Great! On Tue, Mar 24, 2015 at 2:53 PM, roni <roni.epi...@gmail.com> wrote:
> Reza, > That SVD.v matches the H2o and R prComp (non-centered) > Thanks > -R > > On Tue, Mar 24, 2015 at 11:38 AM, Sean Owen <so...@cloudera.com> wrote: > >> (Oh sorry, I've only been thinking of TallSkinnySVD) >> >> On Tue, Mar 24, 2015 at 6:36 PM, Reza Zadeh <r...@databricks.com> wrote: >> > If you want to do a nonstandard (or uncentered) PCA, you can call >> > "computeSVD" on RowMatrix, and look at the resulting 'V' Matrix. >> > >> > That should match the output of the other two systems. >> > >> > Reza >> > >> > On Tue, Mar 24, 2015 at 3:53 AM, Sean Owen <so...@cloudera.com> wrote: >> >> >> >> Those implementations are computing an SVD of the input matrix >> >> directly, and while you generally need the columns to have mean 0, you >> >> can turn that off with the options you cite. >> >> >> >> I don't think this is possible in the MLlib implementation, since it >> >> is computing the principal components by computing eigenvectors of the >> >> covariance matrix. The means inherently don't matter either way in >> >> this computation. >> >> >> >> On Tue, Mar 24, 2015 at 6:13 AM, roni <roni.epi...@gmail.com> wrote: >> >> > I am trying to compute PCA using computePrincipalComponents. >> >> > I also computed PCA using h2o in R and R's prcomp. The answers I get >> >> > from >> >> > H2o and R's prComp (non h2o) is same when I set the options for H2o >> as >> >> > standardized=FALSE and for r's prcomp as center = false. >> >> > >> >> > How do I make sure that the settings for MLib PCA is same as I am >> using >> >> > for >> >> > H2o or prcomp. >> >> > >> >> > Thanks >> >> > Roni >> >> >> >> --------------------------------------------------------------------- >> >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> >> For additional commands, e-mail: user-h...@spark.apache.org >> >> >> > >> > >
