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Interval-valued fuzzy decision trees with optimal neighbourhood perimeter

Lertworaprachaya, Youdthachai; Yang, Yingjie; John, Robert

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Authors

Youdthachai Lertworaprachaya

Yingjie Yang

Robert John



Abstract

This research proposes a new model for constructing decision trees using interval-valued fuzzy membership values. Most existing fuzzy decision trees do not consider the uncertainty associated with their membership values, however, precise values of fuzzy membership values are not always possible. In this paper, we represent fuzzy membership values as intervals to model uncertainty and employ the look-ahead based fuzzy decision tree induction method to construct decision trees. We also investigate the significance of different neighbourhood values and define a new parameter insensitive to specific data sets using fuzzy sets. Some examples are provided to demonstrate the effectiveness of the approach.

Citation

Lertworaprachaya, Y., Yang, Y., & John, R. (2014). Interval-valued fuzzy decision trees with optimal neighbourhood perimeter. Applied Soft Computing, 24, https://doi.org/10.1016/j.asoc.2014.08.060

Journal Article Type Article
Acceptance Date Aug 14, 2014
Online Publication Date Sep 4, 2014
Publication Date Nov 1, 2014
Deposit Date Sep 27, 2014
Publicly Available Date Mar 29, 2024
Journal Applied Soft Computing
Print ISSN 1568-4946
Electronic ISSN 1872-9681
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 24
DOI https://doi.org/10.1016/j.asoc.2014.08.060
Keywords Look-ahead based fuzzy decision tree induction; Optimal perimeter; Interval-valued fuzzy decision trees
Public URL https://nottingham-repository.worktribe.com/output/993960
Publisher URL http://www.sciencedirect.com/science/article/pii/S1568494614004256

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