e_pca.m

支持向量机工具箱

figure('name','特征提取_PCA方法');


%addpath G:\Matlab_EXP\stprtool
%addpath G:\Matlab_EXP\stprtool\data
X = gsamp([5;5],[1 0.8;0.8 1],100); % generate data
model = pca(X,1); % train PCA
Z = linproj(X,model); % lower dim. proj.
XR = pcarec(X,model); % reconstr. data
figure; hold on; axis equal; % visualization
pause;
h1 = ppatterns(X,'kx');pause;
h2 = ppatterns(XR,'bo');pause;
[dummy,mn] = min(Z);
[dummy,mx] = max(Z);pause;
h3 = plot([XR(1,mn) XR(1,mx)],[XR(2,mn) XR(2,mx)],'r');pause;
legend([h1 h2 h3], ...
'Input vectors','Reconstructed', 'PCA subspace');

clear;clc;