Great!
On Tue, Mar 24, 2015 at 2:53 PM, roni 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 wrote:
>
>> (Oh sorry, I've only been thinking of TallSkinnySVD)
>>
>> On Tue, Mar 24, 2015 at 6:36 PM, Reza Zadeh
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 wrote:
> (Oh sorry, I've only been thinking of TallSkinnySVD)
>
> On Tue, Mar 24, 2015 at 6:36 PM, Reza Zadeh wrote:
> > If you want to do a nonstandard (or uncentered) PCA, you ca
(Oh sorry, I've only been thinking of TallSkinnySVD)
On Tue, Mar 24, 2015 at 6:36 PM, Reza Zadeh 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.
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 wrote:
> Those implementations are computing an SVD of the i
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
