Multiple Classification Ripple Round Rules: A Preliminary Study

Authors:
Ivan Bindoff;Tristan Ling;Byeong Ho Kang
Affiliations:
School of Computing, University of Tasmania,;School of Computing, University of Tasmania,;School of Computing, University of Tasmania,
Venue:
Knowledge Acquisition: Approaches, Algorithms and Applications
Year:
2009

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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.