A study in experimental evaluation of neural network and genetic algorithm techniques for knowledge acquisition in fuzzy classification systems

This paper addresses the issue of appropriate evaluation criteria for knowledge acquisition techniques for fuzzy classification systems. It describes an empirical study in which two different systems, one based on neural networks, and the other based on genetic algorithms were developed, applied to three classification problems and evaluated. Comparison of the approaches with the C4.5 inductive algorithm was also carried out.