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 > >> > > >
