title: Application of K-nearest neighbors algorithm on breast cancer diagnosis problem.
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.
authors.affiliation: 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
authors.forename: M
authors.initials: M
authors.lastname: Sarkar
authors.forename: T Y
authors.initials: TY
authors.lastname: Leong
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000175:diagnosis*; D006801:Humans