wehub-resource-sync
37 lines
916 B
Matlab
Executable File
37 lines
916 B
Matlab
Executable File
function [label, R] = mixGaussPred(model, X)
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% Predict label and responsibility for Gaussian mixture model.
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% Input:
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% X: d x n data matrix
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% model: trained model structure outputed by the EM algirthm
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% Output:
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% label: 1 x n cluster label
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% R: k x n responsibility
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% Written by Mo Chen (sth4nth@gmail.com).
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mu = model.mu;
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Sigma = model.Sigma;
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w = model.w;
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n = size(X,2);
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k = size(mu,2);
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logRho = zeros(n,k);
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for i = 1:k
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logRho(:,i) = loggausspdf(X,mu(:,i),Sigma(:,:,i));
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end
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logRho = bsxfun(@plus,logRho,log(w));
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T = logsumexp(logRho,2);
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logR = bsxfun(@minus,logRho,T);
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R = exp(logR);
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[~,label(1,:)] = max(R,[],2);
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function y = loggausspdf(X, mu, Sigma)
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d = size(X,1);
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X = bsxfun(@minus,X,mu);
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[U,p]= chol(Sigma);
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if p ~= 0
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error('ERROR: Sigma is not PD.');
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end
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Q = U'\X;
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q = dot(Q,Q,1); % quadratic term (M distance)
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c = d*log(2*pi)+2*sum(log(diag(U))); % normalization constant
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y = -(c+q)/2; |