Title :
ClaDia: a fuzzy classifier system for disease diagnosis
Author :
Walter, David ; Mohan, Chilukuri K.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY, USA
Abstract :
The paper describes ClaDia, a learning classifier system applied to the Wisconsin breast cancer data set, using a fuzzy representation of the rules, a median based fuzzy combination rule, and separate subpopulations for each class. The system achieves a classification rate of over 90%, for many sets of system parameter values
Keywords :
cancer; diagnostic expert systems; evolutionary computation; fuzzy set theory; learning (artificial intelligence); medical diagnostic computing; medical expert systems; pattern classification; ClaDia; Wisconsin breast cancer data set; classification rate; disease diagnosis; fuzzy classifier system; fuzzy representation; learning classifier system; median based fuzzy combination rule; subpopulations; system parameter values; Breast cancer; Computer science; Diseases; Evolutionary computation; Expert systems; Fuzzy sets; Fuzzy systems; Humans; Machine learning; System testing;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870821
