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Induction of fuzzy-rule-based classifiers with evolutionary boosting algorithms

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4 Author(s)
del Jesus, M.J. ; Comput. Sci. Dept., Jaen Univ., Spain ; Hoffmann, F. ; Navascues, L.J. ; Sanchez, L.

This paper proposes a novel Adaboost algorithm to learn fuzzy-rule-based classifiers. Connections between iterative learning and boosting are analyzed in terms of their respective structures and the manner these algorithms address the cooperation-competition problem. The results are used to explain some properties of the former method. The evolutionary boosting scheme is applied to approximate and descriptive fuzzy-rule bases. The advantages of boosting fuzzy rules are assessed by performance comparisons between the proposed method and other classification schemes applied on a set of benchmark classification tasks.

Published in:

Fuzzy Systems, IEEE Transactions on  (Volume:12 ,  Issue: 3 )

Date of Publication:

June 2004

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