Performance comparison of SVM and neural networks for Large-set classification problems 


Vol. 12,  No. 1, pp. 25-30, Feb.  2005
10.3745/KIPSTB.2005.12.1.25


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  Abstract

In this paper, we analyzed and compared the performances of modular FFMLP(feedforward multilayer perceptron) and SVM(Support Vector Machine) for the large-set classification problems. Overall, SVM dominated modular FFMLP in the correct recognition rate and other aspects. Additionally, the recognition rate of SVM degraded more slowly than neural network as the number of classes increases. The trend of the recognition rates depending on the rejection rate has been analyzed. The parameter set of SVM(kernel functions and related variable) has been identified for the large-set classification problems.

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[IEEE Style]

J. S. Lee, Y. W. Kim, I. S. Oh, "Performance comparison of SVM and neural networks for Large-set classification problems," The KIPS Transactions:PartB , vol. 12, no. 1, pp. 25-30, 2005. DOI: 10.3745/KIPSTB.2005.12.1.25.

[ACM Style]

Jin Seon Lee, Young Won Kim, and II Seok Oh. 2005. Performance comparison of SVM and neural networks for Large-set classification problems. The KIPS Transactions:PartB , 12, 1, (2005), 25-30. DOI: 10.3745/KIPSTB.2005.12.1.25.

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