Kaddour Sadouni

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In many problems of classification, the performances of a classifier are often evaluated by a factor (rate of error).the factor is not well adapted for the complex real problems, in particular the problems multiclass. Our contribution consists in adapting an evolutionary method for optimization of this factor. Among the methods of optimization used we chose(More)
In this paper we introduce and investigate the performance of a simple framework for multiclass problems of support vector machine (SVM), we present a new architecture named EBTSVM (Efficient Binary Tree Multiclass SVM), in order to achieve high classification efficiency for multiclass problems. The proposed paradigm builds a binary tree for multiclass SVM(More)
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