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Online Learning Algorithm for Ensemble of Decision Rules

  • Igor Chikalov
  • Mikhail Moshkov
  • Beata Zielosko
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6743)

Abstract

We describe an online learning algorithm that builds a system of decision rules for a classification problem. Rules are constructed according to the minimum description length principle by a greedy algorithm or using the dynamic programming approach.

Keywords

decision rules online learning greedy algorithm dynamic programming 

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References

  1. 1.
    Moshkov, M., Piliszczuk, M., Zielosko, B.: Partial Covers, Reducts and Decision Rules in Rough Sets: Theory and Applications. Studies in Computational Intelligence, vol. 145. Springer, Heidelberg (2008)zbMATHGoogle Scholar
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    Pawlak, Z.: Rough Sets—Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)zbMATHGoogle Scholar
  3. 3.
    Rissanen, J.: Modeling by shortest data description. Automatica 14, 465–471 (1978)CrossRefzbMATHGoogle Scholar
  4. 4.
    Zielosko, B., Moshkov, M., Chikalov, I.: Optimization of decision rules based on methods of dynamic programming. Bulletin of Nizhny Novgorod State University (to appear) (in Russian)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Igor Chikalov
    • 1
  • Mikhail Moshkov
    • 1
  • Beata Zielosko
    • 1
  1. 1.Mathematical and Computer Sciences & Engineering DivisionKing Abdullah University of Science and TechnologyThuwalSaudi Arabia

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