| 增强型单类支持向量机 |
| |
| 引用本文： | 冯爱民,薛晖,刘学军,陈松灿,杨明.增强型单类支持向量机[J].计算机研究与发展,2008,45(11). |
| |
| 作者姓名： | 冯爱民 薛晖 刘学军 陈松灿 杨明 |
| |
| 作者单位： | 1. 南京航空航天大学信息科学与技术学院,南京,210016
2. 南京师范大学计算机科学系,南京,210097 |
| |
| 基金项目： | 国家自然科学基金项目，江苏省博士后科研资助计划基金项目 |
| |
| 摘 要： | 现有基于超平面的单类分类器,包括one-class SVM(OCSVM)和马氏one-class SVM(MOCSVM),由于未考虑数据的结构信息或粒度较粗,寻找的超平面很可能是次优解.为此,增强型单类支持向量机(enhanced OCSVM,EnOCSVM)通过在现有SVM算法中加入数据先验信息以克服其不足.首先,EnOCSVM通过聚类得到数据的内在分布簇,而后将各簇结构信息嵌入到OCSVM框架中,最大化间隔的同时,优化输出空间中各簇数据的繁性.由于保留了SVM框架不变,EnOCSVM仍具备原算法的全部优点,并因结合了数据的簇结构信息而具有更好的推广性.标准数据集上的实验表明,EnOCSVM的推广性能较OCSVM和MOCSVM均有显著提高.
|
| 关 键 词： | 单类分类器 超平面 结构信息 支持向量机 簇分布 |
Enhanced One-Class SVM |
| |
| Feng Aimin,Xue Hui,Liu Xuejun,Chen Songcan,Yang Ming.Enhanced One-Class SVM[J].Journal of Computer Research and Development,2008,45(11). |
| |
| Authors: | Feng Aimin Xue Hui Liu Xuejun Chen Songcan Yang Ming |
| |
| Affiliation: | Feng Aimin1,Xue Hui1,Liu Xuejun1,Chen Songcan1,, Yang Ming21(College of Information Science & Technology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016)2(Department of Computer Science,Nanjing Normal University,Nanjing 210097) |
| |
| Abstract: | One-class-classifier (OCC) aims to distinguish a target class from outliers. Existing OCC algorithms based on hyperplane, such as one-class SVM (OCSVM) and Mahalanobis one-class SVM (MOCSVM), solve this problem by finding a hyperplane with the maximum distance to the origin. However, since they either neglect the structure of the given data or just takes the structure into account in a relatively coarse granularity, only the suboptimal hyperplane may be abtained. In order to mitigate this problem, a novel O... |
| |
| Keywords: | one-class-classifier hyperplane structure information support vector machine multi-clustered |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
