Combining Evolutionary and Fuzzy Techniques in Medical Diagnosis

  • C. A. Peña-Reyes
  • M. Sipper
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 96)


In this chapter we focus on the Wisconsin breast cancer diagnosis (WBCD) problem, combining two methodologies—fuzzy systems and evolutionary algorithms—to automatically produce diagnostic systems. We present two hybrid approaches: (1) a fuzzy-genetic algorithm, and (2) Fuzzy CoCo, a novel cooperative coevolutionary approach to fuzzy modeling. Both methods produce systems exhibiting high classification performance, and which are also human-interpretable. Fuzzy CoCo obtains higher-performance systems than the standard fuzzy-genetic approach while using less computational effort.


Membership Function Evolutionary Algorithm Fuzzy System Fuzzy Rule Fuzzy Modeling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • C. A. Peña-Reyes
  • M. Sipper

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