Generating concise and accurate classification rules for breast cancer diagnosis
10.1016/S0933-3657(99)00041-X
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sg-nus-scholar.10635-423712023-10-25T20:58:47Z Generating concise and accurate classification rules for breast cancer diagnosis Setiono, R. INFORMATION SYSTEMS Attribute selection Data pre-processing Neural network rule extraction Wisconsin breast cancer diagnosis 10.1016/S0933-3657(99)00041-X Artificial Intelligence in Medicine 18 3 205-219 AIMEE 2013-07-11T10:07:33Z 2013-07-11T10:07:33Z 2000 Article Setiono, R. (2000). Generating concise and accurate classification rules for breast cancer diagnosis. Artificial Intelligence in Medicine 18 (3) : 205-219. ScholarBank@NUS Repository. https://doi.org/10.1016/S0933-3657(99)00041-X 09333657 http://scholarbank.nus.edu.sg/handle/10635/42371 000085369700002 Scopus |
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Attribute selection Data pre-processing Neural network rule extraction Wisconsin breast cancer diagnosis |
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Attribute selection Data pre-processing Neural network rule extraction Wisconsin breast cancer diagnosis Setiono, R. Generating concise and accurate classification rules for breast cancer diagnosis |
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10.1016/S0933-3657(99)00041-X |
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INFORMATION SYSTEMS |
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INFORMATION SYSTEMS Setiono, R. |
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Article |
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Setiono, R. |
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Setiono, R. |
title |
Generating concise and accurate classification rules for breast cancer diagnosis |
title_short |
Generating concise and accurate classification rules for breast cancer diagnosis |
title_full |
Generating concise and accurate classification rules for breast cancer diagnosis |
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Generating concise and accurate classification rules for breast cancer diagnosis |
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Generating concise and accurate classification rules for breast cancer diagnosis |
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generating concise and accurate classification rules for breast cancer diagnosis |
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2013 |
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http://scholarbank.nus.edu.sg/handle/10635/42371 |
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