兵工自动化2011，Vol.30Issue(4)：85-87,3.DOI:10.3969/j.issn.1006-1576.2011.04.028
代价敏感支持向量机的投影次梯度求解方法
Projection Sub-Gradient Solving Method for Cost-Sensitive SVM
摘要
Abstract
Aiming at the traditional method and its precision which used as evaluation index can not meet the requirements of practical classification. Introduce cost sensitive method into SVM, put forward a new learning algorithm CSSVM (cost-sensitive SVM), and acquire projection sub-gradient solving method which is similar as Pegasos to deal with large scale data. The Pegasos process includes initialization, iteration, ascertaining step lengths and direction of sub-gradient descent, update, projection and the end. The test results show that this algorithm can effectively improve identifying rate and identifying precision and it is competitive.关键词
不均衡数据/代价敏感/支持向量机/大规模数据Key words
class-imbalance data/ cost-sensitive/ SVM/ large scale data分类
信息技术与安全科学引用本文复制引用
梁万路..代价敏感支持向量机的投影次梯度求解方法[J].兵工自动化,2011,30(4):85-87,3.基金项目
国家自然科学基金项目"统计学习理论与算法研究"(60575001)和"基于损失函数的统计机器学习算法及其应用研究"(60975040) （60575001）
