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Interval-valued fuzzy decision trees with optimal neighbourhood perimeter

Lertworaprachaya, Youdthachai; Yang, Yingjie; John, Robert

Authors

Youdthachai Lertworaprachaya youd@dmu.ac.uk

Yingjie Yang yyang@dmu.ac.uk

Robert John robert.john@nottingham.ac.uk



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.

Journal Article Type Article
Publication Date Nov 1, 2014
Journal Applied Soft Computing
Print ISSN 1568-4946
Electronic ISSN 1872-9681
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 24
APA6 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
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
Publisher URL http://www.sciencedirect.com/science/article/pii/S1568494614004256
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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