Effective classifier pruning with rule information

  • Authors:

  • Xiaolong Zhang;Mingjian Luo;Daoying Pi

  • Affiliations:

  • School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, P.R. China;School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, P.R. China;Dept. of Control Science and Engineering, Zhejiang University, Hangzhou, P.R. China

  • Venue:
  • DS'05 Proceedings of the 8th international conference on Discovery Science
  • Year:
  • 2005

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Abstract

This paper presents an algorithm to prune a tree classifier with a set of rules which are converted from a C4.5 classifier, where rule information is used as a pruning criterion. Rule information measures the goodness of a rule when discriminating labeled instances. Empirical results demonstrate that the proposed pruning algorithm has high predictive accuracy.