Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Polychotomous Machines;

  • Koo, Ja-Yong (Department of Statistics, Inha University) ;
  • Park, Heon Jin (Department of Statistics, Inha University) ;
  • Choi, Daewoo (Department of Statistics, Hankuk University of Foreign Studies)
  • Published : 2003.04.01
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Abstract

The support vector machine (SVM) is becoming increasingly popular in classification. The import vector machine (IVM) has been introduced for its advantages over SMV. This paper tries to improve the IVM. The proposed method, which is referred to as the polychotomous machine (PM), uses the Newton-Raphson method to find estimates of coefficients, and the Rao and Wald tests, respectively, for addition and deletion of import points. Because the PM basically follows the same addition step and adopts the deletion step, it uses, typically, less import vectors than the IVM without loosing accuracy. Simulated and real data sets are used to illustrate the performance of the proposed method.

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References

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