If there is L1 from DB's OWLQN development, why do we need dropout
regularization ?

On Wed, Apr 15, 2015 at 8:59 PM, rakeshchalasani <[email protected]> wrote:

> GitHub user rakeshchalasani opened a pull request:
>
>     https://github.com/apache/spark/pull/5539
>
>     Add dropout regularization to logistic regression.
>
>     Right now implemented only for logistic regression wit SGD.
>
>     If everything is ok, I can add the same for LR with LBGFS as well.
>
> You can merge this pull request into a Git repository by running:
>
>     $ git pull https://github.com/rakeshchalasani/spark dropout
>
> Alternatively you can review and apply these changes as the patch at:
>
>     https://github.com/apache/spark/pull/5539.patch
>
> To close this pull request, make a commit to your master/trunk branch
> with (at least) the following in the commit message:
>
>     This closes #5539
>
> ----
> commit 16b76681808d0c84f3c63e83709c7440a1565f8d
> Author: rakeshchalasani <[email protected]>
> Date:   2015-04-16T03:46:02Z
>
>     [SPARK-6867][MLlib] Add dropout regularization to logistic regression
> with SGD.
>
>     Check JIRA https://issues.apache.org/jira/browse/SPARK-6867 for
> details.
>
>     Author: Rakesh Chalasani <[email protected]>
>
>     Add gradient with dropout and logistic regression with dropout
> regularization
>
>     Add LR dropout to examples
>
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