Associative classification framework for cancer microarray data
Having good cancer classifiers are crucial in order to give the most effective and cost saving treatments for patients. Microarray is one of the vital tools in cancer studies, as it allows the discovery of gene expression patterns and promises better accuracy of cancer classification. This paper pre...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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American Scientific Publishers
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/46531/ http://psasir.upm.edu.my/id/eprint/46531/1/Associative%20classification%20framework%20for%20cancer%20microarray%20data.pdf |
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| author | Fang, Ong Huey Mustapha, Norwati Mustapha, Aida Hamdan, Hazlina Rosli, Rozita |
| author_facet | Fang, Ong Huey Mustapha, Norwati Mustapha, Aida Hamdan, Hazlina Rosli, Rozita |
| author_sort | Fang, Ong Huey |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Having good cancer classifiers are crucial in order to give the most effective and cost saving treatments for patients. Microarray is one of the vital tools in cancer studies, as it allows the discovery of gene expression patterns and promises better accuracy of cancer classification. This paper presents an associative classification framework for microarray data. The proposed framework combined the strength of both filter method and association rule mining. The experimental results showed that the selected gene subsets from generated association rules can improve the accuracy and interpretability of classifiers. |
| first_indexed | 2025-11-15T10:10:08Z |
| format | Article |
| id | upm-46531 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:10:08Z |
| publishDate | 2017 |
| publisher | American Scientific Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-465312019-05-09T04:41:16Z http://psasir.upm.edu.my/id/eprint/46531/ Associative classification framework for cancer microarray data Fang, Ong Huey Mustapha, Norwati Mustapha, Aida Hamdan, Hazlina Rosli, Rozita Having good cancer classifiers are crucial in order to give the most effective and cost saving treatments for patients. Microarray is one of the vital tools in cancer studies, as it allows the discovery of gene expression patterns and promises better accuracy of cancer classification. This paper presents an associative classification framework for microarray data. The proposed framework combined the strength of both filter method and association rule mining. The experimental results showed that the selected gene subsets from generated association rules can improve the accuracy and interpretability of classifiers. American Scientific Publishers 2017-05 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/46531/1/Associative%20classification%20framework%20for%20cancer%20microarray%20data.pdf Fang, Ong Huey and Mustapha, Norwati and Mustapha, Aida and Hamdan, Hazlina and Rosli, Rozita (2017) Associative classification framework for cancer microarray data. Advanced Science Letters, 23 (5). pp. 4153-4157. ISSN 1936-6612; ESSN: 1936-7317 https://www.ingentaconnect.com/content/asp/asl/2017/00000023/00000005/art00074 10.1166/asl.2017.8312 |
| spellingShingle | Fang, Ong Huey Mustapha, Norwati Mustapha, Aida Hamdan, Hazlina Rosli, Rozita Associative classification framework for cancer microarray data |
| title | Associative classification framework for cancer microarray data |
| title_full | Associative classification framework for cancer microarray data |
| title_fullStr | Associative classification framework for cancer microarray data |
| title_full_unstemmed | Associative classification framework for cancer microarray data |
| title_short | Associative classification framework for cancer microarray data |
| title_sort | associative classification framework for cancer microarray data |
| url | http://psasir.upm.edu.my/id/eprint/46531/ http://psasir.upm.edu.my/id/eprint/46531/ http://psasir.upm.edu.my/id/eprint/46531/ http://psasir.upm.edu.my/id/eprint/46531/1/Associative%20classification%20framework%20for%20cancer%20microarray%20data.pdf |