Interval-valued fuzzy decision trees with optimal neighbourhood perimeter
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...
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| Format: | Article |
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Elsevier
2014
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| Online Access: | https://eprints.nottingham.ac.uk/3364/ |
| _version_ | 1848791023881289728 |
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| author | Lertworaprachaya, Youdthachai Yang, Yingjie John, Robert |
| author_facet | Lertworaprachaya, Youdthachai Yang, Yingjie John, Robert |
| author_sort | Lertworaprachaya, Youdthachai |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T18:21:55Z |
| format | Article |
| id | nottingham-3364 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:21:55Z |
| publishDate | 2014 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-33642020-05-04T20:12:53Z https://eprints.nottingham.ac.uk/3364/ Interval-valued fuzzy decision trees with optimal neighbourhood perimeter Lertworaprachaya, Youdthachai Yang, Yingjie John, Robert 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. Elsevier 2014-11 Article PeerReviewed Lertworaprachaya, Youdthachai, Yang, Yingjie and John, Robert (2014) Interval-valued fuzzy decision trees with optimal neighbourhood perimeter. Applied Soft Computing, 24 . pp. 851-866. ISSN 1872-9681 Look-ahead based fuzzy decision tree induction; Optimal perimeter; Interval-valued fuzzy decision trees http://www.sciencedirect.com/science/article/pii/S1568494614004256 doi:10.1016/j.asoc.2014.08.060 doi:10.1016/j.asoc.2014.08.060 |
| spellingShingle | Look-ahead based fuzzy decision tree induction; Optimal perimeter; Interval-valued fuzzy decision trees Lertworaprachaya, Youdthachai Yang, Yingjie John, Robert Interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| title | Interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| title_full | Interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| title_fullStr | Interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| title_full_unstemmed | Interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| title_short | Interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| title_sort | interval-valued fuzzy decision trees with optimal neighbourhood perimeter |
| topic | Look-ahead based fuzzy decision tree induction; Optimal perimeter; Interval-valued fuzzy decision trees |
| url | https://eprints.nottingham.ac.uk/3364/ https://eprints.nottingham.ac.uk/3364/ https://eprints.nottingham.ac.uk/3364/ |