Theory of fisher linear discriminant analysis and its application 线性鉴别分析的理论研究及其应用
A study on personal credit scoring using linear discriminant analysis 线性判别式分析在个人信用评估中的应用
A new two - dimensional linear discriminant analysis algorithm based on fuzzy set theory 基于模糊集理论的二维线性鉴别分析新方法
In this paper , we focus on two - class discriminating problem and chiefly study two types of linear discriminant analysis : principal component classifier ( pcc ) and fisher linear discriminant analysis ( flda ) 本文就两分类问题,研究了两种线性判别:主分量分类器和fisher判别分析。
Linear discriminant analysis (LDA) and the related Fisher's linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.