The problem of missing values in decision tree grafting

  • Geoffrey I. Webb
Scientific Track
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1502)


Decision tree grafting adds nodes to inferred decision trees. Previous research has demonstrated that appropriate grafting techniques can improve predictive accuracy across a wide cross-selection of domains. However, previous decision tree grafting systems are demonstrated to have a serious deficiency for some data sets containing missing values. This problem arises due to the method for handling missing values employed by C4.5, in which the grafting systems have been embedded. This paper provides an explanation of and solution to the problem. Experimental evidence is presented of the efficacy of this solution.

Key words

Grafting Decision Tree Learning Missing Values 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Geoffrey I. Webb
    • 1
  1. 1.School of Computing and MathematicsDeakin UniversityGeelongAustrlia

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