ. of Magdeburg, WWW, 1998. http://fuzzy.cs.uni-magdeburg.de/nefclass.

    Google Scholar 

  12. Detlef Nauck. Using symbolic data in neuro-fuzzy classification. In Proc. 18th International Conf. of the North American Fuzzy Information Processing Society (NAFIPS99), pages 536–540, New York, NY, 1999. IEEE.

    Google Scholar 

  13. Detlef Nauck. Adaptive rule weights in neuro-fuzzy systems. Neural Computing & Applications, 9(1): 60–70, 2000.

    Article  Google Scholar 

  14. Detlef Nauck. Fuzzy data analysis with nefclass. In Proc. Joint 9th IFSA World Congress and 20th NAFIPS International Conference, pages 1413–1418, Piscataway, July 2001. IEEE.

    Google Scholar 

  15. Detlef Nauck. Measuring interpretability in rule-based classification systems. In Proc. IEEE Int. Conf. on Fuzzy Systems 2003, pages 196–201, St. Louis, MO, 2003. IEEE.

    Google Scholar 

  16. Detlef Nauck, Frank Klawonn, and Rudolf Kruse. Foundations of Neuro-Fuzzy Systems. Wiley, Chichester, 1997.

    Google Scholar 

  17. Detlef Nauck and Rudolf Kruse. How the learning of rule weights affects the interpretability of fuzzy systems. In Proc. IEEE Int. Conf. on Fuzzy Systems 1998, pages 1235–1240, Anchorage, May 1998.

    Google Scholar 

  18. Detlef Nauck and Rudolf Kruse. NEFCLASS-J — a Java-based soft computing tool. In Behnam Azvine, Nader Azarmi, and Detlef Nauck, editors, Intelligent Systems and Soft Computing: Prospects, Tools and Applications, number 1804 in Lecture Notes in Artificial Intelligence, pages 143–164. Springer-Verlag, Berlin, 2000.

    Google Scholar 

  19. J.R. Quinlan. Induction of decision trees. Machine Learning, 1: 81–106, 1986.

    Google Scholar 

  20. J.R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufman, San Mateo, CA, 1993.

    Google Scholar 

  21. Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques with JAVA Implementations. Morgan Kaufmann Publishers, San Francisco, CA, 2000. Software available at http://www.cs.waikato.ac.nz/~ml/.

    Google Scholar 

  22. Qingqing Zhou, Martin Purvis, and Nikola Kasabov. A membership function selection method for fuzzy neural networks. In Proc. of Int. Conf. Neural Information Processing and Intelligent Systems ICONIP/ANZIIS/ANNES’97, volume II, pages 785–788, Dunedin, 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Nauck, D.D. (2005). Neuro-Fuzzy Systems for Explaining Data Sets. In: Gabrys, B., Leiviskä, K., Strackeljan, J. (eds) Do Smart Adaptive Systems Exist?. Studies in Fuzziness and Soft Computing, vol 173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32374-0_15

Download citation

  • DOI: https://doi.org/10.1007/3-540-32374-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24077-8

  • Online ISBN: 978-3-540-32374-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics