Question

我有一个程序，可以在运行时生成10个固定点和3个随机点。我希望10个固定点使用K-means聚类，但不知道从哪里开始。我的代码在

之下

function TESTING (re_point)

%***********************NOTE*************************************
% if re_point = 0 [default]
%     points generated for xtemp and y_temp remain fixed
% if re_point = 1
%     new points are generated for x_temp and y_temp

% Variable definitions for tags and figure window
persistent xtemp ytemp hFig

% Initialisiation of re_point
if nargin<1
    re_point = 0; % If 0, the points are fixed, if 1 they move
end

A1 = 30; % area defined as 30 X 30 grid
N = 10;
R = 3; % 3 readers
s = rng; % fixed tags does not change position when simulated repatedly
rng(s)

if (isempty(xtemp) && isempty(xtemp)) || re_point == 1
    % Generate x and y position of tags 
    xtemp = A1*rand(1,N);
    ytemp = A1*rand(1,N);
end
if isempty(hFig)
    hFig = figure;
end

% Generate x and y position of red points 
xtemp_2 = A1*rand(1,R);
ytemp_2 = A1*rand(1,R);

% plot data
plot(xtemp,ytemp,'.',xtemp_2,ytemp_2,'rs','LineWidth',1,'MarkerEdgeColor','k','MarkerFaceColor','r','MarkerSize',14);

% Labelling of the red markers
for iter = 1:numel(xtemp_2)
    text(xtemp_2(iter),ytemp_2(iter), num2str(iter),...
        'FontSize',8,'HorizontalAlignment','center',...
        'Color','White','FontWeight','bold');
end

grid on
hold off
axis([0 A1 0 A1])

% Tag formatting
xoffset = 0;
yoffset = -1;
fsize = 8;
temp_str = mat2cell(num2str([xtemp(:) ytemp(:)], '(%.2f,%.2f)'), ones(1,N));
text(xtemp+xoffset, ytemp+yoffset, temp_str,'fontsize', fsize)

% distance function calculator
cDistance = distanceCalc()

    function S = distanceCalc
        S = size(numel(xtemp),numel(xtemp_2));
        for ri = 1:numel(xtemp)
            for fi = 1:numel(xtemp_2)
                S(ri,fi) = pdist([xtemp(ri),ytemp(ri);...
                            xtemp_2(fi),ytemp_2(fi)],...
                            'euclidean');
            end
        end
    end

end

上面这个块中的特定片段生成需要聚类的10个固定点

if (isempty(xtemp) && isempty(xtemp)) || re_point == 1
        % Generate x and y position of tags 
        xtemp = A1*rand(1,N);
        ytemp = A1*rand(1,N);
    end

Answer 1

您的问题根本不清楚您要对kmeans做什么，例如您要查找多少个群集？我建议查看MATLAB ref guide

中的第一个示例

对于您的数据，您可以尝试例如

X = [xtemp(:) ytemp(:)];
Nclusters = 3;
[idx,C] = kmeans(X,Nclusters);

对于绘图，以下内容应该有效：

figure, hold on
plot(X(idx==1,1),X(idx==1,2),'b*')
plot(X(idx==2,1),X(idx==2,2),'g*')
plot(X(idx==3,1),X(idx==3,2),'r*')

开始使用。这将尝试将您的随机点分类为3个群集。每个点已被分类到的簇在idx中定义。

K-Means在Matlab中对随机数进行聚类

1 个答案: