Capturing Uncertainty in Associative Classification Model
This paper aims to propose a weighted linguistic associative classification model for uncertainty data analysis using rough membership function. Transformation of quantitative association rules into linguistic representation can be achieved in discretizing the numerical interval into rough interval...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/144/ http://eprints.utem.edu.my/id/eprint/144/1/CapturingUncertaintyInWeightedACModel_DMO09_CYH.pdf |
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| author | Choo, Yun Huoy Abu Bakar, Azuraliza Draman @ Muda, Azah Kamilah |
| author_facet | Choo, Yun Huoy Abu Bakar, Azuraliza Draman @ Muda, Azah Kamilah |
| author_sort | Choo, Yun Huoy |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | This paper aims to propose a weighted linguistic associative classification model for uncertainty data analysis using rough membership function. Transformation of quantitative association rules into linguistic representation can be achieved in discretizing the numerical interval into rough interval described with respective rough membership values. Transformation of linguistic information system is suggested prior to the frequent pattern discovery. Neither pruning of association rules nor classifier modelling is needed. The rough membership values of the each linguistic frequent item are composited to form the weighted associative classification rule. Simulated results on Iris Plant dataset were shown in the paper. The future work of the research will focus on implementing the model with more experimental dataset. |
| first_indexed | 2025-11-15T19:45:41Z |
| format | Conference or Workshop Item |
| id | utem-144 |
| institution | Universiti Teknikal Malaysia Melaka |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:45:41Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utem-1442023-05-23T16:30:23Z http://eprints.utem.edu.my/id/eprint/144/ Capturing Uncertainty in Associative Classification Model Choo, Yun Huoy Abu Bakar, Azuraliza Draman @ Muda, Azah Kamilah Q Science (General) T Technology (General) AS Academies and learned societies (General) This paper aims to propose a weighted linguistic associative classification model for uncertainty data analysis using rough membership function. Transformation of quantitative association rules into linguistic representation can be achieved in discretizing the numerical interval into rough interval described with respective rough membership values. Transformation of linguistic information system is suggested prior to the frequent pattern discovery. Neither pruning of association rules nor classifier modelling is needed. The rough membership values of the each linguistic frequent item are composited to form the weighted associative classification rule. Simulated results on Iris Plant dataset were shown in the paper. The future work of the research will focus on implementing the model with more experimental dataset. 2009 Conference or Workshop Item PeerReviewed text en http://eprints.utem.edu.my/id/eprint/144/1/CapturingUncertaintyInWeightedACModel_DMO09_CYH.pdf Choo, Yun Huoy and Abu Bakar, Azuraliza and Draman @ Muda, Azah Kamilah (2009) Capturing Uncertainty in Associative Classification Model. In: 2nd Conference on Data Mining and Optimization, 27-28 October 2009, Selangor, Malaysia. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5341904 |
| spellingShingle | Q Science (General) T Technology (General) AS Academies and learned societies (General) Choo, Yun Huoy Abu Bakar, Azuraliza Draman @ Muda, Azah Kamilah Capturing Uncertainty in Associative Classification Model |
| title | Capturing Uncertainty in Associative Classification Model |
| title_full | Capturing Uncertainty in Associative Classification Model |
| title_fullStr | Capturing Uncertainty in Associative Classification Model |
| title_full_unstemmed | Capturing Uncertainty in Associative Classification Model |
| title_short | Capturing Uncertainty in Associative Classification Model |
| title_sort | capturing uncertainty in associative classification model |
| topic | Q Science (General) T Technology (General) AS Academies and learned societies (General) |
| url | http://eprints.utem.edu.my/id/eprint/144/ http://eprints.utem.edu.my/id/eprint/144/ http://eprints.utem.edu.my/id/eprint/144/1/CapturingUncertaintyInWeightedACModel_DMO09_CYH.pdf |