e_kernel_classifier.asv

具有图形操作界面的支持向量机多类分类实验系统.全部用Matlab实现,可以实现多种分类识别. 这是本人的毕业设计的附属程序

% load input data
trn = load('riply_trn');
subplot(3,1,1);title('原始分布1');cla;
 h1=ppatterns(trn); legend([h1],'Training set');

% train kernel PCA by greedy algorithm
options = struct('ker','rbf','arg',1,'new_dim',10);
kpca_model = greedykpca(trn.X,options);
% project data
map_trn = kernelproj(trn,kpca_model);
% train linear classifier
lin_model = fld(map_trn);
% combine linear rule and kernel PCA
kfd_model = lin2svm(kpca_model,lin_model);
% visualization

subplot(3,1,1);title('原始分布1');cla;
 h1=ppatterns(trn);
 pboundary(kfd_model);
 ppatterns(kfd_model.sv.X,'ok',13);

 % evaluation on testing data 

 subplot(3,1,2);title('原始分布2');
 
 tst = load('riply_tst');
 h2=ppatterns(tst);

ypred = svmclass(tst.X,kfd_model);
cerror(ypred,tst.y)
h2=ppatterns(ypred);

 legend([h2],'Training set');
 
 subplot(3,1,3);title('原始分布3');
 h3=ppatterns(tst);
 legend([h3],'Training set');