Rule extraction from neural network by genetic algorithm with Pareto optimization

Abstract

The method of rule extraction from a neural network based on the genetic approach with Pareto optimization is presented in the paper. The idea of Pareto optimization is shortly described and the details of developed method such as fitness function, genetic operators and the structure of chromosome are shown. The method was tested with well known benchmark data sets. The results of these experiments are presented and discussed.