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dc.titleApplication of K-nearest neighbors algorithm on breast cancer diagnosis problem.
dc.contributor.authorSarkar, M.
dc.contributor.authorLeong, T.Y.
dc.identifier.citationSarkar, M.,Leong, T.Y. (2000). Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.. Proceedings / AMIA . Annual Symposium. AMIA Symposium : 759-763. ScholarBank@NUS Repository.
dc.description.abstractThis paper addresses the Breast Cancer diagnosis problem as a pattern classification problem. Specifically, this problem is studied using the Wisconsin-Madison Breast Cancer data set. The K-nearest neighbors algorithm is employed as the classifier. Conceptually and implementation-wise, the K-nearest neighbors algorithm is simpler than the other techniques that have been applied to this problem. In addition, the Knearest neighbors algorithm produces the overall classification result 1.17% better than the best result known for this problem.
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings / AMIA . Annual Symposium. AMIA Symposium
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