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Construction of Efficient Rulesets from Fuzzy Data through Simulated Annealing

  • Francisco Botana
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1904)

Abstract

This paper proposes a simulated annealing-based approach for obtaining compact efficient classification systems from fuzzy data. Different methods for generating decision rules from fuzzy data share a problem in multidimensional spaces: their high cardinality. In order to solve it, the method of simulated annealing is proposed. This approach is illustrated with two well-known learning sets.

Keywords

Simulated Annealing Fuzzy Rule Fuzzy Data Weight Lift High Membership 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Francisco Botana
    • 1
  1. 1.Departamento de Matemática AplicadaUniversidad de VigoPontevedraSpain

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