支持向量机非线性回归通用MATLAB源码.doc

文档介绍：支持向量机非线性回归通用MATLAB源码
% Epsilon ε不敏感损失函数的参数，Epsilon越大，支持向量越少
% C 惩罚系数，C过大或过小，泛化能力变差
% TKF Type of Kern
='off';
%%
%%
%------------------------整理输出回归方程的系数------------------------------
Alpha1=(Gamma(1:l,1))';
Alpha2=(Gamma((l+1):end,1))';
Alpha=Alpha1-Alpha2;
Flag=2*ones(1,l);
%%
%%
%---------------------------支持向量的分类----------------------------------
Err=;
for i=1:l
AA=Alpha1(i);
BB=Alpha2(i);
if (abs(AA-0)<=Err)&&(abs(BB-0)<=Err)
Flag(i)=0;%非支持向量
end
if (AA>Err)&&(AA Flag(i)=2;%标准支持向量
end
if (abs(AA-0)<=Err)&&(BB>Err)&&(BB Flag(i)=2;%标准支持向量
end
if (abs(AA-C)<=Err)&&(abs(BB-0)<=Err)
Flag(i)=1;%边界支持向量
end
if (abs(AA-0)<=Err)&&(abs(BB-C)<=Err)
Flag(i)=1;%边界支持向量
end
end
%%
%%
%--------------------计算回归方程中的常数项B---------------------------------
B=0;
counter=0;
for i=1:l
AA=Alpha1(i);
BB=Alpha2(i);
if (AA>Err)&&(AA %计算支持向量加权值
SUM=0;
for j=1:l
if Flag(j)>0
switch TKF
case 1
SUM=SUM+Alpha(j)*sum(X(:,j).*X(:,i));
case 2
SUM=SUM+Alpha(j)*(sum(X(:,j).*X(:,i))+c)^p;
case 3
SUM=SUM+Alpha(j)*exp(-(norm(X(:,j)-X(:,i)))^2/(2*sigma^2));
case 4
SUM=SUM+Alpha(j)*exp(-norm(X(:,j)-X(:,i))/(2*sigma^2));
case 5
SUM=SUM+Alpha(j)*1/(1+exp(-v*sum(X(:,j).*X(:,i))+c));
otherwise
SUM=SUM+Alpha(j)*exp(-(sum((X(:,j)-X(:,i)).^2)/(2*sigma^2)));
end
end
end
b=Y(i)-SUM-Epsilon;
B=B+b;
counter=counter+1;
end
if (abs(AA-0)<=Err)&&(BB>Err)&&(BB SUM=0;
for j=1:l
if Flag(j)>0
switch TKF
case 1
SUM=SUM+Alpha(j)*sum(X(:,j).*X(:,i));
case 2
SUM=SUM+Alpha(j)*(sum(X(:,j).*X(:,i))+c)^p;
case 3
SUM=SUM+Alpha(j)*exp(-(norm(X(:,j)-X(:,i)))^2/(2*sigma^2));
case 4
SUM=SUM+Alpha(j)*exp(-norm(X(:,j)-X(:,i))/(2*sigma^2));
case 5
SUM=SUM+Alpha(j)*1/(1+exp(-v*sum(X(:,j).*X(:,i))+c));
otherwise
SUM=SUM+Alpha(j)*exp(-(sum((X(:,j)-X(:,i)).^2)/(2*sigma^2)));
end
end
end
b=Y(i)-SUM+Epsilon;
B=B+b;
counter=counter+1;
end
end
if counter==0
B=0;
else
B=B/counter;
end
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