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Proceedings of the AMIA Symposium logoLink to Proceedings of the AMIA Symposium
. 2000:759–763.

Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.

M Sarkar 1, T Y Leong 1
PMCID: PMC2243774  PMID: 11079986

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.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Pena-Reyes C. A., Sipper M. A fuzzy-genetic approach to breast cancer diagnosis. Artif Intell Med. 1999 Oct;17(2):131–155. doi: 10.1016/s0933-3657(99)00019-6. [DOI] [PubMed] [Google Scholar]

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