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| Study on ν-SVM for Classification Optimization Problem without Bias |
| Ding Xiao-jian Zhao Yin-liang |
| School of Electrical and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China |
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Abstract In the high-dimensional space, the classification hyperplane tends to pass through the origin and bias (b) is not need. To study whether ν-SVM for classification needs (b), dual optimization formulation of ν-SVM without (b) is proposed and the corresponding method of solving the optimization formulation is presented. The dual optimization formulation is transformed into equality constraint sub-optimization formulation by the active set strategy in this method, then the sub-optimization formulation is transformed into the linear equation by lagrange multiplier method. The experimental results show that the existence of (b) would reduce the generalization ability of ν-SVM and ν-SVM can only obtain the sub-optimal solution of ν-SVM without b.
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Received: 22 November 2010
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Corresponding Authors:
Ding Xiao-jian
E-mail: xjding@stu.xjtu.edu.cn
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2011, Vol. 33 
