Optimization of SVM Multiclass by Particle Swarm (PSO-SVM)

Optimization of SVM Multiclass by Particle Swarm (PSO-SVM)

Автор: Fatima Ardjani, Kaddour Sadouni

Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs

Статья в выпуске: 2 vol.2, 2010 года.

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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 the method PSO (Particle Swarm Optimization) which makes it possible to optimize the performance of classifier SVM (Separating with Vast Margin). The experiments are carried out on corpus TIMIT. The results obtained show that approach PSO-SVM gives a better classification in terms of accuracy even though the execution time is increased.

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SVM multiclass, PSO, TIMIT, evolutionary method, optimization

Короткий адрес: https://sciup.org/15010056

IDR: 15010056

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