GitHub user sethah opened a pull request:
https://github.com/apache/spark/pull/17426
[SPARK-17137][ML][WIP] Compress logistic regression coefficients
## What changes were proposed in this pull request?
Use the new `compressed` method on matrices to store the logistic
regression coefficients as sparse or dense - whichever is requires less memory.
Marked as WIP so we can add some performance test results. Basically, we
should see if prediction is slower because of using a sparse matrix over a
dense one. This can happen since sparse matrices do not use native BLAS
operations when computing the margins.
## How was this patch tested?
Unit tests added.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/sethah/spark SPARK-17137
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17426.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 #17426
----
commit c677696fe714be04df614877a0ee0d4f76254812
Author: sethah <seth.hendrickso...@gmail.com>
Date: 2017-03-25T04:04:55Z
compress log reg coefficients
----
---
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 infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
