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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Performance Evaluation of Fuzzy Rule-Based Systems

With Class Priority For Medical Diagnosis Problems

Authors:

Tomoharu Nakashima, Yasuyuki Yokota, Gerald Schaefer,

Hisao Ishibuchi

Published in:

 

ECMS 2007 Proceedings

Edited by: Ivan Zelinka, Zuzana Oplatkova, Alessandra Orsoni

 

ISBN: 978-0-9553018-2-7

Doi: 10.7148/2007

 

21st European Conference on Modelling and Simulation,

Prague, June 4-6, 2007

 

Citation format:

Nakashima, T., Yokota, Y., Schaefer, G., & Ishibuchi, H. (2007). Performance Evaluation of Fuzzy Rule-Based Systems With Class Priority For Medical Diagnosis Problems. ECMS 2007 Proceedings edited by: I. Zelinka, Z. Oplatkova, A. Orsoni (pp. 283-288). European Council for Modeling and Simulation. doi:10.7148/2007-0283.

DOI:

http://dx.doi.org/10.7148/2007-0283

Abstract:

In this paper we examine the performance of fuzzy rule-based systems with classification priority for medical diagnosis problems. The assumption in this pa- per is that a classification priority is given a priori for each class in a pattern classification problem. Our fuzzy rule- based system consists of a set of fuzzy if-then rules that are automatically generated from a set of given training pat- terns. The consequent class of fuzzy if-then rules are de- cided based on the number of covered training patterns for each class. We apply the fuzzy classifier with class prior- ity to two medical diagnosis problems: appendix diagnosis and breast cancer diagnosis, and compare its performance with that of a conventional fuzzy rule-based systems.

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