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Neuro-fuzzy Rough Classifier Ensemble

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

Abstract

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.

Keywords

Neuro-fuzzy rough sets classifier ensemble 

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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

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