K均值聚类（Kmeans）

Sigma = [1, 0; 0, 1];
mu1 = [1, -1];
x1 = mvnrnd(mu1, Sigma, 200);
mu2 = [5.5, -4.5];
x2 = mvnrnd(mu2, Sigma, 200);
mu3 = [1, 4];
x3 = mvnrnd(mu3, Sigma, 200);
mu4 = [6, 4.5];
x4 = mvnrnd(mu4, Sigma, 200);
mu5 = [9, 0.0];
x5 = mvnrnd(mu5, Sigma, 200);
% obtain the 1000 data points to be clustered
X = [x1; x2; x3; x4; x5];
% Show the data point
plot(x1(:,1), x1(:,2), 'r.'); hold on;
plot(x2(:,1), x2(:,2), 'b.');
plot(x3(:,1), x3(:,2), 'k.');
plot(x4(:,1), x4(:,2), 'g.');
plot(x5(:,1), x5(:,2), 'm.');

save myX  %将X存储到文件中，在其他文件中load就可以了

结果如下：

 % 初始聚类中心
 mu0=[X(,:); X(,:);X(,:);X(,:);X(,:)];
 mu1=zeros(,c);
 lable=zeros(r,);
 % first cluster
     dist=zeros(,);
     for k=:r
         for n=:
             dist(n)=norm(X(k,:)-mu0(n,:));
         end
         lable(k)=find(dist==min(dist));
     end    

 %     X1=[lable X];
     sum=zeros(,);
     count=zeros(,);

  % 第一次聚类
     for n=:
         for k=:r
             if lable(k)==n
              sum(n,:)=sum(n,:)+X(k,:);
              count(n)=count(n)+;
             end
         end
         mu1(n,:)=sum(n,:)/count(n);
     end

  % square error
     e=zeros(,);
     esum=;
     for n=:
         for k=:r
             if lable(k)==n
                  e(n,:)=e(n,:)+norm(X(k,:)-mu1(n,:));
             end
         end
         esum=esum+e(n,:);
     end

 % ***************** start Iteration **************

 countNotX=;% 到达一定值后，停止迭代
 s=;
 count1=zeros(,);
 while true
     s=s+;
 %random choose X to update
     ran=round(+*rand());%总共1000个样本
     Xrand=X(ran,:);
     rou=zeros(,);
     rouMin=inf;
     newClassLable=;
     if count(lable(ran))~=
         for n=:
             if lable(ran)==n
                 rou(n)=norm(Xrand-mu1(n,:))*count(n)/(count(n)-);
             else
                 rou(n)=norm(Xrand-mu1(n,:))*count(n)/(count(n)+);
             end
             if rou(n)<=rouMin;
                 rouMin=rou(n);
                 newClassLable=n;
             end
         end
        if rouMin<rou(lable(ran))
             countNotX=;
 %              new mu  这里用课件中的公式，不知道哪里错了，总是不行，就用最蠢的办法了
            for n=:
                 for k=:r
                     if lable(k)==n
                      sum(n,:)=sum(n,:)+X(k,:);
                      count1(n)=count1(n)+;
                     end
                 end
                 mu1(n,:)=sum(n,:)/count1(n);
            end
 %             new count
             count(lable(ran))=count(lable(ran))-;
             count(newClassLable)=count(newClassLable)+;
 %           new esum
             e(lable(ran),:)=e(lable(ran),:)-rou(lable(ran));
             e(newClassLable,:)=e(newClassLable,:)+rouMin;
              esum=esum+rouMin-rou(lable(ran));
              lable(ran)=newClassLable ;
          else
 %            disp('No')
            countNotX= countNotX+;
            if countNotX==
                %when J is not changed for  times,reckon OK
                break
            end
        end
     end
 end