PCA steps: 1 of the first data center 2 covariance matrix obtained 3 obtained covariance matrix eigenvalues and eigenvectors 4 eigenvalues and eigenvectors will be sorted 5 according to the dimension of dimension reduction d ' , seek to reduce the dimension projection direction 6, the data obtained after the dimensionality reduction

马新悦 0610210076 实验4\fisher\fisher.m
.......................\......\FLDA_classify.m
.......................\......\input.mat
.......................\......\main.m
.......................\......\target.mat
.......................\基于Fisher准则线性分类器设计.doc
.......................\基于Fisher准则线性分类器设计.docx
.......................\fisher
马新悦 0610210076 实验4

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