how could I know which dimensions are the principle component? [duplicate]

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Matlab Principal Component Analysis (eigenvalues order) (2 answers)

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I use matlab's princomp function to do PCA. From my understanding, I could check the latent to decide how many dimensions I need.

[coeff, score, latent, t2] = princomp(fdata);
 cumsum(latent)./sum(latent);

And by using trainMatrix = coeff(:,1:10) (I choose the top 10 dimensions), and newData = data*trainMatrix, I could get the reduced data.

But how could I figure out which dimension is reduced and which 10 dimensions are remained?

I mean if I have 30 features, could I figure out after princomp, which 10 features (the column index of original data) I reserved?

Thanks.

Answer 1

The new dimensions correspond to a linear combination of the original dimensions, i.e each new feature is expressed in terms of all the old ones with varying weights.