Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/KPMtools/pca_kpm.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/KPMtools/pca_kpm.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,32 @@ +function [pc_vec]=pca_kpm(features,N, method); +% PCA_KPM Compute top N principal components using eigs or svd. +% [pc_vec]=pca_kpm(features,N) +% +% features(:,i) is the i'th example - each COLUMN is an observation +% pc_vec(:,j) is the j'th basis function onto which you should project the data +% using pc_vec' * features + +[d ncases] = size(features); +fm=features-repmat(mean(features,2), 1, ncases); + + +if method==1 % d*d < d*ncases + fprintf('pca_kpm eigs\n'); + options.disp = 0; + C = cov(fm'); % d x d matrix + [pc_vec, evals] = eigs(C, N, 'LM', options); +else + % [U,D,V] = SVD(fm), U(:,i)=evec of fm fm', V(:,i) = evec of fm' fm + fprintf('pca_kpm svds\n'); + [U,D,V] = svds(fm', N); + pc_vec = V; +end + +if 0 +X = randn(5,3); +X = X-repmat(mean(X),5,1); +C = X'*X; +C2=cov(X) +[U,D,V]=svd(X); +[V2,D2]=eig(X) +end