LSSVM 最小二乘仿真程序
X = (0.1:0.2:12.5)'
Y = log(10*X)+sin(X)+normrnd(0,0.1,length(X),1)
gam = 9.8647;
sig2 = 0.3269;
%gam = 947.85;
%sig2 = 0.3229;
Xt=(12.5:0.2:18.5)'
type = 'function estimation';
[alpha,b] = trainlssvm({X,Y,type,gam,sig2,'RBF_kernel','preprocess'});
Yt
=simlssvm({X,Y,type,gam,sig2,'RBF_kernel','preprocess'},{alpha,b},Xt)
Yp = predict({X,Y,type,gam,sig2}, Xt)
plotlssvm({X,Y,type,gam,sig2,'RBF_kernel','preprocess'},{alpha,b}),ho
ld on
plot(X,Y,'r:')
plot(Xt,Yt)
legend()
hold off
plot([ X,Y,'r:'],[Xt,Yt])
legend off
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