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Comparison Study of Multi-class Classification Methods

  • Bae, Wha-Soo (Department of Data Science and Institute of Statistical Information, Inje University) ;
  • Jeon, Gab-Dong (Telluce Corporation) ;
  • Seok, Kyung-Ha (Department of Data Science and Institute of Statistical Information, Inje University)
  • Published : 2007.08.31

Abstract

As one of multi-class classification methods, ECOC (Error Correcting Output Coding) method is known to have low classification error rate. This paper aims at suggesting effective multi-class classification method (1) by comparing various encoding methods and decoding methods in ECOC method and (2) by comparing ECOC method and direct classification method. Both SVM (Support Vector Machine) and logistic regression model were used as binary classifiers in comparison.

Keywords

References

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