Hi, Deb.
Thanks for your idea to use ALS for PLSA training. I discussed it with our
engineers and it seems it's better to use EM. We have the following points:
1. We have some doubts that ALS is applicable to the problem. By its
definition, PLSA is a matrix decomposition with respect to Kullback–
Thanks for the pointer...
Looks like you are using EM algorithm for factorization which looks similar
to multiplicative update rules
Do you think using mllib ALS implicit feedback, you can scale the problem
further ?
We can handle L1, L2, equality and positivity constraints in ALS now...As
long
Hi, Deb.
I don't quite understand the question. PLSA is an instance of matrix
factorization problem.
If you are asking about inference algorithm, we use EM-algorithm.
Description of this approach is, for example, here:
http://www.machinelearning.ru/wiki/images/1/1f/Voron14aist.pdf
Best, Denis.
Hi Denis,
Are you using matrix factorization to generate the latent factors ?
Thanks.
Deb
On Thu, Jul 3, 2014 at 8:49 AM, Denis Turdakov wrote:
> Hello guys,
>
> We made pull request with PLSA and its modifications:
> - https://github.com/apache/spark/pull/1269
> - JIRA issue SPARK-2199
> Co
