Neuro-fuzzy systems for explaining data sets

Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Volumn 2002-January, Issue , 2002, Pages 195-200

  Nauck, D D ^a  

^a MARTLESHAM HEATH   (United Kingdom)

Author keywords

Customer relationship management; Data analysis; Data visualization; Electronic mail; Fuzzy neural networks; Fuzzy systems; Intelligent systems; Predictive models; Web and internet services; World Wide Web

Indexed keywords

DATA REDUCTION; DATA VISUALIZATION; ELECTRONIC MAIL; FUZZY INFERENCE; FUZZY LOGIC; FUZZY NEURAL NETWORKS; FUZZY RULES; FUZZY SYSTEMS; INFORMATION SCIENCE; INTELLIGENT SYSTEMS; INTERNET; PUBLIC RELATIONS; VISUALIZATION; WEB SERVICES; WORLD WIDE WEB;

CUSTOMER RELATIONSHIP MANAGEMENT; INTERACTIVE EXPLORATION; INTERNET SERVICES; INTERPRETABLE FUZZY RULES; MOBILE WORKFORCE; NEUROFUZZY SYSTEM; PREDICTIVE MODELS; WORKFORCE MANAGEMENT;

INFORMATION MANAGEMENT;

EID: 0037597515     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NAFIPS.2002.1018054     Document Type: Conference Paper

References (14)

1. 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.
2. 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.
3. 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.
4. Cezary Z. Janikow. Fuzzy decision trees: Issues and methods. IEEE Trans. Systems, Man & Cybernetics. Part B: Cybernetics, 28(1):1-14, 1998.
5. 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.
6. 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.
7. 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.
8. Detlef Nauck. Adaptive rule weights in neuro-fuzzy systems. Neural Computing & Applications, 9(1):60-70, 2000.
9. 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.
10. Detlef Nauck, Frank Klawonn, and Rudolf Kruse. Foundations of Neuro-Fuzzy Systems. Wiley, Chichester, 1997.
11. Detlef Nauck and Rudolf Kruse. How the learning of rule weights affects the interpretabiiity of fuzzy systems. In Proc. IEEE Int. Conf. on Fuzzy Systems 1998, pages 1235-1240, Anchorage, May 1998.
12. 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.
13. J.R. Quinlan. Induction of decision trees. Machine Learning, 1:81-106, 1986.
14. 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, Singapore, 1997.