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• W2543726982 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 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." @default.
• W2543726982 created "2016-11-04" @default.
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• W2543726982 date "2012-10-01" @default.
• W2543726982 modified "2023-09-24" @default.
• W2543726982 title "Parameter determination of support vector machine using scatter search approach" @default.
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• W2543726982 doi "https://doi.org/10.1109/iccta.2012.6523566" @default.
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