东南大学学报（自然科学版）2013，Vol.43Issue(z1)：206-209,4.DOI:10.3969/j.issn.1001-0505.2013.S1.043
面向大规模数据集的单类支持向量机
One-class support vector machines for large-scale data sets
摘要
Abstract
A method to train one-class support vector machine (OCSVM) on the large-scale data sets is proposed.The proposed method selects inner points representing the distribution characteristics of the original large-scale data sets based on the principle of k-nearest neighbor,and generates the edge points using the inner points selected.A new data set is formed by combining these two kinds of points to train OCSVM.The new data set not only reduces the volume of the original large-scale data set greatly,but also maintains the distribution characteristics of the original data set.Thus the problems faced by OCSVM on the large-scale data sets,such as long training time,complicated models and low predicting speed,are effectively solved.Finally,the experiment is conducted on typical data sets to illustrate the effectiveness of the method proposed.关键词
单类支持向量机/大规模数据集/数据集压缩Key words
one-class support vector machine/ large data sets/ training-set condensation分类
信息技术与安全科学引用本文复制引用
肖志博,王焕钢,肖英超,徐文立..面向大规模数据集的单类支持向量机[J].东南大学学报（自然科学版）,2013,43(z1):206-209,4.基金项目
国家高技术研究计划(863计划)资助项目(2011AA060203)、国家重点基础研究发展计划(973计划)资助项目(2009CB320602). （863计划）
