democl1.m

SVM支持向量机 里面包含一个教程

clear
close all
grain = 100;

load ripley;

echo on;


%
% RADIAL BASE FUNCTION KERNEL
%

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

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

% make-a-plot
figure;
plotlssvm({X,Y,'classifier',gam,sig2,kernel,'preprocess'},{alpha,b},grain);

% receiver operator characteristics CURVE
roc({X,Y,'classifier',gam,sig2,kernel,'preprocess'},'figure');

disp('press <ENTER>');
pause





%
% LINEAR KERNEL
%

% train
gam = 10;
kernel = 'lin_kernel';
sig2 = [];
[alpha,b] = trainlssvm({X,Y,'classifier',gam,sig2,kernel,'preprocess'});

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

% make-a-plot
figure;
plotlssvm({X,Y,'classifier',gam,sig2,kernel,'preprocess'},{alpha,b},grain);

% receiver operator characteristics CURVE
roc({X,Y,'classifier',gam,sig2,kernel,'preprocess'},'figure');


kernel = 'poly_kernel';
sig2 = [1;3];
kernel = 'MLP_kernel';
sig2 = [1;3];


echo off;