Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/13617
@JeremyNixon Thanks for your thoughts. I agree this should get in, but
want to make sure the priorities are clear.
With respect to examples of improvements, I really meant either (a)
research papers showing the importance or (b) industry use cases. One can
always construct examples where an algorithm is helpful, and I agree that
feature engineering is likely a good use case. But references are very helpful
for guidance.
+1 for separating the activation functions out into another PR
About scaling: I'd say this should mimic LinearRegression's standardization
API.
---
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]
