A multiobjective genetic algorithm for feature selection and granularity learning in fuzzy-rule based classification systems
Óscar Cordón, Francisco Herrera, María José del Jesús, Pedro Villar · 2002
We propose a new method to automatically learn the knowledge base of a fuzzy rule-based classification system (FRBCS) by selecting an adequate set of features and by finding an appropiate granularity for them. This process uses a multiobjective genetic algorithm and considers a simple generation method to derive the fuzzy classification rules.