Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24773
Title: A fuzzy matching method of fuzzy decision trees
Authors: Lee, JWT
Sun, J
Yang, LZ
Keywords: Classification
Decision trees
Fuzzy set theory
Issue Date: 2003
Publisher: IEEE
Source: 2003 International Conference on Machine Learning and Cybernetics, 2-5 November 2003, v. 3, p. 1569-1573 How to cite?
Abstract: In this paper, we present a matching method that can improve the classification performance of a fuzzy decision tree (FDT). This method takes into consideration prediction strength of leave nodes of a fuzzy decision tree by combining true degrees (CF) of fuzzy rules, generated from a fuzzy decision tree, with membership degrees of antecedent parts of rules when applied to cases for classification. We illustrate the importance of CF through an example. An experiment shows by using this method, we can obtain more accurate results of classification when compared to the original method and to those obtained using the C5.0 decision tree.
URI: http://hdl.handle.net/10397/24773
ISBN: 0-7803-8131-9
DOI: 10.1109/ICMLC.2003.1259745
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

35
Last Week
2
Last month
Checked on Aug 14, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.