Volume 35 Issue 11
Nov.  2009
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Zhou Hao, Li Shaohong. Relative position modification of SVM’s optimal hyperplane[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(11): 1302-1305. (in Chinese)
Citation: Zhou Hao, Li Shaohong. Relative position modification of SVM’s optimal hyperplane[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(11): 1302-1305. (in Chinese)

Relative position modification of SVM’s optimal hyperplane

  • Received Date: 20 Oct 2008
  • Publish Date: 30 Nov 2009
  • Through releasing the equal-margin constraint in the standard support vector machines (SVM), keeping the sum of the binary-class function margins, a new SVM was gotten within the framework of SVM. The separating hyperplane of the new SVM can be adjusted as per the distribution of the binary-class samples, and its dual express is same as the standard SVM. Thus, the SVM was further improved theoretically. On the basis of the new SVM, a concrete algorithm, variance modification algorithm, was proposed. In the variance modification algorithm, the binary-class margins are in proportion to the standard deviation of binary-class samples. The goal of adjusting the optimal separating hyperplane as per sample-s variance is attained through the variance modification algorithm. Statistically, errors are reduced through the variance modification algorithm, while the computational complexity is not increased much.

     

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