FUZZY CLUSTERING WITH AMBIGUITY FOR MULTI-CLASSIFIERS FUSION : CLUSTERING-CLASSIFICATION COOPERATION
Résumé
The main aim of this paper is to demonstrate the performance of multi-classifiers fusion based on fuzzy clustering with ambiguity. The problem is seen from the multi-decision point of view (i.e. several classification modules). Each classification module is specialized on a particular region of the features space. These regions are obtained by fuzzy clustering and constitute the original data set by union.
Origine : Fichiers produits par l'(les) auteur(s)
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