Neuro-fuzzy Rough Classifier Ensemble

  • Marcin Korytkowski
  • Robert Nowicki
  • Rafał Scherer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5768)


The paper proposes a new ensemble of neuro-fuzzy rough set classifiers. The ensemble uses fuzzy rules derived by the Adaboost metalearning. The rules are used in an ensemble of neuro-fuzzy rough set systems to gain the ability to work with incomplete data (in terms of missing features). This feature is not common among different machine learning methods like neural networks or fuzzy systems. The systems are combined into the larger ensemble to achieve better accuracy. Simulations on a well-known benchmark showed the ability of the proposed system to perform relatively well.


Neuro-fuzzy rough sets classifier ensemble 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley-Interscience Publication, Hoboken (2000)zbMATHGoogle Scholar
  2. 2.
    Jang, R.J.S., Sun, C.T., Mizutani, E.: Neuro-Fuzzy and Soft Computing, A Computational Approach to Learning and Machine Intelligence. Prentice Hall, Upper Saddle River (1997)Google Scholar
  3. 3.
    Kuncheva, L.I.: Fuzzy Classifier Design. Studies in Fuzziness and Soft Computing. Physica-Verlag, Heidelberg (2000)CrossRefzbMATHGoogle Scholar
  4. 4.
    Kuncheva, L.: Foundations of Neuro-Fuzzy Systems. John Wiley, Chichester (1997)Google Scholar
  5. 5.
    Wang, L.X.: Adaptive Fuzzy Systems and Control. PTR Prentice Hall, Englewood Cliffs (1994)Google Scholar
  6. 6.
    Rutkowski, L.: Flexible Neuro-Fuzzy Systems. Kluwer Academic Publishers, Dordrecht (2004)zbMATHGoogle Scholar
  7. 7.
    Kuncheva, L.: Combining Pattern Classifiers. John Wiley & Sons, Chichester (2004)CrossRefzbMATHGoogle Scholar
  8. 8.
    Pawlak, Z.: Rough sets. International Journal of Information and Computer Science 11, 341–356 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer, Dordrecht (1991)CrossRefzbMATHGoogle Scholar
  10. 10.
    Pawlak, Z.: Rough sets, decision algorithms and bayes’ theorem. European Journal of Operational Research 136, 181–189 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    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, pp. 1274–1277 (2006)Google Scholar
  12. 12.
    Dubois, D., Prade, H.: Putting rough sets and fuzzy sets together. In: Słowiński, R. (ed.) Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, pp. 203–232. Kluwer, Dordrecht (1992)CrossRefGoogle Scholar
  13. 13.
    Dubois, D., Prade, H.: Rough fuzzy sets and fuzzy rough sets. Internat. J. General Systems 17, 191–209 (1990)CrossRefzbMATHGoogle Scholar
  14. 14.
    Breiman, L.: Bias, variance, and arcing classifiers. Technical Report 460, Statistics Department, University of California (1997)Google Scholar
  15. 15.
    Meir, R., Rätsch, G.: An introduction to boosting and leveraging. In: Mendelson, S., Smola, A.J. (eds.) Advanced Lectures on Machine Learning. LNCS (LNAI), vol. 2600, pp. 118–183. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  16. 16.
    Schapire, R.E.: A brief introduction to boosting. In: Conference on Artificial Intelligence, pp. 1401–1406 (1999)Google Scholar
  17. 17.
    Asuncion, A., Newman, D.: Uci machine learning repository (2007),

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Marcin Korytkowski
    • 1
    • 2
  • Robert Nowicki
    • 1
    • 3
  • Rafał Scherer
    • 1
    • 3
  1. 1.Department of Computer EngineeringCzęstochowa University of TechnologyCzęstochowaPoland
  2. 2.Olsztyn Academy of Computer Science and ManagementOlsztynPoland
  3. 3.Department of Artificial IntelligenceAcademy of Humanities and Economics in ŁódźŁódźPoland

Personalised recommendations