how to reduce dimensionality of features by usin pca?
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Now I can apply PCA in Matlab by using [coeff, score, latent, ~, explained] = pca(X);and size of X 20*20, And now my confusion begins. Should I take the first column of coeff or of score or other to get reconstructed features by pca?
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