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Multiple Classification Ripple Round Rules: A Preliminary Study

  • Ivan Bindoff
  • Tristan Ling
  • Byeong Ho Kang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5465)

Abstract

This paper details a set of enhancements to the Multiple Classification Ripple Down Rules methodology which enable the expert to create rules based on the existing presence of a conclusion. A detailed description of the method and associated challenges are included as well as the results of a preliminary study which was undertaken with a dataset of pizza topping preferences. These results demonstrate that the method loses none of the appeal or capabilities of MCRDR and show that the enhancements can see practical and useful application even in this simple domain.

Keywords

Expert System Knowledge Acquisition Rule Condition Multiple Classification Result List 
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 2009

Authors and Affiliations

  • Ivan Bindoff
    • 1
  • Tristan Ling
    • 1
  • Byeong Ho Kang
    • 1
  1. 1.School of ComputingUniversity of TasmaniaAustralia

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