Hi.
As far as I know, sparse data is not mean-centered.
I don't know the poster of the answer, but I don't think the claim is true.
Anyway, our documentation doesn't seem to be sufficient :-/
Best,
Andy
On 01/12/2013 06:19 PM, Neva Cherniavsky wrote:
Hello,
I'm using RandomizedPCA to get the first few principal components of a
large sparse matrix. However, the matrix isn't mean-centered to begin
with. If I call RandomizedPCA with the full version of the matrix,
the function will mean-center it before running the SVD. What happens
with a sparse matrix? I read through the code and it doesn't appear
to mean-center.
I ask because the last answer here
<http://stackoverflow.com/questions/13425947/principal-component-analysis-pca-on-huge-sparse-dataset> seems
to imply that the mean is subtracted off on-the-fly for the sparse
version; but if so, I don't see where that's happening, and I get
different answers when running the code as a full versus sparse matrix.
Thanks for any insight,
Neva
--
Neva Cherniavsky, Ph.D.
Broad Institute of MIT and Harvard
7 Cambridge Center Room 6047-C
Cambridge, MA 02142
+1-617-714-7817
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