Title: Parameter determination of support vector machine using scatter search approach
Abstract:Support Vector Machine (SVM) is a popular data classification method with many diverse applications. SVM has many parameters, which have significant influences on the performance of SVM classifier. In...Support Vector Machine (SVM) is a popular data classification method with many diverse applications. SVM has many parameters, which have significant influences on the performance of SVM classifier. In this paper, a Scatter Search approach is used to find near optimal values of the SVM parameters and its kernel parameters. The proposed method integrates a scatter search approach with support vector machine using three different kernel functions, shortly (3SVM). To evaluate the performance of the proposed method, 4 benchmark datasets are used. Experiments and comparisons prove that the 3SVM is a promising approach and has a competitive performance relative to some other published methods.Read More
Publication Year: 2012
Publication Date: 2012-10-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 1
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