main.m

模式识别中的K均值算法

clear all;
close all;
Data=[0 0 1 1 1 2 2 3 6 6 7 7 7 8 8 8 8 9 9 9
      0 1 0 1 2 1 2 2 6 7 6 7 8 6 7 8 9 7 8 9;];
[DataRow,DataColumn]=size(Data);
Step=2;
NumKind=2;
Center=Data(:,1:NumKind) %取Data中的数为分类点
[KindData,KindNum]=Clustering(Center,Data);
NewCenter=CaculateCenter(KindData,KindNum,DataRow);


err_r=zeros(1,NumKind)
for k=1:NumKind 
  for g=1:DataRow 
      err_r(k)=err_r(k)+(NewCenter(g,k)-Center(g,k)).^2;
  end
end
err=sum(sqrt(err_r))

while err>=Step
    err_r=zeros(1,NumKind);
    Center=NewCenter;
    [KindData,KindNum]=Clustering(Center,Data);
    NewCenter=CaculateCenter(KindData,KindNum,DataRow);
    
for k=1:NumKind 
  for g=1:DataRow 
      err_r(k)=err_r(k)+(NewCenter(g,k)-Center(g,k)).^2;
  end
end
   err=sum(sqrt(err_r))
end

for i=1:NumKind
  KindData(:,1:KindNum(i),i) %列出分类清单
end

plot(KindData(1,1:KindNum(1),1),KindData(2,1:KindNum(1),1),'b*')
hold on
plot(NewCenter(1,1),NewCenter(2,1),'bo')
%hold on
 plot(KindData(1,1:KindNum(2),2),KindData(2,1:KindNum(2),2),'r.')
%hold on
plot(NewCenter(1,2),NewCenter(2,2),'rx')