KNN.rar_knn_knn matlab_knn分类_knn数据

x=xlsread('F:\matlab7.0\work\air.xlsx'); a=0;b=0; for i=1:200 if x(i,8)==0 a=a+1; y(a,:)=x(i,:); else b=b+1; z(b,:)=x(i,:); end end test_data=x(201:238,:); train_data=[y(:,1:7);z(:,1:7)]; classify=[y(:,8);z(:,8)]; m=11;n=0; for j=1:38 for k=1:200 d(j,k)=sqrt((test_data(j,1:7)-train_data(k,:))*(test_data(j,1:7)-train_data(k,:))'); end [di(j,:),s(j,:)]=sort(d(j,:),'ascend'); n0(j)=0; for f=1:m classify_new(j,f)=classify(s(j,f)); if classify_new(j,f)==0 n0(j)= n0(j)+1; end n1(j)=m-n0(j); if n0(j)>n1(j) classify_test(j)=0; else classify_test(j)=1; end end if label_test(j)==test_data(j,8) n=n+1; end end classify_test pe=1-n/23 figure; hold on; plot(test_data(:,8),'bo'); plot(classify_test,'r*'); legend('实际分类','预测分类'); %%测试集的实际分类和预测分类对比图%% title('测试集的实际分类和预测分类图','FontSize',12); grid on;