[
https://issues.apache.org/jira/browse/SPARK-20729?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16008922#comment-16008922
]
Apache Spark commented on SPARK-20729:
--------------------------------------
User 'zero323' has created a pull request for this issue:
https://github.com/apache/spark/pull/17969
> Reduce boilerplate in Spark ML models
> -------------------------------------
>
> Key: SPARK-20729
> URL: https://issues.apache.org/jira/browse/SPARK-20729
> Project: Spark
> Issue Type: Improvement
> Components: ML, SparkR
> Affects Versions: 2.2.0
> Reporter: Maciej Szymkiewicz
>
> Currently we implement both {{predict}} and {{write.ml}} for ML wrappers,
> although R code is virtually identical and all the model specific logic is
> handled by Scala wrappers.
> Since we use S4 classes we can extract these functionalities into separate
> traits.
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
