Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/20629#discussion_r181547119
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
---
@@ -64,12 +65,12 @@ class ClusteringEvaluator @Since("2.3.0")
(@Since("2.3.0") override val uid: Str
/**
* param for metric name in evaluation
- * (supports `"silhouette"` (default))
+ * (supports `"silhouette"` (default), `"kmeansCost"`)
--- End diff --
but does it make sense to introduce something which is already considered
legacy when introduced?
I think this brigs up again the question: shall we maintain a metric which
was introduced only temporary as a fallback due to the lack of better metrics?
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