testkmean.m

K-mean 模式識別分析法使用k-mean作為分析方法

clear all
close all
clc
load('\data.mat')
k=4;

%%%%%%%%%%%%%%%%%%%%%
%  Funcion k-means  %
%%%%%%%%%%%%%%%%%%%%%
[center, Xcluster, Ycluster, clustering]=kmean(X, Y, k);

% Presentation of results per screen.

% Create the colors.
color=zeros(k,3);
for i=1:k
    color(i,:)=rand(1,3);
end;

% Represent information.
figure;
hold on;
for i=1:k,
    n=find(clustering==i);
    p=plot(X(n), Y(n),'.');
    set(p,'Color',color(i,:));
    title(['Number of clusters:  ',num2str(k)])
end;