Journal of the Korean Data and Information Science Society
- 제17권2호
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- Pages.311-324
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- 2006
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- 1598-9402(pISSN)
A Comparison Study of Multiclass SVM Methods in Microarray Data
초록
The Support Vector Machine(SVM) is very functional and efficient classification method to any other classification analysis method. However, its optimal extension to more than two classes is not obvious. In this paper several multi-category SVM methods are introduced and compared using simulation and real data sets. Also comparison with traditional multi-category classification and SVM based methods is performed.