wehub-resource-sync
34 lines
833 B
Matlab
Executable File
34 lines
833 B
Matlab
Executable File
function [W, Z, mu, mse] = pcaEm(X, m)
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% Perform EM-like algorithm for PCA (by Sam Roweis).
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% Input:
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% X: d x n data matrix
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% m: dimension of target space
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% Output:
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% W: d x m weight matrix
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% Z: m x n projected data matrix
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% mu: d x 1 mean vector
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% mse: mean square error
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% Reference:
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% Pattern Recognition and Machine Learning by Christopher M. Bishop
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% EM algorithms for PCA and SPCA by Sam Roweis
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% Written by Mo Chen (sth4nth@gmail.com).
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d = size(X,1);
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mu = mean(X,2);
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X = bsxfun(@minus,X,mu);
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W = rand(d,m);
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tol = 1e-6;
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mse = inf;
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maxIter = 200;
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for iter = 1:maxIter
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Z = (W'*W)\(W'*X); % 12.58
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W = (X*Z')/(Z*Z'); % 12.59
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last = mse;
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E = X-W*Z;
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mse = mean(dot(E(:),E(:)));
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if abs(last-mse)<mse*tol; break; end;
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end
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fprintf('Converged in %d steps.\n',iter);
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