Title :
A multiobjective genetic algorithm for feature selection and granularity learning in fuzzy-rule based classification systems
Author :
Cordón, O. ; Herrera, F. ; del Jesus, M.J. ; Villar, P.
Author_Institution :
Dept. Comput. Sci. & A.I., Granada Univ., Spain
Abstract :
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
Keywords :
fuzzy logic; genetic algorithms; knowledge acquisition; knowledge based systems; learning (artificial intelligence); feature selection; fuzzy classification rules; fuzzy rule based classification system; granularity learning; knowledge base; knowledge representation; multiobjective genetic algorithm; rule generation; Computer science; Diversity reception; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Input variables; Knowledge based systems; Neural networks; System performance;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.943727
