k_means.m

数据挖掘K－平均算法的MATLAB程序

clear all;
%pionts=100; %Inout the pionts number
k=4; %Input the class number
load data100_noise.txt;
data=data100_noise;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%% K-Means Clustering %%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%data=randn(pionts,2);
size_data=length(data);
%============= Random Initial Center Points =========
cent=randperm(size_data); 
for i=1:k
    initial_center(i,:)=data(cent(i),:);
end
%================== Distence Matrix =================
for i=1:k
    for j=1:size_data
        a=data(j,1);b=data(j,2);
        c=initial_center(i,1);
        d=initial_center(i,2);
        disten(j)=sqrt((a-c)^2+(b-d)^2);
    end
    D(i,:)=disten;
    e(i)=sum(D(i,:));
end  
E(1)=sum(e);
%======================= Class ======================
[n1,n2]=size(D);
for i=1:n2
    for j=1:n1
        dd(j)=D(j,i);
    end
    mindd=min(dd);
    for s=1:n1
        if(dd(s)==mindd)
            class(i)=s;
        end
    end
end
%================= The Average Value =================
for i=1:k
ad=1;
clear C;
    for j=1:size_data
        if(class(j)==i)
            C(ad,:)=data(j,:);
            ad=ad+1;
        end
    end
    aver_x(i)=sum(C(:,1))/(ad-1);
    aver_y(i)=sum(C(:,2))/(ad-1);
end
%================== New Center Pionts =================
new_center=[aver_x;aver_y]';

%------------circle------------
count=1;
Class_new=class;
distence;

plot(aver_x,aver_y,'+k');hold on;

while true
count=count+1;
    if(class==Class_new)
        disp(class),break
    else
        Class_new=class;
        distence;
    end
end
%========================= Plot =======================
plot(aver_x,aver_y,'ok');hold on; %Center pionts

for i=1:k
acc=1;b=['*g'
         '.r'
         '*b'
         '.m'
         '*c'
         '.y'];
clear Cc;
clear d;
    for j=1:size_data
        if(class(j)==i)
            Cc(acc,:)=data(j,:);
            acc=acc+1;
        end
    end
    CX=Cc(:,1);
    CY=Cc(:,2);
    d=b(i,:);
    plot(CX,CY,d);hold on; %Data pionts
end
figure;
plot(E);