e_greedykpca.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_greedykpca方法');


X = gencircledata([1;1],5,250,1); % generate training data
subplot(3,1,1);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
options.m = 25; % size of sel. subset
model = greedykpca(X,options); % run greedy algorithm 
XR = kpcarec(X,model); % reconstructed vectors

subplot(3,1,2);title('新分布一');
h2 = ppatterns(XR,'+r');
 legend([h2],'Reconstructed set');

subplot(3,1,3);title('新分布二');
h3 = ppatterns(model.sv.X,'ob',12);
legend([h3], 'Selected subset');

clear;
clc;