Matlab 基于K-means实现数据聚类分析含Matlab源码.zip

function KmeansMain close all;clear;clc; %随机生成随机数 mu = [0 0]; %协方差矩阵，对角为方差值0.3，0.35 var = [0.3 0; 0 0.35]; samNum = 200; data = mvnrnd(mu, var, samNum); a = figure; plot(gca, data(:,1), data(:,2), '*', 'color', 'k');hold on; classNum = [];%类数 iterNum = 0;%迭代次数 x = []; centerPoint = []; centerPointPathAarry = []; h_plotCenterPoint = [];%中心点绘制handle h_plotPath = [];%中心点路径绘制handle %centerPointPathAarry结构 %第1次迭代|中心点1(x,y)|中心点2(x,y)|中心点3(x,y)|中心点n(x,y) %第2次迭代|中心点1(x,y)|中心点2(x,y)|中心点3(x,y)|中心点n(x,y) h_slider = uicontrol(a,'Style', 'slider',... 'SliderStep',[0.02 0.02],... 'Min',0,'Max',50,'Value',0,... 'Position', [400 20 100 20],... 'Callback', {@classify,gca}); h_edit = uicontrol(a,'Style', 'edit',... 'String', '200',... 'Position', [80 20 40 20],... 'Callback', {@paintRandomPoint,gca}); uicontrol('Style', 'popup',... 'String', '自定义|随机2点|随机3点|随机4点',... 'Position', [200 22 120 20],... 'Callback', {@SpsfPoit,gca}); h_t1 = uicontrol('Style','text','String','迭代', ... 'Position', [355 20 40 20]); h_textClassNum = uicontrol('Style','text','String','中心点', ... 'Position', [140 20 55 20]); uicontrol('Style','text','String','样本点数:', ... 'Position', [25 20 50 20]); h_textshow = uicontrol('Style','text','String','0','Position', [500 20 20 20]); set(gca,'xtick',[],'ytick',[],... 'title',text('string','Kmeans演示脚本','color','k')); xlim([-1.5 1.5]);ylim([-1.5 1.5]); %%%%%%%%%%%%%%%%%%%% function SpsfPoit(hObj,event,ax) set(h_slider,'value',0); %清零滑动条，以实现从0迭代 cla;%清空axes set(h_textshow,'string',0);%界面显示的迭代次数清零 %句柄赋值为空 h_plotCenterPoint = []; h_plotPath = []; centerPointPathAarry = [];%轨迹归零 plot(gca, data(:,1), data(:,2), '*', 'color', 'k');%样本点颜色初始化 val = get(hObj, 'Value');%获得popup menu的值 if val == 1 %选择任意若干点作为中心点 [x, y] = ginput; centerPoint = [x y]; [classNum, ~] = size(centerPoint); repaintBeginPoint(h_plotCenterPoint, classNum, centerPoint); elseif val == 2 %选择任意2点作为中心点 centerPoint = rand(2, 2)*2-0.5; [classNum, ~] = size(centerPoint); repaintBeginPoint(h_plotCenterPoint, classNum, centerPoint); elseif val == 3 %选择任意3点作为中心点 centerPoint = rand(3, 2)*2-0.5; [classNum, ~] = size(centerPoint); repaintBeginPoint(h_plotCenterPoint, classNum, centerPoint); elseif val == 4 %选择任意4点作为中心点 centerPoint = rand(4,2)*2-0.5; [classNum,~] = size(centerPoint); repaintBeginPoint(h_plotCenterPoint, classNum, centerPoint); end [labelSample] = classifyAndShowAndLabel(classNum, centerPoint, data, samNum, gca); centerPointPathAarry = [centerPointPathAarry; reshape(centerPoint', 1, classNum*2)]; set(h_textClassNum, 'string', [num2str(classNum) '个中心点']); end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%迭代分类函数%%%%%%%%%%%%%%%%%%%% function classify(hObj,event,ax) iterNum = round(get(hObj, 'value')); set(h_textshow, 'string', iterNum); %根据起始点分类，并且为不同的类标记不同颜色，返回带标签样本数据 [labelSample] = classifyAndShowAndLabel(classNum, centerPoint, data, samNum, gca); %重新获得起始点矩阵centerPoint（x|y） [centerPoint] = recalClassCenter(labelSample, classNum); centerPointPathAarry = [centerPointPathAarry; reshape(centerPoint', 1, classNum*2)]; %重新绘制起始点centerPoint（x|y）到axes上 repaintBeginPoint(h_plotCenterPoint, classNum, centerPoint); disp('path:'); disp(centerPointPathAarry);%将中心点的轨迹显示出来 for i = 1:classNum [selected_color] = colorMap(i, classNum); h_plotPath(i)=plot(centerPointPathAarry(:, (i*2)-1), centerPointPathAarry(:,i*2), 'color', selected_color); end end %%%%%%%%%%%%%%%函数部分%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%重新绘制起始点函数%%%%%%%%% function repaintBeginPoint(handle_plo,classnum,R) delete(h_plotCenterPoint);%清除绘制的中心点，并将句柄赋值为空 h_plotCenterPoint=[]; %重新绘制起始点，每个起始点的颜色不同 for i = 1:classnum [selected_color] = colorMap(i, classnum); h_plotCenterPoint(i) = plot(R(i,1), R(i,2), 'o', 'MarkerSize', 7, 'MarkerFaceColor', selected_color); end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%重新计算类重心%%%%%%%%%%%%%%%%%%%%%% function [newCenterPoint]=recalClassCenter(labelSample,classNum) %R为重新被计算的类中心 newCenterPoint=[]; %分类并且计算每个类的重心 for i=1:classNum %取出所有标签为i类的所有行，即第i类的所有点 classs=labelSample(labelSample(:,3)==i,:); %有用的只有第一列和第二列，去除标签列 classs=[classs(:,1),classs(:,2)]; %重新计算重心 classs_repoint=mean(classs); newCenterPoint=[newCenterPoint;classs_repoint]; end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%根据起始点分类，并且为不同的类标记不同颜色，返回带标签样本数据%%%%%%%%% function [labelSample]=classifyAndShowAndLabel(classNum,centerPoint,data1,samNum,gca) disArray=[]; for i=1:classNum calproA=[centerPoint(i,:);data1(:,1),data1(:,2)]; Adist=pdist(calproA,'euclidean'); Adist=Adist(1:samNum)'; disArray=[disArray,Adist]; end %拼接,得到距离矩阵，一列代表一个点到所有样本点的距离 %disArray=[Adist Bdist]; %disp(disArray); %获取每一行最小值所在距离矩阵的列 %并和原样本矩阵拼接为labelSample %labelSample 表示被标记的原始样本，每一行为一个样本 %每一行的最后一列为标记值，在这里标记是距离哪个样本点最近。 minn=min(disArray'); cols=[]; for i=1:length(minn) [row,col] = find(disArray==minn(i)); cols(i)=col; end cols=cols'; labelSample=[data1(:,1),data1(:,2),cols]; %将不同类的点标上不同的颜色 for i=1:samNum [selected_color]=colorMap(labelSample(i,3),classNum); plot(gca,data1(i,1),data1(i,2),'*','color',selected_color); end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%样本点选择并绘制函数%%%%%%%%%%%%%%%%%%%%%%%%%%% function paintRandomPoint(hObj,event,ax) textt = get(hObj, 'string'); samNum = str2num(textt); data = mvnrnd(mu, var, samNum); cla; set(h_slider,'value',0); %清零滑动条，以实现从0迭代 plot(ax,data(:,1), data(:,2), '*', 'color', 'k');hold on; end end