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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