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SVM���ŷ��������λ�õ�����
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Relative position modification of SVM’s optimal hyperplane
Zhou Hao, Li Shaohong*
School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

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ժҪ ͨ���ſ��׼֧��������(SVM,Support Vector Machines)�����߽���������ȼ����Լ��,�������ຯ�����֮�Ͳ��������,��֧��������˼�����µó��������������ֲ����е���������֧��������,���ż��ʽ���׼֧����������ȫ��ͬ,�Ӷ��������Ͻ�һ��������֧��������.�ڴ˻�����,���ʹ���ĺ������������������׼��ľ����㷨——����������,�ﵽ���ŷ���������λ�����������������֮Ŀ��.��ͳ����������˵,�����������ڷ��ྫ�����������,�����������Ӳ���.
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Abstract�� 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.
Keywords�� support vector machines   modification   computational complexity   classifiers     
Received 2008-10-20;
About author: �� �(1970-),��,����������,��ʿ��,zhouhao@ee.buaa.edu.cn.
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�� �, ���ٺ�.SVM���ŷ��������λ�õ�����[J]  �������պ����ѧѧ��, 2009,V35(11): 1302-1305
Zhou Hao, Li Shaohong.Relative position modification of SVM’s optimal hyperplane[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2009,V35(11): 1302-1305
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