Please use this identifier to cite or link to this item:
|Title:||Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.|
|Authors:||Sarkar, M. |
|Citation:||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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 29, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.