光学精密工程2012，Vol.20Issue(1)：140-147,8.DOI:10.3788/OPE.20122001.0140
基于边界的最大间隔模糊分类器
Maximum-margin fuzzy classifier based on boundary
摘要
Abstract
Several kinds of current boundary classification methods based on hyperplane, hypersphere or ellipsoid were studied, and a novel classification method called Maximum-margin Fuzzy Classifier (MFC) was proposed by using a space point as the classification criterion. By the proposed method, a fuzzy classified point c was chosen in the pattern space firstly, which should be as close to two classes as possible. Moreover, the angle between the two classes should be also as large as possible. Then, the testing points could be classified in terms of the maximum angular margin between c and all the training points. Finally, the applications of the MFC were popularized from two-class classification to one-class classification according to the kernel dual of MFC equivalent to the Minimum Enclosed Ball (MEB). Comparative experiments with current classification methods verify that the MFC has good classification performance and noise resistance ability and its classification accuracy has been reached 98.9%.关键词
模式分类/模糊分类器/模糊分类点/抗噪能力/单类问题Key words
pattern classification/ fuzzy classifier/ fuzzy classified point/ noise resistance/ one-class classification分类
信息技术与安全科学引用本文复制引用
刘忠宝,王士同..基于边界的最大间隔模糊分类器[J].光学精密工程,2012,20(1):140-147,8.基金项目
国家863高技术研究发展计划资助项目(No.2007AA1Z158,No.2006AA10Z313) （No.2007AA1Z158,No.2006AA10Z313）
国家自然科学基金资助项目(No.60773206,No.60704047) （No.60773206,No.60704047）
