Github user yanboliang commented on the issue:
https://github.com/apache/spark/pull/17360
@sethah I left some questions on
[SPARK-17136](https://issues.apache.org/jira/browse/SPARK-17136). I think the
main question we should figure out is whether we still expose the optimizer
params as the estimator params after SPARK-17136. I'm more prefer to keep these
params in estimators, make the optimizer layer as an internal API, and users
can register their own optimizer implementation such as the data source
support. Since I found this is more aligned with the original [ML pipeline
design](https://docs.google.com/document/d/1rVwXRjWKfIb-7PI6b86ipytwbUH7irSNLF1_6dLmh8o/edit#)
which stores params outside a pipeline component.
So I think this PR is not conflict with SPARK-17136 and can work parallel.
I'm also open to hear your thoughts. Thanks!
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