K-mean Plotting for 3 Dimensional Data

Question

Я работаю с k-средствами в MATLAB. Я пытаюсь создать график/график, но мои данные имеют трехмерный массив. Вот мой к-средства код:

clc 
clear all 
close all 
load cobat.txt; % read the file 

k=input('Enter a number: ');  % determine the number of cluster 
isRand=0; % 0 -> sequeantial initialization 
      % 1 -> random initialization 

[maxRow, maxCol]=size(cobat); 
if maxRow<=k, 
    y=[m, 1:maxRow]; 
elseif k>7 
    h=msgbox('cant more than 7'); 
else 
    % initial value of centroid 
    if isRand, 
     p = randperm(size(cobat,1));  % random initialization 
     for i=1:k 
      c(i,:)=cobat(p(i),:); 
     end 
    else 
     for i=1:k 
      c(i,:)=cobat(i,:);  % sequential initialization 
     end 
    end 

    temp=zeros(maxRow,1); % initialize as zero vector 
    u=0; 
    while 1, 
     d=DistMatrix3(cobat,c); % calculate the distance 
     [z,g]=min(d,[],2);  % set the matrix g group 

     if g==temp,    % if the iteration doesn't change anymore 
      break;    % stop the iteration 
     else 
      temp=g;    % copy the matrix to the temporary variable 
     end 
     for i=1:k 
      f=find(g==i); 
      if f    % calculate the new centroid 
       c(i,:)=mean(cobat(find(g==i),:),1); 
      end 
     end 
     c 
     [B,index] = sortrows(c); % sort the centroids 
     g = index(g); % arrange the labels based on centroids 
    end 
    y=[cobat,g] 

    hold off;  

    %This plot is actually placed in plot 3D code (last line), but I put it into here, because I think this is the plotting line 
    f = PlotClusters(cobat,g,y,Colors) %Here is the error 
    if Dimensions==2 
    for i=1:NumOfDataPoints %plot data points  
     plot(cobat(i,1),cobat(i,2),'.','Color',Colors(g(i),:)) 
     hold on 
    end 
    for i=1:NumOfCenters %plot the centers 
     plot(y(i,1),y(i,2),'s','Color',Colors(i,:)) 
    end 
else 
    for i=1:NumOfDataPoints %plot data points 
     plot3(cobat(i,1),cobat(i,2),cobat(i,3),'.','Color',Colors(g(i),:)) 
     hold on 
    end 
    for i=1:NumOfCenters %plot the centers 
     plot3(y(i,1),y(i,2),y(i,3),'s','Color',Colors(i,:)) 
    end 

    end 
end 

А вот сюжет 3D-код:

