k-means.zip_k-means++ matlab_kmeans聚类matlab_kmeans聚类函数_matlab k-

%% 数据准备和初始化 clc clear close all x=[0 0; 1 0; 0 1;1 1;2 1; 1 2; 2 2;3 2;6 6;7 6;8 6;6 7; 7 7;8 7;9 7;7 8;8 8;9 8;8 9;9 9]; z1=zeros(2,2); z=x(1:2,1:2); %% 寻找聚类中心 while 1 count=zeros(2,1); allsum=zeros(2,2); for i=1:20 %对每一个样本i，计算到2个聚类中心的距离 temp1=sqrt((z(1,1)-x(i,1)).^2+(z(1,2)-x(i,2)).^2); temp2=sqrt((z(2,1)-x(i,1)).^2+(z(2,2)-x(i,2)).^2); if(temp1<temp2) count(1)=count(1)+1; allsum(1,1)=allsum(1,1)+x(i,1); allsum(1,2)=allsum(1,2)+x(i,2); else count(2)=count(2)+1; allsum(2,1)=allsum(2,1)+x(i,1); allsum(2,2)=allsum(2,2)+x(i,2); end end z1(1,1)=allsum(1,1)/count(1); z1(1,2)=allsum(1,2)/count(1); z1(2,1)=allsum(2,1)/count(2); z1(2,2)=allsum(2,2)/count(2); if(z==z1) break; else z=z1; end end %% 结果显示 disp(z1);%输出聚类终须 plot(x(:,1),x(:,2),'k*',... 'LineWidth',2,... 'MarkerSize',10,... 'MarkerEdgeColor','k',... 'MarkerFaceColor',[0.5,0.5,0.5]) hold on plot(z1(:,1),z1(:,2),'ko',... 'LineWidth',2,... 'MarkerSize',10,... 'MarkerEdgeColor','k',... 'MarkerFaceColor',[0.5,0.5,0.5]) set(gca,'linewidth',2); xlabel('特征x1','fontsize',12); xlabel('特征x2','fontsize',12); title('K-means分类图','fontsize',12);