Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/13617
As per @avulanov's [comment on
SPARK-15581](https://issues.apache.org/jira/browse/SPARK-15581?focusedCommentId=15325377&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15325377),
if we do indeed plan to add the "essentials" for DL to Spark (e.g. MLP, CNN,
autencoder), then MLPR seems like it should be in there too. Especially since
this PR is mostly "wrapper" code to expose the DF-based API, example, and
tests. The core changes are minimal and open up a powerful model for users - I
guess what I am saying is the "risk vs reward" here seems good.
Also, FWIW this is in scikit-learn dev
(http://scikit-learn.org/dev/modules/neural_networks_supervised.html)
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