Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/1778#issuecomment-51180541
As a meta-question, what's the theory about what implementations should go
into Spark, and which should be external? Not everything needs to be in a
"core" library like MLlib. I know Mahout suffered mightily from adding a lot of
implementations without much regard to their use or support. I'm not suggesting
anything either way about this algorithm. If there's a working theory about
what's in and out of scope, I'd love to see it and maybe make sure that people
don't implement things for contribution that are too niche.
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