Kmeans algorithm for data

Hi everyone.

I need help, checking internet I found the following code;

in= load('C:\Users\Profesional\Desktop\datos_RBR.txt'); % *174x3 double input parameters*

x= (in-min(in(:))) ./ (max(in(:)))-min(in(:));  %normalize values

N= 4; %number of clusters

iter= 100; %number of iterations

centros= x( ceil(rand(N,1)*size(x,1)) ,:); % ubication of the centers (random) 

DAL   = zeros(size(x,1),N+2); 
CV    = '+r+b+c+m+k+yorobocomokoysrsbscsmsksy';       % Color Vector

for n = 1:iter

   for i = 1:size(x,1)
        for j = 1:N  
          DAL(i,j) = norm(x(i,:) - centros(j,:));     % Menor distancia
        end
        [Distance CN] = min(DAL(i,1:N));                % 1:K are Distance from Cluster Centers 1:K 
        DAL(i,N+1) = CN;                                % K+1 etiquetación
        DAL(i,N+2) = Distance;                          % K+2 distancia minima
     end 
     for i = 1:N
        A = (DAL(:,N+1) == i);                          % Cluster K Points
        centros(i,:) = mean(x(A,:));                      % media de cada columna para centros
        if sum(isnan(centros(:))) ~= 0                    %eliminamos posiles valores NAN delete NAN valors
           NC = find(isnan(centros(:,1)) == 1);           % encontrar centros minimos
           for Ind = 1:size(NC,1)
           centros(NC(Ind),:) = x(randi(size(x,1)),:);
           end
        end
     end
  end
  %  Plot   
   clf
   figure(1)
  hold on
  for i = 1:N
   PT = x(DAL(:,N+1) == i,:);                            % encontrar los puntos de cada neurona // find points   
   plot(PT(:,1),PT(:,2),CV(2*i-1:2*i),'LineWidth',2);    % Plot groups
   plot(centros(:,1),centros(:,2),'*k','LineWidth',7);       % Plotear centers
   end
  hold off
  grid on
  pause(0.1)

Well, this one allows me set the number of cluster (groups),number of iterations and clust the input values which is really good, however, I don't know how to view the number of values or points that containes each cluster (group), I would appreciate your help.

I've added two notes one with the code and the other one with the input values (datos_RBR.txt) as well

Answer 1

[KSSV]

data = importdata('data.txt') ;
x = data(:,1) ; 
y = data(:,2) ; 
z = data(:,3) ;

N = 3 ; % number of groups 
idx = kmeans(data,N) ;   % this gives you indices to which group the points belong

figure
hold on
for i = 1:N
    plot3(x(idx==i),y(idx==i),z(idx==i),'.')
end

[Valerie Cala]

Thank you so much :3