Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/15593#discussion_r87501621
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -489,13 +485,14 @@ class LogisticRegression @Since("1.2.0") (
val initialCoefWithInterceptArray =
initialCoefficientsWithIntercept.toArray
--- End diff --
It's harder to think about we are using column major in MLOR, and not
consistent with the rest of linear models. Do you think we can still use row
major as much as possible so we don't need to touch code here, and only do the
column major thing in `LogisticAggregator` internally, and when `gradient` of
`LogisticAggregator` is called, we convert it back from column major to row
major?
---
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
