Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
Publication Type
Conference Proceeding Article
Publication Date
1-2000
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.
Discipline
Health Information Technology | Theory and Algorithms
Publication
Proceedings of American Medical Informatics Association Annual Fall Symposium (AMIA)
First Page
759
Last Page
763
City or Country
Los Angeles, CA, USA
Citation
Sarkar M. and Tze-Yun LEONG.
Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.. (2000). Proceedings of American Medical Informatics Association Annual Fall Symposium (AMIA). 759-763.
Available at: https://ink.library.smu.edu.sg/sis_research/2991