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

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4 Author(s)
Cordon, O. ; Dept. Comput. Sci. & A.I., Granada Univ., Spain ; Herrera, F. ; del Jesus, M.J. ; Villar, P.

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

Published in:

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th  (Volume:3 )

Date of Conference:

25-28 July 2001