SVM自编程序_SVM_SVM轴承故障_故障识别_轴承_svm轴承

%主函数 clear all; clc; C = 10; kertype = 'linear'; %训练样本 n = 50; randn('state',6);%可以保证每次每次产生的随机数一样 x1 = randn(2,n); %2行N列矩阵 y1 = ones(1,n); %1*N个1 x2 = 5+randn(2,n); %2*N矩阵 y2 = -ones(1,n); %1*N个-1 figure; plot(x1(1,:),x1(2,:),'bx',x2(1,:),x2(2,:),'k.'); axis([-3 8 -3 8]); xlabel('x轴'); ylabel('y轴'); hold on; X = [x1,x2]; %训练样本d*n矩阵，n为样本个数，d为特征向量个数，在这里，X为一个2*100的数组 Y = [y1,y2]; %训练目标1*n矩阵，n为样本个数，值为+1或-1，在这里，Y为一个1*100的数组 svm = svmTrain(X,Y,kertype,C); plot(svm.Xsv(1,:),svm.Xsv(2,:),'ro'); %测试 [x1,x2] = meshgrid(-2:0.05:7,-2:0.05:7); %x1和x2都是181*181的矩阵 [rows,cols] = size(x1); nt = rows*cols; Xt = [reshape(x1,1,nt);reshape(x2,1,nt)]; Yt = ones(1,nt); result = svmTest(svm, Xt, Yt, kertype); Yd = reshape(result.Y,rows,cols); contour(x1,x2,Yd,'m');