计算机工程与应用Issue(16)：31-34,61,5.DOI:10.3778/j.issn.1002-8331.1208-0471
基于改进停机准则的SMO算法
Improved stopping criteria based SMO algorithm
摘要
Abstract
In SMO training process, standard KKT stopping criteria will lead to training speed declining along with training progress. According to the optimum theory, if the dual gap is zero, convex quadratic optimization problem will also obtain global optimal solution. Therefore, an improved stopping criteria of SMO is proposed in this paper, it combines the duality gap and standard KKT condition as the stopping criteria. This algorithm can improve the training speed without training accuracy decrease. Two cases experimental simulating results corroborate the efficiency of this algorithm.关键词
支持向量机回归/序列最小优化算法/对偶间隙/KKT条件/停机准则Key words
Support Vector Regression/Sequential Minimal Optimization(SMO)/duality gap/Karush-Kuhn-Tucker (KKT)/Stopping Criteria分类
信息技术与安全科学引用本文复制引用
韩顺成,马小晴,陈进东,潘丰..基于改进停机准则的SMO算法[J].计算机工程与应用,2014,(16):31-34,61,5.基金项目
国家高技术研究发展计划（863）（No.2009AA05Z203）；江苏高校优势学科建设工程资助项目。 （）
