GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/18992
[SPARK-19762][ML][FOLLOWUP]Add necessary comments to L2Regularization.
## What changes were proposed in this pull request?
MLlib LiR/LoR/SR always standardize the data during training to improve the
rate of convergence regardless of _standardization_ is true or false. If
_standardization_ is false, we perform reverse standardization by penalizing
each component differently to get effectively the same objective function when
the training dataset is not standardized. We should keep these comments in the
code to let developers understand how we handle it correctly.
## How was this patch tested?
Existing tests, only adding some comments in code.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yanboliang/spark SPARK-19762
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/18992.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 #18992
----
commit 88b20dc8db1a95d202faaf0eaad2c60f42ff603d
Author: Yanbo Liang <[email protected]>
Date: 2017-08-18T10:43:20Z
Add necessary comments to L2Regularization.
----
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
