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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | % VL_DEMO_GMM_2D_RAND Demonstrate clustering points with a GMM
%% Create a random set of points
numPoints = 5000 ;
dimension = 2 ;
numClusters = 20 ;
data = rand(dimension, numPoints) ;
%% Learn a GMM: fit the points at maximum likelihood
vl_twister('state',0) ;
[means, covariances, priors] = ...
vl_gmm(data, numClusters, ...
'MaxNumIterations', 1000, ...
'Verbose') ;
figure(1) ; clf ; hold on
plot(data(1,:),data(2,:),'r.');
for i=1:numClusters
vl_plotframe([means(:,i)' covariances(1,i) 0 covariances(2,i)], ...
'Color','blue','LineWidth',2);
end
title('GMM: Gaussian mixture initialized choosing random points') ;
axis equal ; axis off ;
vl_demo_print('gmm_2d_rand',0.6);
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