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|Title: ||A genetic algorithm-based multi-class support vector machine for Mongolian character recognition|
|???metadata.dc.creator???: ||Batsaikan, O.|
Ho, C. K.
Singh, Y. P.
|Keywords: ||Support vector machines|
Máquinas de vetores de suporte
|Publisher: ||Editora da UFLA|
|Citation: ||BATSAIKAN, O.; HO, C. K.; SINGH, Y. P. A genetic algorithm-based multi-class support vector machine for Mongolian character recognition. INFOCOMP: Journal of Computer Science, Lavras, v. 8, n. 1, p. 1-7, Mar. 2009.|
|Abstract: ||This paper proposes a hybrid genetic algorithm and support vector machine (GA-SVM) approach to address the Mongolian character recognition problem. As the character recognition problem can be considered as a multi-class classification problem, we devise a DAG-SVM classifier. DAG-SVM uses the One-Against-One technique to combine multiple binary SVM classifiers. The GA is used to select the multi-class SVM model parameters. Empirical results demonstrate that the GA-SVM approach is able to achieve good accuracy rate.|
|Other Identifiers: ||http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/244|
|Appears in Collections:||Infocomp|
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