利用Matlab_libsvm构造支持向量机回归算法

1、利用Matlablibsvm构造支持向量机回归算法ticclear;clc;Fnum=4;%输入个数/输出个数只能为1个TnumX=0.8;%训练数据比例Terror=0.2;%误差小于Terror的预测比例eps=10(7);%误差阈值v=6;%交互检验%寻找最佳c参数/g参数CVcmax=10;cmin=-10;gmax=10;gmin=-10;cstep=1;gstep=1;msestep=0.05;local=C:Users37989Desktop2688.xlsx;%数据文件地址data=xlsread(local);Ynum,Xnum=size(data);Train=data(r

2、andperm(Ynum),:);Tnum=round(TnumX*Ynum);TSnum=Ynum-Tnum;%主要修改以上数据以下代码不要修改%训练集p_train=Train(1:Tnum,1:Fnum);%2:4是回弹后的零件5列是分组标记t_train=Train(1:Tnum,Fnum+1);%测试集p_test=Train(Tnum+1:Ynum,1:Fnum);%这个改了R8000生成的只有3列t_test=Train(Tnum+1:Ynum,Fnum+1);%无所谓%数据归一化%训练集pn_train,inputps=mapminmax(p_train);%归一化方法？pn_

3、train=pn_train;tn_train,outputps=mapminmax(t_train);tn_train=tn_train;%测试集pn_test=mapminmax(apply,p_test,inputps);pn_test=pn_test;tn_test=mapminmax(apply,t_test,outputps);tn_test=tn_test;%SVM莫型创建/训练%寻找最佳c参数/g参数CVc,g=meshgrid(cmin:cstep:cmax,gmin:gstep:gmax);m,n=size(c);cg=zeros(m,n);bestc=0;bestg=0;

4、error1=Inf;count=1;%循环前h=waitbar(O,正在计算.);fori=1:ma=i;forj=1:n%寻优的cmd参数应该与下文训练的cmd相符cmd=-v,num2str(v),-t2,-c!num2str(2Ac(a,j)!-g!num2str(2Ag(a,j),-s3-p0.1-q;%0.01cg(a,j)=svmtrain(tn_train,pn_train,cmd)*10000;ifcg(a,j)errorlerrorl=cg(a,j);%回归均方根误差bestc=2Ac(a,j);bestg=2Ag(a,j);endifabs(cg(a,j)-errorl)

5、2Ac(a,j)%两次的mse相差很小取c较小的errorl=cg(a,j);bestc=2Ac(a,j);bestg=2Ag(a,j);endwaitbar(count/(m*n),h);count=count+1;endendcg,ps=mapminmax(cg,0,1);figure;set(gcf,position,0,100,1366,500);%13是宽度24是高度subplot(1,2,1)C,h=contour(c,g,cg,0.0023:msestep:0.5);clabel(C,h,FontSize,14,Color,r);xlabel(log_2C,FontName,Ti

6、mes,FontSize,14);ylabel(log_2g,FontName,Times,FontSize,14);firstline=SVR参数选择结果图(等高线图)GridSearchMethod;secondline=BestC=,num2str(bestc),g=,num2str(bestg),.CVmse=,num2str(error1);title(firstline;secondline,Fontsize,14);gridon;set(gca,xtick,cmin:cstep:cmax);set(gca,ytick,gmin:gstep:gmax);subplot(1,2,2)

7、meshc(c,g,cg);%mesh(X,Y,cg);%surf(X,Y,cg);axis(cmin,cmax,gmin,gmax,0,1);xlabel(log_2C,FontName,Times,FontSize,14);ylabel(log_2g,FontName,Times,FontSize,14);zlabel(MSE,FontName,Times,FontSize,14);firstline=SVR参数选择结果图(3D视图)GridSearchMethod;secondline=BestC=,num2str(bestc),g=,num2str(bestg),.CVmse=,num

8、2str(error1);title(firstline;secondline,Fontsize,14);%创建/训练SVM%参考libsvm使用说明对cmd参数修改cmd=-t2,-c,num2str(bestc),-g,num2str(bestg),-s3-p0.001;model=svmtrain(tn_train,pn_train,cmd);%SVMf方真预测Predict_2,error_2,decision_values=svmpredict(tn_test,pn_test,model);%反归一化F=mapminmax(reverse,Predict_2,outputps);toc%输出结果E=F-t_test;E=F-t_test;percent=sum(ETerror)/TSnum*100;MSE=sum(ES2)/TSnum;mse_norm=error_2(2);R2=error_2(3);SD=std(E);Result=t_test,F,abs(t_test-F);fprintf(%4.3ft%4.3ft%4.3fn,Result);fprintf(nc=%4.4fg=%4.4fnSTD=%4.4fM