demor4.m

SVM支持向量机 里面包含一个教程

clear
close all
echo on;

X = (-6:0.1:6)';
Y = (sin(pi.*X+eps)./(pi.*X+eps))+normrnd(0,0.2,length(X),1);
Xt = (-6:.01:6)';


% train
gam = 25;
sig2 = 0.2;

figure(1);
subplot(1,2,1);
[alpha,b] = trainlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});
plotlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},{alpha,b});
hold on; plot(Xt,sinc(Xt),'r-.'); hold off

figure(2);
[alpha,b] = robustlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});
plotlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},{alpha,b});
hold on; plot(Xt,sinc(Xt),'r-.'); hold off
title('robust weighted LS-SVM');

echo off



disp('Press <ENTER>');
pause


outlier = 1.5*rand(size(Y(1:12:end)))-.75;

for i=1:10,

  Y(1:12:end) = Y(1:12:end)+outlier;
  
  figure(1);
  subplot(1,2,1);
  [alpha,b] = trainlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});
  plotlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},{alpha,b});
  hold on; plot(Xt,sinc(Xt),'r-.'); hold off
  
  figure(2);
  [alpha,b] = robustlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});
  plotlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},{alpha,b});
  hold on; plot(Xt,(sin(pi.*Xt+eps)./(pi.*Xt+eps)),'r-.'); hold off
  title('robust weighted LS-SVM');  
  
end