PCA如何来进行降维 %% This scr ipt generates and plots 3D data, and performs a principal %% component analysis to decorrelate the data, and to reduce the %% dimensionality of the feature space. % Note that matlab has an optimized function to perform PCA: pr
1 Introduction 1 1.1 Classical and robust approaches to statistics 1 1.2 Mean and standard deviation 2 1.3 The “three-sigma edit” rule 5 1.4 Linear regression 7 1.4.1 Straight-line regression 7 1.4.2 Multiple linear regression 9 1.5 Correlation coef
str='F:\\code\\matlab\\face\\face'; %图像存放路径 S=0.0;%行向量 dis=zeros(1,100,'double');%每一个人脸跟平均脸的距离 b=zeros(2700,400,'double');%人脸向量矩阵 for i=1:2700 B=imread([str,num2str(i),'.bmp']); %依次读取每一幅图像 m = size(B, 3); if m==1 I = B; else I=rgb2gray(B); end %在此处进
