The Problem of Missing Values in Decision Tree Grafting

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 de ciency 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 e cacy of this solution.

• Type: Conference
• Year: 1998
• Where: AUSAI
• Authors: Geoffrey I. Webb
• Keywords: Artificial Intelligence, AUSAI 1998, Decision Tree, Grafting, Grafting Systems