模糊聚类 matlab 代码,模糊聚类+Matlab代码

算法原理

Matlab代码

%根据lambda截集，模糊聚类

clear;

x = [80,10,6,2;

50,1,6,4;

90,6,4,6;

40,5,7,3;

10,1,2,4]; %样本

row = size(x,1); %样本个数

x2 = bz(x); %标准化

R = gm(x2); %构造模糊相似矩阵

biBao = transBiBao(R); %求传递闭包

[L,J] = lambdaJie(biBao); %截集

[T] = juLei(L,J,row); %聚类

H = dendrogram(T); %绘制聚类谱系图

function [x2] = bz(x)

%最大值标准化

temp = max(x);

x2 = x./temp;

end

function [R] = gm(x2)

%最大最小法构造模糊相似矩阵

row = size(x2,1);

R = zeros(row,row);

for i = 1:row

for j = 1:row

R(i,j) = sum(jiao(x2(i,:),x2(j,:)))/sum(bing(x2(i,:),x2(j,:)));

end

end

end

function [Z] = jiao(X,Y)

%两个矩阵交

[row,col] = size(X);

Z = zeros(row,col);

for i = 1:row

Z(i,:) = min([X(i,:);Y(i,:)]);

end

end

function [Z] = bing(X,Y)

%并

[row,col] = size(X);

Z = zeros(row,col);

for i = 1:row

Z(i,:) = max([X(i,:);Y(i,:)]);

end

end

function [Ystar] = heCheng(X,R)

%合成

rowX = size(X,1);

colR = size(R,2);

Ystar = zeros(rowX,colR);

for i = 1:rowX

for j = 1:colR

Ystar(i,j) = max(min([X(i,:);R(:,j)’]));

end

end

end

function [biBao] = transBiBao(X)

%传递背包

Y = heCheng(X,X);

while Y ~= X

X = Y;

Y = heCheng(X,X);

end

biBao = Y;

biBao = biBao-diag(diag(biBao))+eye(size(biBao));

end

function [lambda,jieMatrix] = lambdaJie(X)

%lambda截集

lambda = unique(X);

len = length(lambda);

jieMatrix = zeros([size(X),len]);

for i = 1:len

temp = X;

temp(X<=lambda(i)) = 0;

temp(X>=lambda(i)) = 1;

jieMatrix(:,:,i) = temp;

end

end

function [Z] = juLei(L,J,geShu)

%聚类

len = size(J,3); %聚类次数

mark = [-1,-1,-1]; %暂时生成，记录每次聚类的两个对象及此使的lambda

for i=len:-1:1 %从独自一类到全部一类

mat = triu(J(:,:,i)); %选择上三角矩阵

[row,col] = find(mat==1);

temp = [row,col]; %聚类的两个对象

panDuan = [mark;[temp,ones(size(temp,1),1)*L(i)]]; %lambda

[~,temp2] = unique(panDuan(:,1:2),’rows’); %去重

mark = panDuan(temp2,:);

end

mark = mark(2:end,:); %将第一个去掉

mark(:,3) = 1-mark(:,3); %lambda反转

T = sortrows(mark,3); %排序

T = T(geShu+1:end,:); %将独自一类的去掉

B = T(:,1:2); %不选择lambda

len = size(B,1);

visited = [];

Y = 1:2; %为之后setdiff做准备

Z = []; %为dendrogram做准备

flag = geShu+1; %加上中间过程类的数目，不断递增

for i=1:len

temp1 = B(i,:);

[C,ia] = setdiff(temp1,visited); %没有出现过的记录下来

if length(C) == 2

Z = [Z;[temp1,T(i,3)]];

elseif length(C) == 1 %重复的标记为flag

temp2 = setdiff(Y,ia);

temp1(temp2)= flag;

flag=flag+1;

Z = [Z;[temp1,T(i,3)]];

end

visited = [visited,C];

end

end

运行结果