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.
丁晓剑, 赵银亮. 无偏置ν-SVM分类优化问题研究[J]. 电子与信息学报, 2011, 33(8): 1998-2002.
Ding Xiao-Jian, Zhao Yin-Liang. Study on ν-SVM for Classification Optimization Problem without Bias. , 2011, 33(8): 1998-2002.