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

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