Evolving fuzzy rule-based classifiers

Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, CIISP 2007

Volumn , Issue , 2007, Pages 220-225

  Angelov, Plamen ^a   Zhou, Xiaowei ^a   Klawonn, Frank ^b  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF APPLIED SCIENCES   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTATIONAL LINGUISTICS; DATA STRUCTURES; LEARNING SYSTEMS; REAL TIME SYSTEMS; ROBOTICS;

FUZZY RULE-BASED CLASSIFIERS; LANDMARK RECOGNITION; REAL-LIFE DATA; REAL-TIME MACHINES;

FUZZY RULES;

EID: 34548752445     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIISP.2007.369172     Document Type: Conference Paper

References (29)

1. R. O. Duda, P. E. Hart, and D.G. Stork. "Pattern Classification" Second Edition. Wiley-Interscience, Chichester, West Sussex, England, 2000.
2. U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, From Data Mining to Knowledge Discovery: An, Overview, Advances in, Knowledge Discovery and Data Mining, MIT Press, Cambridge, Massachusetts, USA, 1996.
3. P. Domingos and G. Hulten, " Catching Up with the Data: Research, Issues in Mining Data Streams, Workshop on Research Issues in Data Mining and Knowledge Discovery, Santa Barbara, CA, USA, 2001.
4. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference and Prediction. Heidelberg, Germany: Springer Verlag, 2001.
5. V. N. Vapnik, The Statistical Learning Theory, Springer Verlag, Berlin, Germany, 1998.
6. V. Kecman. Learning and Soft Computing. MIT Press, Cambridge, Massachusetts, London, England, 2001.
7. J. R. Quinlan, "Simplifying decision, trees", International Journal of Man-Machine Studies, vol. 27, No3, pp.221-234, 1987.
8. C. M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, Oxford, UK, 1995.
9. M. Butz, Rule-based Evolutionary Online Learning Systems: A Principal Approach to LCS Analysis and Design, Physica Verlag, v.191, Berlin, Heidelberg, Germany, 2006, ISBN 3-540-25379-3.
10. K. M. A. Chai, H. T. Ng, and H. L. Chieu, "Bayesian Online Classifiers for Text Classification and Filtering", Proc.of the SIGIR'02, August 11-15, 2002, pp. 97-104, Tampere, Finland.
11. F. Klawonn and P. Angelov, Evolving Extended Naive Bayesian Classifier, 2006 IEEE Intern. Conf. on Data Mining, 18-22 December, 2006, Hong Kong, to appear
12. P. Angelov, Evolving Rule-based Models: A Tool for Design of Flexible Adaptive Systems. Heidelberg, Germany: Springer Verlag, 2002.
13. P. Angelov and D. Filev, "An approach to on-line identification of evolving Takagi-Sugeno models", IEEE Transactions on Systems, Man and Cybernetics, part B, Cybernetics, vol.34, No1, pp. 484-498, 2004.
14. P. Angelov and R. Buswell, "Identification of Evolving Rule-based Models", IEEE Transactions on Fuzzy Systems, vol.10, No5, pp.667-677, 2002.
15. P. Angelov, V. Giglio, C. Guardiola, E. Lughofer, and J. M. Lujan, "An, Approach to Model-based Fault Detection in In- dustrial Measurement Systems with Application to Engine Test Benches", Measurement Science and Technology, vol. 17, No7, 2006, pp. 1809-1818.
16. P. Angelov, "A Fuzzy Controller with Evolving Structure", Information Sciences, ISSN 0020-0255, vol.161, 2004, pp.21-35.
17. A. S. Hornby, Oxford Advance Learner's Dictionary, Oxford University Press, UK, 1974.
18. B. Fritzke, "Growing cell structures - a self-organizing network for unsupervised and supervised learning", Neural Networks, vol. 7, No 9, pp.1441-1460, 1994.
19. N. Kasabov, "Evolving fuzzy neural networks for on-line supervised/unsupervised, knowledge-based learning," IEEE Transactions on Systems, Man, and cybernetics, part B - Cybernetics, vol. 31, PP. 902-918, 2001.
20. R. Jin and G. Agrawal, "Efficient Decision Tree Construction, on Streaming Data", Proc. of ACM SIGKDD, 2003.
21. th IFSA World Congress, Vancouver, BC, Canada, 25-28 July 2001, pp. 1062-1067.
22. P. Angelov and X. Zhou, "Evolving Fuzzy Systems from Data Streams in Real-Time", Proc. 2006 International Symposium on Evolving Fuzzy Systems, UK, IEEE Press, pp.29-35, September 2006, ISBN 0-7803-9719-3.
23. st IEEE International Conference on Fuzzy Systems, FUZZ-IEEE, San Diego, CA, USA, pp.1163-1170, 1992.
24. R. R. Yager and D. P. Filev, "Learning of Fuzzy Rules by Mountain Clustering," Proc. of SPIE Conference on Application of Fuzzy Logic Technology, Boston, MA, USA, pp.246-254, 1993.
25. H. Ishibuchi and T. Nakashima, "Voting in fuzzy rule-based systems for pattern, classification problems", Fuzzy Sets and Systems, vol. 103, pp.223-238, 1999.
26. P. Angelov and D. Filev, "Simpl_eTS: A Simplified Method for Learning Evolving Takagi-Sugeno Fuzzy Models", The 2005 IEEE International Conference on Fuzzy Systems FUZZ-IEEE, Reno, Las Vegas, USA, 22-25 May 2005, pp.1068-1073, ISSN 0-7803-9158-6/05.
27. st IEEE Symposium on Computational Intelligence for Security and Defense Applications, CISDA 2007, April 1-5, 2007 Honolulu, HI, USA, to appear.
28. S.Pang, S.Ozawa, and N.Kasabov, "Incremental Linear Discriminant Analysis for Classification of Data Streams", IEEE Transactions on Systems, Man, And Cybernetics -Part B: Cybernetics, Vol35, No.5, October 2005.
29. E. Lughofer and E. Klement, "FLEXFIS: A variant for incremental learning of Takagi-Sugeno fuzzy systems," in Proceedings of FUZZ-IEEE 2005, Reno, Nevada, U.S.A., 2005.