Scientific Track

Advanced Topics in Artificial Intelligence

Volume 1502 of the series Lecture Notes in Computer Science pp 273-283


The problem of missing values in decision tree grafting

  • Geoffrey I. WebbAffiliated withSchool of Computing and Mathematics, Deakin University

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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