Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39076
Title: Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
Authors: Sarkar, M. 
Leong, T.Y. 
Issue Date: 2000
Source: Sarkar, 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.
Abstract: This 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.
Source Title: Proceedings / AMIA . Annual Symposium. AMIA Symposium
URI: http://scholarbank.nus.edu.sg/handle/10635/39076
ISSN: 1531605X
Appears in Collections:Staff Publications

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