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article · 2010

On Multiclass Support Vector Machines: One-Against-Half Approach

Jying‐Nan Wang, Sheng-Te Chou, Xinfeng

Cited by 1Abstract and details only

Abstract

⎯Support vector machines (SVM) was originally designed for binary classification. SVM has been recently applied to solve multi-class problems. And there lies the unsolving research issues on developing 2-class SVM into multi-class SVM. In this paper, five common multi-class SVMs have been reviewed and a new multi-class SVM has been proposed along with the comparison between the performance of one-against-half method and the other five multi-class SVMs. The experiments proved oneagainst-half method to be a qualified multi-class SVM. Keyword⎯One-against-half method, Support vector machines, Multi-classification. ∗ Corresponding author’s e-mail: s929603@mail.yzu.edu.tw International Journal of Operations Research 1813-713X Copyright © 2009 ORSTW

Cite this paper

APA 7

Wang, J., Chou, S.-T., & Xinfeng. (2010). On Multiclass Support Vector Machines: One-Against-Half Approach.

MLA 9

Wang, Jying‐Nan, et al. “On Multiclass Support Vector Machines: One-Against-Half Approach.” 2010.

Chicago

Wang, Jying‐Nan, Sheng-Te Chou, and Xinfeng. 2010. “On Multiclass Support Vector Machines: One-Against-Half Approach.”

Harvard

Wang, J., Chou, S.-T. and Xinfeng (2010) ‘On Multiclass Support Vector Machines: One-Against-Half Approach’.

BibTeX
@article{wang2010multiclass,
  title = {{On Multiclass Support Vector Machines: One-Against-Half Approach}},
  author = {Wang, Jying‐Nan and Chou, Sheng-Te and Xinfeng},
  year = {2010}
}

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