计算机工程与应用2013，Vol.49Issue(3)：210-212,221,4.DOI:10.3778/j.issn.1002-8331.1107-0024
一种改进Fisher准则的线性鉴别分析方法
Linear discriminant analysis based on improved Fisher criterion
戴文战 1周昌亮1
作者信息
- 1. 浙江理工大学机械与自动化学院,杭州310018
- 折叠
摘要
Abstract
Traditional linear discriminant analysis is based on Fisher criterion or weighted pairwise Fisher criterion. The former can' t restrain outlier classes, and the latter has high computation complexity, for that, a new improved Fisher criterion for linear discriminant analysis is presented. Fisher criterion and weighted pairwise Fisher criterion are reviewed. Reasons for their drawbacks are pointed out. Class distance and class outlier level are defined. Class outlier level is based on class distance. Each class is given weights for its outlier level, so as to re-estimate global mean vector and between-class scatter matrix, in order to get the new improved Fisher criterion which emphasizes less on outlier classes and more on normal classes. The improved Fisher criterion can restrain outlier classes without high computation complexity.关键词
线性鉴别分析/Fisher准则/离群类/人脸识别Key words
linear discriminant analysis/ Fisher criterion/ outlier class/ face recognition分类
信息技术与安全科学引用本文复制引用
戴文战,周昌亮..一种改进Fisher准则的线性鉴别分析方法[J].计算机工程与应用,2013,49(3):210-212,221,4.
