中南大学学报（自然科学版）2012，Vol.43Issue(7)：2648-2654,7.
支持向量机平凡解判别与修正的新方法
A new method for discrimination and modification of null solutions in support vector machines
摘要
Abstract
For binary classification problems, a new method for discrimination and modification of null solutions in linear support vector machines (SVMs) was proposed. The following theorems for discrimination of null solutions in SVMs were proved: The necessary and sufficient conditions for the optimal solution of SVMs being a null solution are that for a given training set, the distribution of the positive and negative samples must satisfy an inequality which is related to the respective penalty parameters C+, C- of the two classes, and is independent of the shared penalty parameter C. Based on the above results, a modification method for null solutions in SVMs was presented by selecting samples in the training set, and adjusting the values of penalty parameters, which provides theoretical support and technique method for avoiding generating null solutions in SVMs. Computational examples illustrate the effectiveness of the proposed methods.关键词
支持向量机/惩罚因子/平凡解/闭凸包Key words
support vector machine/penalty parameter/null solution/convex hull分类
信息技术与安全科学引用本文复制引用
刘春明,左磊,吴军..支持向量机平凡解判别与修正的新方法[J].中南大学学报（自然科学版）,2012,43(7):2648-2654,7.基金项目
国家自然科学基金资助项目(60774076,90820302) （60774076,90820302）
