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Extraction of Prototype-Based Threshold Rules Using Neural Training Procedure

  • Marcin Blachnik
  • Mirosław Kordos
  • Włodzisław Duch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7553)

Abstract

Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule.

Keywords

Data understanding rule extraction prototype-based rules 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marcin Blachnik
    • 1
  • Mirosław Kordos
    • 2
  • Włodzisław Duch
    • 3
    • 4
  1. 1.Department of Management and InformaticsSilesian University of TechnologyKatowicePoland
  2. 2.Department of Mathematics and Computer ScienceUniversity of Bielsko-BialaBielsko-BiałaPoland
  3. 3.Department of InformaticsNicolaus Copernicus UniversityToruńPoland
  4. 4.School of Computer ScienceNanyang Technological UniversitySingapore

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