How to create a multivariate gaussian mixture model??
4 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
[counts,binLocations] = imhist(X);
stem(binLocations, counts, 'MarkerSize', 1 );
xlim([-1 1]);
% inital kmeans step used to initialize EM
K = 2; % number of mixtures/clusters
rng('default');
cInd = kmeans(X(:), K,'MaxIter', 75536);
% fit a GMM model
options = statset('MaxIter', 75536);
gmm = fitgmdist(X(:), K,'Start',cInd,'CovarianceType','diagonal','Regularize',1e-5,'Options',options);
The piece of code shows how to fit a GMM to a univariate Gaussian distribution. X is and image. But how this can be extended to create a a 2 component 2 dimensional multivariate GMM?
1 commentaire
Sergio Cypress
le 17 Sep 2017
http://web.eecs.umich.edu/~cscott/pubs/tcem_tr.pdf this paper present EM algorithm to handle Multi GMM.
Réponses (1)
Prashant Arora
le 19 Juil 2017
Hi Akshara,
The gmdistribution function supports multivariate gaussian distributions. Check the required dimensions of mu and sigma to create a multivariate 2 dimensional 2 component distribution.
0 commentaires
Voir également
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!