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Prototype-Based Threshold Rules

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Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4234))

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Abstract

Understanding data is usually done extracting fuzzy or crisp logical rules using neurofuzzy systems, decision trees and other approaches. Prototype-based rules are an interesting alternative providing in many cases simpler, more accurate and more comprehensible description of the data. Algorithm for generation of threshold prototype-based rules are described and a comparison with neurofuzzy systems on a number of datasets provided. Results show that systems for data understanding generating prototypes deserve at least the same attention as that enjoyed by the neurofuzzy systems.

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Author information

Authors and Affiliations

  1. Division of Computer Methods, Department of Electrotechnology and Metallurgy, The Silesian University of Technology, Krasińskiego 8, 40-019, Katowice, Poland

    Marcin Blachnik

  2. Department of Informatics, Nicolaus Copernicus University, Grudziądzka 5, Toruń, Poland

    Włodzisław Duch

  3. School of Computer Engineering, Nanyang Technological University, Singapore

    Włodzisław Duch

Authors
  1. Marcin Blachnik
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  2. Włodzisław Duch
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, The Chinese Univ. of Hong Kong, Shatin, N.T., Hong Kong

    Irwin King

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, New Territories,, China

    Jun Wang

  3. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Lai-Wan Chan

  4. Department of Computer Science and Engineering & Center for Cognitive Science, The Ohio State University, OH 43210, Columbus

    DeLiang Wang

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© 2006 Springer-Verlag Berlin Heidelberg

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Blachnik, M., Duch, W. (2006). Prototype-Based Threshold Rules. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_113

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  • DOI: https://doi.org/10.1007/11893295_113

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46484-6

  • Online ISBN: 978-3-540-46485-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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