Nonparametric techniques to extract fuzzy rules for breast cancer diagnosis problem

• Main Authors: SARKAR, Manish, Tze-Yun LEONG
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2001
• Subjects: Clustering; Breast cancer; classification; diagnosis; fuzzy set; nearest neighbors algorithm; rough set; rule base; Wisconsin-Madison data; Health Information Technology; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/3029; https://ink.library.smu.edu.sg/context/sis_research/article/4029/viewcontent/SHTI84_1394.pdf
• Institution: Singapore Management University

This paper addresses breast cancer diagnosis problem as a pattern classification problem. Specifically, the problem is studied using Wisconsin-Madison breast cancer data set. Fuzzy rules are generated from the input-output relationship so that the diagnosis becomes easier and transparent for both pa...