Github user srowen commented on the issue:
https://github.com/apache/spark/pull/16654
I agree that clustering metrics are different from classification metrics,
but that doesn't mean they can't have some common abstraction -- they're
applied to a model and data set and produce a number. It's true that not every
evaluation metric makes sense for every model, but that's not a problem per se.
Why wouldn't WSSSE make sense for DBSCAN?
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