e_kpca.m

支持向量机工具箱

%addpath G:\Matlab_EXP\stprtool
%addpath G:\Matlab_EXP\stprtool\data%\riply_data
figure('name','特征提取_LPCA方法');


X = gencircledata([1;1],5,250,1); % generate circle data
subplot(1,2,1);title('原始分布');
 h1=ppatterns(X);
 legend([h1],'Training set');
options.ker = 'rbf'; % use RBF kernel
options.arg = 4; % kernel argument
options.new_dim = 2; % output dimension
model = kpca(X,options); % compute kernel PCA
XR = kpcarec(X,model); % compute reconstruced data

subplot(1,2,2);title('重构数据分布');

h2 = ppatterns(XR,'+r');
legend([h2],'Reconstructed');

clear;clc;