wehub-resource-sync
31 lines
888 B
Matlab
Executable File
31 lines
888 B
Matlab
Executable File
function [label, Theta, w, llh] = mixGaussGb(X, opt)
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% Collapsed Gibbs sampling for Dirichlet process (infinite) Gaussian mixture model (a.k.a. DPGM).
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% This is a wrapper function which calls underlying Dirichlet process mixture model.
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% Input:
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% X: d x n data matrix
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% opt(optional): prior parameters
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% Output:
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% label: 1 x n cluster label
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% Theta: 1 x k structure of trained Gaussian components
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% w: 1 x k component weight vector
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% llh: loglikelihood
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% Written by Mo Chen (sth4nth@gmail.com).
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[d,n] = size(X);
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mu = mean(X,2);
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Xo = bsxfun(@minus,X,mu);
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s = sum(Xo(:).^2)/(d*n);
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if nargin == 1
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kappa0 = 1;
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m0 = mean(X,2);
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nu0 = d;
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S0 = s*eye(d);
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alpha0 = 1;
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else
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kappa0 = opt.kappa;
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m0 = opt.m;
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nu0 = opt.nu;
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S0 = opt.S;
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alpha0 = opt.alpha;
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end
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prior = GaussWishart(kappa0,m0,nu0,S0);
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[label, Theta, w, llh] = mixDpGb(X,alpha0,prior); |