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% Author: Sharif Shahadat | |
% Email: [email protected] | |
% Website: http://sharifshahadat.com | |
% The following code is inspired by the following paper: | |
% S.C.M. Cohen ; L.N. de Castro., "Data Clustering with Particle Swarms" | |
% Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, pp.1792-1798, 16-21 July 2006 | |
% doi: 10.1109/CEC.2006.1688524 | |
% URL: http://ieeexplore.ieee.org/document/1688524/ | |
clc; clear; close; | |
%% Initialization | |
data_set=[unifrnd(0, 1, [2, 100]), unifrnd(3, 4, [2, 100])]'; | |
max_it=150; | |
vmax=0.01; | |
n_particles=3; | |
w=0.95; | |
n_cluster_per_particle=3; | |
global Y | |
phi1=0; % 1.1; | |
phi2=0; % 0.8; | |
phi3=0.005; % 0.3; | |
phi4=0.06; | |
Y = [data_set(:,1)/max(data_set(:,1)) data_set(:,2)/max(data_set(:,2))]; | |
N=max(size(data_set)); | |
x=rand(n_cluster_per_particle*n_particles,2); % usually every particle xi initialized at random | |
c = reshape(x,1, []); | |
v=vmax*(2*rand(n_particles*n_cluster_per_particle,2)-1); % at random, vi in [-vmax,vmax] | |
distYX=linspace(1e99,1e99,n_part); | |
pI=[0 0]; | |
pG=[0 0]; | |
win_counter=zeros(max(size(x)),1); | |
t=1; | |
%% Particle Swarm Clustering | |
while t < max_it | |
win_counter=zeros(n_particles*n_cluster_per_particle,1); | |
for i = 1 : N %for each data | |
for j=1:n_particles*n_cluster_per_particle | |
distYX(j) = dist(Y(i,:),x(j,:)'); | |
end | |
distMatrix(:,i)=distYX; | |
for k=1:n_cluster_per_particle | |
particle=mat2cell(distMatrix,[3 3 3], N); | |
end | |
I = find(distYX==min(distYX)); | |
f= @(x) sum(sum(bsxfun(@minus,Y,x).^2)); % distance function | |
if f(x(I,:)) < f(pI) | |
pI = x(I,:); | |
end | |
if f(x(I,:)) < f(pG) | |
pG = x(I,:); | |
end | |
v(I,:) = min(vmax, max(-vmax, v(I,:) + phi1*(pI - x(I,:)) + phi2*(pG - x(I,:)) + phi3*(Y(i,:) - x(I,:)))); | |
x(I,:)=x(I,:)+w*v(I,:); | |
end | |
w = 0.95*w; | |
% for plotting | |
plot(Y(:,1),Y(:,2),'bo'),hold on; | |
drawnow | |
plot(x(:,1),x(:,2),'k*'),hold off; | |
pause(0.1); | |
t = t + 1; | |
end | |
disp(x) |
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