Combining Evolutionary and Fuzzy Techniques in Medical Diagnosis
Carlos Andrés Peña-Reyes, Moshe Sipper · Studies in fuzziness and soft computing · 2002
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. 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.