Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Multiclassifier Systems: Back to the Future
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
"Fuzzy" versus "nonfuzzy" in combining classifiers designed by Boosting
IEEE Transactions on Fuzzy Systems
Induction of fuzzy-rule-based classifiers with evolutionary boosting algorithms
IEEE Transactions on Fuzzy Systems
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A new multiclassifier algorithm, called FuzzyBoost, is proposed. FuzzyBoost provides nonlinear composition model construction and is based on the well-known AdaBoost algorithm, but with additional steps for estimation of fuzzy densities of weak classifiers and calculation of the fuzzy integral instead of the AdaBoost linear aggregation rule at each step of boosting. Experimental studies demonstrated that Fuzzy-Boost has better generalization ability than AdaBoost in the cases of small-size training sets and small-size feature space with correlated features.