demor2.m

SVM支持向量机 里面包含一个教程

clear
close all
echo on;

X = (-3:0.1:3)';
Y = X.^3+normrnd(0,3,length(X),1);
Xt = (-4:.0111:4)';


%
% RADIAL BASE FUNCTION KERNEL
% 

% train
gam = 10;
kernel = 'RBF_kernel';
sig2 = .5;
[alpha,b] = trainlssvm({X,Y,'function',gam,sig2,kernel,'preprocess'});

% simulate
Yt = simlssvm({X,Y,'function',gam,sig2,kernel,'preprocess'},{alpha,b},Xt);

% make-a-plot
figure;
plotlssvm({X,Y,'function',gam,sig2,kernel,'preprocess'},{alpha,b});
hold on; plot(Xt,Xt.^3,'r-.'); plot(Xt,Yt,'b-.'); hold off


disp('press <ENTER>');
pause



% 
% POLYNOOM KERNEL
%

% train
gam = 10;
kernel = 'poly_kernel';
sig2 = [1;3];
[alpha,b] = trainlssvm({X,Y,'function',gam,sig2,kernel,'preprocess'});

% simulate 
Yt = simlssvm({X,Y,'function',gam,sig2,kernel,'preprocess'},{alpha,b}, Xt);

% make-a-plot
figure;
plotlssvm({X,Y,'function',gam,sig2,kernel,'preprocess'},{alpha,b});
hold on; plot(Xt,Xt.^3,'r-.'); plot(Xt,Yt,'b-.');hold off


echo off