feisher

代码说明：

  PCA的步骤： 1 先将数据中心化； 2 求得的协方差矩阵； 3 求出协方差矩阵的特征值与特征向量； 4 将特征值与特征向量进行排序； 5 根据要降维的维数d’,求得要降维的投影方向； 6 求出降维后的数据； (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 )

文件列表：

马新悦 0610210076 实验4
.......................\fisher
.......................\......\fisher.m,1158,2009-09-05
.......................\......\FLDA_classify.m,1573,2009-12-07
.......................\......\input.mat,1582,2009-09-05
.......................\......\main.m,167,2009-12-07
.......................\......\target.mat,186,2009-09-05
.......................\基于Fisher准则线性分类器设计.doc,174080,2009-12-09
.......................\基于Fisher准则线性分类器设计.docx,142132,2009-12-07