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Modular Rough Neuro-fuzzy Systems for Classification

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Parallel Processing and Applied Mathematics (PPAM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4967))

Abstract

In the paper we propose a new class of modular systems for classification in the case of missing features. We incorporate the rough set theory into construction of neuro-fuzzy systems which create the modular structure. The AdaBoost algorithm is combined with the gradient algorithm to train the whole system. We illustrate the performance of our approach on typical benchmarks.

This work was supported in part by the Foundation for Polish Science (Professorial Grant 2005-2008) and the Polish Ministry of Science and Higher Education (Special Research Project 2006-2009) and by science funds for 2007-2010 as research project Nr N N516 1155 33.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Czȩstochowa University of Technology, al. Armii Krajowej 36, 42-200, Czȩstochowa, Poland

    Rafał Scherer, Marcin Korytkowski, Robert Nowicki & Leszek Rutkowski

  2. Department of Artificial Intelligence, Academy of Humanities and Economics in Lodz, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer, Robert Nowicki & Leszek Rutkowski

  3. Olsztyn Academy of Computer Science and Management, ul. Artyleryjska 3c, 10-165, Olsztyn, Poland

    Marcin Korytkowski

Authors
  1. Rafał Scherer
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  2. Marcin Korytkowski
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  3. Robert Nowicki
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  4. Leszek Rutkowski
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Editor information

Roman Wyrzykowski Jack Dongarra Konrad Karczewski Jerzy Wasniewski

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Scherer, R., Korytkowski, M., Nowicki, R., Rutkowski, L. (2008). Modular Rough Neuro-fuzzy Systems for Classification. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2007. Lecture Notes in Computer Science, vol 4967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68111-3_56

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  • DOI: https://doi.org/10.1007/978-3-540-68111-3_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68105-2

  • Online ISBN: 978-3-540-68111-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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