%This function plots clustering data, for example the one provided by 
%kmeans. To be able to plot, the number of dimensions has to be either 2 or 
%3. 
%Inputs: 
%  Data - an m-by-d matrix, where m is the number of data points to 
%    cluster and d is the number of dimensions. In my code, it is cobat 
%  IDX - an m-by-1 indices vector, where each element gives the 
%    cluster to which the corresponding data point in Data belongs. In my file, it is 'g' 
%  Centers y - an optional c-by-d matrix, where c is the number of 
%    clusters and d is the dimensions of the problem. The matrix 
%    gives the location of the cluster centers. If this is not 
%    given, the centers will be calculated. In my file, I think, it is 'y' 
%  Colors - an optional color scheme generated by hsv. If this is not 
%    given, a color scheme will be generated. 
% 
function f = PlotClusters(cobat,g,y,Colors) 
%Checking inputs 
switch nargin 
    case 1 %Not enough inputs 
     error('Clustering data is required to plot clusters. Usage: PlotClusters(Data,IDX,Centers,Colors)') 
    case 2 %Need to calculate cluster centers and color scheme 
     [NumOfDataPoints,Dimensions]=size(cobat); 
     if Dimensions~=2 && Dimensions~=3 %Check ability to plot 
      error('It is only possible to plot in 2 or 3 dimensions.') 
     end 
     if length(g)~=NumOfDataPoints %Check that each data point is assigned to a cluster 
      error('The number of data points in Data must be equal to the number of indices in IDX.') 
     end 
     NumOfClusters=max(g); 
     Centers=zeros(NumOfClusters,Dimensions); 
     NumOfCenters=NumOfClusters; 
     NumOfPointsInCluster=zeros(NumOfClusters,1); 
     for i=1:NumOfDataPoints 
      Centers(g(i),:)=y(g(i),:)+cobat(i,:); 
      NumOfPointsInCluster(g(i))=NumOfPointsInCluster(g(i))+1; 
     end 
     for i=1:NumOfClusters 
      y(i,:)=y(i,:)/NumOfPointsInCluster(i); 
     end 
     Colors=hsv(NumOfClusters);   
    case 3 %Need to calculate color scheme   
     [NumOfDataPoints,Dimensions]=size(cobat); 
     if Dimensions~=2 && Dimensions~=3 %Check ability to plot 
      error('It is only possible to plot in 2 or 3 dimensions.') 
     end 
     if length(g)~=NumOfDataPoints %Check that each data point is assigned to a cluster 
      error('The number of data points in Data must be equal to the number of indices in IDX.') 
     end 
     NumOfClusters=max(g); 
     [NumOfCenters,Dims]=size(y); 
     if Dims~=Dimensions 
      error('The number of dimensions in Data should be equal to the number of dimensions in Centers') 
     end 
     if NumOfCenters<NumOfClusters %Check that each cluster has a center 
      error('The number of cluster centers is smaller than the number of clusters.') 
     elseif NumOfCenters>NumOfClusters %Check that each cluster has a center 
      disp('There are more centers than clusters, all will be plotted') 
     end 
     Colors=hsv(NumOfCenters); 
    case 4 %All data is given just need to check consistency   
     [NumOfDataPoints,Dimensions]=size(cobat); 
     if Dimensions~=2 && Dimensions~=3 %Check ability to plot 
      error('It is only possible to plot in 2 or 3 dimensions.') 
     end 
     if length(g)~=NumOfDataPoints %Check that each data point is assigned to a cluster 
      error('The number of data points in Data must be equal to the number of indices in IDX.') 
     end 
     NumOfClusters=max(g); 
     [NumOfCenters,Dims]=size(y); 
     if Dims~=Dimensions 
      error('The number of dimensions in Data should be equal to the number of dimensions in Centers') 
     end 
     if NumOfCenters<NumOfClusters %Check that each cluster has a center 
      error('The number of cluster centers is smaller than the number of clusters.') 
     elseif NumOfCenters>NumOfClusters %Check that each cluster has a center 
      disp('There are more centers than clusters, all will be plotted') 
     end 
     [NumOfColors,RGB]=size(Colors); 
     if RGB~=3 || NumOfColors<NumOfCenters 
      error('Colors should have at least the same number of rows as number of clusters and 3 columns') 
     end    
end 
%Data is ready. Now plotting 

end 

Здесь ошибка:

??? Undefined function or variable 'Colors'. 

Error in ==> clustere at 69 
    f = PlotClusters(cobat,g,y,Colors) 

Я ошибаюсь вызов функции вроде этого ? Что мне делать? Ваша помощь будет оценена очень много.

Answer 1

Ваш код очень грязный, и излишне долго ..

Вот пример меньше, что делает то же самое. Вы будете нуждаться в Statistics Toolbox, чтобы запустить его (для kmeans функции и Iris набора данных):

%# load dataset of 150 instances and 3 dimensions 
load fisheriris 
X = meas(:,1:3); 
[numInst,numDims] = size(X); 

%# K-means clustering 
%# (K: number of clusters, G: assigned groups, C: cluster centers) 
K = 3; 
[G,C] = kmeans(X, K, 'distance','sqEuclidean', 'start','sample'); 

%# show points and clusters (color-coded) 
clr = lines(K); 
figure, hold on 
scatter3(X(:,1), X(:,2), X(:,3), 36, clr(G,:), 'Marker','.') 
scatter3(C(:,1), C(:,2), C(:,3), 100, clr, 'Marker','o', 'LineWidth',3) 
hold off 
view(3), axis vis3d, box on, rotate3d on 
xlabel('x'), ylabel('y'), zlabel('z') 

Answer 2

Вы могли бы просто пойти на scatter():

Как вы можете видеть на картинке, вы различать цвета, размера кластеров. Более подробная информация приведена в документации.