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

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...

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Main Authors:	Sarkar M., Tze-Yun LEONG
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2000
Subjects:	Health Information Technology Theory and Algorithms
Online Access:	https://ink.library.smu.edu.sg/sis_research/2991
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Institution:	Singapore Management University
Language:	English

id	sg-smu-ink.sis_research-3991
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spelling	sg-smu-ink.sis_research-39912016-02-05T06:30:05Z Application of K-nearest neighbors algorithm on breast cancer diagnosis problem. Sarkar M., Tze-Yun LEONG, 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. 2000-01-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/2991 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Health Information Technology Theory and Algorithms
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Health Information Technology Theory and Algorithms
spellingShingle	Health Information Technology Theory and Algorithms Sarkar M., Tze-Yun LEONG, Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
description	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.
format	text
author	Sarkar M., Tze-Yun LEONG,
author_facet	Sarkar M., Tze-Yun LEONG,
author_sort	Sarkar M.,
title	Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
title_short	Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
title_full	Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
title_fullStr	Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
title_full_unstemmed	Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
title_sort	application of k-nearest neighbors algorithm on breast cancer diagnosis problem.
publisher	Institutional Knowledge at Singapore Management University
publishDate	2000
url	https://ink.library.smu.edu.sg/sis_research/2991
_version_	1770572771806412800

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

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