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Evolutionary Approaches to Rule Extraction from Neural Networks

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Book cover Engineering Evolutionary Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 82))

Summary

A short survey of existing methods of rule extraction from neural networks starts the chapter. Because searching rules is similar to NP-hard problem it justifies an application of evolutionary algorithm to the rule extraction. The survey contains a short description of evolutionary based methods, as well. It creates a background to show own experiences from satisfying applications of evolutionary algorithms to this process. Two methods of rule extraction namely: REX and GEX are presented in details. They represent a global approach to rule extraction, perceiving a neural network by the set of pairs: input pattern and response produced by the neural network. REX uses prepositional fuzzy rules and is composed of two methods REX Michigan and REX Pitt. GEX takes an advantage of classical crisp rules. All details of these methods are described in the chapter. Their efficiency was tested in experimental studies using different benchmark data sets from UCI repository. The comparison to other existing methods was made and is presented in the chapter.

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Author information

Authors and Affiliations

  1. Institute of Applied Informatics, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Urszula Markowska-Kaczmar

Authors
  1. Urszula Markowska-Kaczmar
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Editor information

Editors and Affiliations

  1. Centre for Quantifiable Quality of Service in Communication Systems (Q2S), Centre of Excellence Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491, Trondheim, Norway

    Ajith Abraham

  2. Department of Computer Science Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Kogalniceanu 1, 400084, Cluj - Napoca, Romania

    Crina Grosan

  3. Department of Electrical & Computer Engineering, University of Alberta, ECERF Bldg., 2nd floor, Edmonton, AB, T6G 2V4, Canada

    Witold Pedrycz

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© 2008 Springer-Verlag Berlin Heidelberg

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Markowska-Kaczmar, U. (2008). Evolutionary Approaches to Rule Extraction from Neural Networks. In: Abraham, A., Grosan, C., Pedrycz, W. (eds) Engineering Evolutionary Intelligent Systems. Studies in Computational Intelligence, vol 82. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75396-4_7

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  • DOI: https://doi.org/10.1007/978-3-540-75396-4_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75395-7

  • Online ISBN: 978-3-540-75396-4

  • eBook Packages: EngineeringEngineering (R0)

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