Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/9169#issuecomment-149473946
To give you an idea of how prevalent the `@Experimental` tag is ...
- Streaming: 6
- Core: 29
- SQL: 42
- ML: 93
- MLlib: 95
Worth cleaning up MLlib I think; does anyone have particular opinions about
applying similar logic to ML (anything from <= 1.4.0 is no longer Experimental,
in general)? There would be much less to remove there.
Or, core and streaming? I could keep going to swat this in one logical
change, but don't feel strongly enough to push on it. MLlib is the most
important part to update.
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