A Fuzzy Algorithm for the Efficient Utilization of Information in Decision Trees

Keeley A. Crockett and Zuhair Bandar, The Manchester Metropolitan University, UK; Akeel Al-Attar, Attar Software Limited, UK

Highly optimized decision trees which have been created from ID3-type algorithms are often recognized as being one of the best methods for partitioning a given domain in terms of both classification accuracy and for the formulation of small rule sets. However, these trees are highly optimized and potential information in lower branches of the tree is lost through pruning. This paper presents a novel algorithm that regains this information by relazing sharp decition boundaries and by regrowing the decision tree by relaxing the pruning criteria.

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.