A multiobjective genetic algorithm for feature selection and granularity learning in fuzzy-rule based classification systems

O. Cordon, F. Herrera, M.J. del Jesus, P. Villar
Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)  
In this contribution, 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. 0-7803-7@78-3/0U$l0~00 (C)u#)l WE.
doi:10.1109/nafips.2001.943727 fatcat:squwgjiidjentgsapjgadeekym