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 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.
Sarkar
M
M
Medical Computing Laboratory, Department of Computer Science, School of Computing, National University of Singapore, Lower Kent Ridge Road, Singapore: 119260. manish@comp.nus.edu.sg
Leong
T Y
TY
D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000175:diagnosis*; D006801:Humans