From ensemble of fuzzy classifiers to single fuzzy rule base classifier

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5097 LNAI, Issue , 2008, Pages 265-272

  Korytkowski, Marcin ^a,b   Rutkowski, Leszek ^a,c   Scherer, Rafał ^a,c  

^a CZESTOCHOWA UNIVERSITY OF TECHNOLOGY   (Poland)

^b Academy of Computer Science and Management   (Poland)

^c Wyzsza Szkola Humanistyczno Ekonomiczna w Lodzi   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; CYBERNETICS; FUZZY LOGIC; FUZZY RULES; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; SOFT COMPUTING;

ADABOOST; EXCELLENT PERFORMANCE; FUZZY CLASSIFIERS; FUZZY RULE BASE; INTERNATIONAL CONFERENCES; INTERPRETABILITY; KNOWLEDGE BASE; NEURO-FUZZY SYSTEMS; RULE BASES;

FUZZY SYSTEMS;

EID: 48249090550     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69731-2_26     Document Type: Conference Paper

References (18)

1. Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press Inc., New York (1995)
2. Bezdek, J.C., Pal, S.K.: Fuzzy Models for Pattern Recognition. IEEE Press, New York (1992)
3. Bezdek, J., Keller, J., Krisnapuram, R., Pal, N.R.: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing. Kluwer Academic Press, Norwell (1999)
4. Asuncion, A., Newman, D.J.: UCI Machine Learning Repository, University of California, School of Information and Computer Science, Irvine, CA (2007), http://www.ics.uci.edu/$\sim$mlearn/{MLR}epository.html
5. Breiman, L.: Bias, variance, and arcing classifiers, Technical Report 460, Statistics Department, University of California (1997)
6. Czogała, E., Łȩski, J.: Fuzzy and Neuro Fuzzy Intelligent Systems. Physica Verlag, Heidelberg (2000)
7. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. Wiley, Chichester (2000)
8. Konar, A.: Computational Intelligence. Springer, Heidelberg (2005)
9. Kuncheva, L.I.: Fuzzy Classifier Design. Physica Verlag, Heidelberg (2000)
10. Kuncheva, L.I.: Combining Pattern Classifiers, Methods and Algorithms. John Wiley & Sons, Chichester (2004)
11. Łȩski, J.: A Fuzzy If-Then Rule-Based Nonlinear Classifier. Int. J. Appl. Math. Comput. Sci. 13(2), 215-223 (2003)
12. Meir., R., Ratsch, G.: An Introduction to Boosting and Leveraging. Advanced Lectures on Machine Learning (2003)
13. Korytkowski, M., Rutkowski, L., Scherer, R.: On Combining Backpropagation with Boosting. In: 2006 International Joint Conference on Neural Networks, IEEE World Congress on Computational Intelligence, Vancouver, BC, Canada (2006)
14. Łȩski, J.: A Fuzzy If-Then Rule-Based Nonlinear Classifier. Int. J. Appl. Math. Comput. Sci. 13(2), 215-223 (2003)
15. Rutkowski, R.: Flexible Neuro-Fuzzy Systems. Kluwer Academic Publishers, Dordrecht (2004)
16. Schapire, R.E.: A brief introduction to boosting. In: Proc. of the Sixteenth International Joint Conference on Artificial Intelligence (1999)
17. Świniarski, R.W.: Rough Sets Methods in Feature Reduction and Classification. Int. J. Appl. Math. Comput. Sci. 11(3), 565-582 (2001)
18. Wang, L.-X.: Adaptive Fuzzy Systems And Control. PTR Prentice Hall, Englewood Cliffs (1994)