title: |
A Fuzzy Rule Mining Approach involving Absent Items |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| volume-issue: | 1 - 1 | |
| pages: | 275 - 282 | |
ISBN: |
978-90-78677-00-0 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/eusflat.2011.126 (how to use a DOI) | |
author(s): |
Miguel Delgado, Maria Dolores Ruiz, Daniel Sanchez, José Maria Serrano |
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publication date: |
July 2011 |
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keywords: |
Data mining, Fuzzy association rules,
absence of items, negative rules. |
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abstract: |
In this paper we present how to extract fuzzy association rules involving both the presence and the
absence of items using a fuzzy rule mining procedure introduced by the authors in previous works.
The rule mining procedure is based on the GUHA
logical model, fuzzified via a recently proposed representation of gradualness. We present some results
obtained with real datasets. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |