计算机应用与软件2013，Vol.30Issue(6)：16-18,3.DOI:10.3969/j.issn.1000-386x.2013.06.005
确定经验风险水平的线性规划支持向量回归算法
LINEAR PROGRAMMING SUPPORT VECTOR REGRESSION ALGORITHM WITH GIVEN EMPIRICAL RISK
摘要
Abstract
Traditional linear programming support vector regression algorithm needs to choose a tradeoff coefficient C for making certain the proportion between the empirical risk and the confidence risk,generally speaking it is not easy to choose an optimal C in correspondence to different data.In order to solving the problem,a linear programming support vector regression with given empirical risk is proposed,it can make sure the extent of empirical risk in advance.In addition,the new algorithm can also solve the problem of heterogeneity of variance existing in samples by setting different empirical risks for different samples.The results of simulative experiments verify the feasibility and effectiveness of the proposed algorithm.关键词
线性规划/支持向量回归/经验风险/结构风险/置信风险Key words
Linear programming / Support vector regression / Empirical risk / Structural risk / Confidence risk分类
信息技术与安全科学引用本文复制引用
孙德山,马冬玲,柳莎莎,盛超..确定经验风险水平的线性规划支持向量回归算法[J].计算机应用与软件,2013,30(6):16-18,3.基金项目
国家自然科学基金项目(61105059). （61105059）
