Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Ho, K.M. | Scott, P.D.
Affiliations: Department of Computer Science, University of Essex, Colchester, CO4 3SQ, UK. E-mail: hokokx@essex.ac.uk, scotp@essex.ac.uk
Abstract: The trees constructed by decision tree induction programs are often unnecessarily large and containing substantial degrees of duplication because such programs typically build a separate subtree for each value of a categorical attribute. Attribute value grouping procedures attempt to avoid this problem by partitioning attribute values into groups, each of which gives rise to only one subtree. In this paper we raise and attempt to answer a number of questions about the performance of such procedures. We review the limited amount of research that has been done in this area and propose a number of novel attribute value grouping procedures. We then present the results of a systematic comparative study in which eight alternative attribute grouping procedures were evaluated using both artificial and real data sets. We found that attribute value grouping can produce substantial reductions in tree size and that the best methods produce average reductions approaching 50% found that there was no effect on the classification accuracy of the trees produced but the time required to produce them was reduced. The most surprising finding was that global methods, which group attribute values once prior to tree construction were superior to local methods, which repartition values throughout tree construction: they produce substantially smaller trees in less time that are marginally more accurate classifiers.
Keywords: attribute value grouping, decision tree induction
DOI: 10.3233/IDA-2000-43-407
Journal: Intelligent Data Analysis, vol. 4, no. 3-4, pp. 255-274, 2000
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl