Parameter determination of support vector machine using scatter search approach
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...
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| creator | Afif, M. H. Hedar, A-R Hamid, T. H. A. Mahdy, Y. B. |
| description | 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. |
| doi_str_mv | 10.1109/ICCTA.2012.6523566 |
| format | Conference Proceeding |
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B.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Afif, M. H.</au><au>Hedar, A-R</au><au>Hamid, T. H. A.</au><au>Mahdy, Y. B.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Parameter determination of support vector machine using scatter search approach</atitle><btitle>2012 22nd International Conference on Computer Theory and Applications (ICCTA)</btitle><stitle>ICCTA</stitle><date>2012-10</date><risdate>2012</risdate><spage>181</spage><epage>186</epage><pages>181-186</pages><isbn>1467328235</isbn><isbn>9781467328234</isbn><eisbn>1467328243</eisbn><eisbn>9781467328227</eisbn><eisbn>9781467328241</eisbn><eisbn>1467328227</eisbn><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. 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| title | Parameter determination of support vector machine using scatter search approach |
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