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memory pca vs pcacov

조회 수: 9(최근 30일)
Hans van der Horn
Hans van der Horn 2 Nov 2020
Dear all,
I'm running a pca on a large matrix (33*500,000) and with pcacov I get a memory error, but pca gives me no trouble. Could anyone explain this to me? Is the matrix somehow being reduced before computing the covariance matrix in pca?
Thanks!
Best
Hans

답변(3개)

Hiro
Hiro 2 Nov 2020
In PCA, your matrix (p x q) will be once converted into the variance-covariance matrix (q x q).
This would reqiure huge memory comsumption. Meanwhile, pcacov accepts a variance-covariance matrix as an input and, therefore the argument (input) should be a square matrix though.
As for big data anaysis, you may want to use tall array - this can be a solution.

Hans van der Horn
Hans van der Horn 2 Nov 2020
Dear Hiro,
Thanks for your answer. If I compute cov(my matrix) to get the input for pcacov I run out of memory. However, if I run the pca function on my matrix. Why does the pca.m not get into memory problems?
Best
Hans
  댓글 수: 2
Hiro
Hiro 2 Nov 2020
I do not believe pcacov works with your matrix in the first place since the shape of your matrix is unacceptable. I do not know what the error will be like.

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Hans van der Horn
Hans van der Horn 2 Nov 2020
Dear Hiro,
The problem is that by constructing the covariance matrix Matlab runs out of memory. Why does the pca.m function not give memory problems (when I of course enter the original matrix)?
thanks!
  댓글 수: 2
Hans van der Horn
Hans van der Horn 2 Nov 2020
thanks! It's clear to me now:) I will also read the documentation for PCA (I thought pcacov also used svd..).

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