An Overview of Alternative Rule Evaluation Criteria and Their Use in Separate-and-Conquer Classifiers

  • Fernando Berzal
  • Juan-Carlos Cubero
  • Nicolás Marín
  • José-Luis Polo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4203)

Abstract

Separate-and-conquer classifiers strongly depend on the criteria used to choose which rules will be included in the classification model. When association rules are employed to build such classifiers (as in ART [3]), rule evaluation can be performed attending to different criteria (other than the traditional confidence measure used in association rule mining). In this paper, we analyze the desirable properties of such alternative criteria and their effect in building rule-based classifiers using a separate-and-conquer strategy.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fernando Berzal
    • 1
  • Juan-Carlos Cubero
    • 1
  • Nicolás Marín
    • 1
  • José-Luis Polo
    • 1
  1. 1.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

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