demor3.m~

来自「SVM支持向量机 里面包含一个教程」· M~ 代码 · 共 30 行

clear
close all
echo on;

X = (-6:0.1:6)';
Y = (sin(pi.*X+eps)./(pi.*X+eps))+0.2*sin(X*10)+normrnd(0,0.1,length(X),1);
Xt = (-6:.01:6)';


% train
gam = 2;
sig2 = 0.02;
[alpha,b] = trainlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});


figure; plotlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});

%
% tuning with gridsearch
%
%[gam, sig2] = tunelssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},[1 0.005; 10000 10], 'gridsearch', {}, 'leaveoneout_lssvm');
%[gam, sig2] = tunelssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},[1 0.005; 10000 10], 'gridsearch', {}, 'crossvalidate');
[gam, sig2] = tunelssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'},[1 0.005; 10000 10], 'gridsearch', {}, 'gcvlssvm');

figure; plotlssvm({X,Y,'function',gam,sig2,'RBF_kernel','preprocess'});
hold on; plot(Xt,(sin(pi.*Xt+eps)./(pi.*Xt+eps))+0.2*sin(10*Xt),'r-.'); hold off


echo off