Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Multiclass Classification via Least Squares Support Vector Machine Regression

  • Shim, Joo-Yong (Department of Applied Statistics, Catholic University of Daegu) ;
  • Bae, Jong-Sig (Department of Mathematics, Sungkyunkwan University) ;
  • Hwang, Chang-Ha (Division of Information and Computer Science, Dankook University)
  • Published : 2008.05.30
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Abstract

In this paper we propose a new method for solving multiclass problem with least squares support vector machine(LS-SVM) regression. This method implements one-against-all scheme which is as accurate as any other approach. We also propose cross validation(CV) method to select effectively the optimal values of hyper-parameters which affect the performance of the proposed multiclass method. Experimental results are then presented which indicate the performance of the proposed multiclass method.

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References

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