Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/16654
Existing metrics (WSSSE,Loglikelihood) are relevant to detail of algorithm.
Computation of WSSSE for KMeans/BisectKMeans use the average vectors as the
centers, but for KMedoids the medoids, other than averages, should be used. If
we use the same logic in KMeans to compute the WSSSE for KMedoids, I think it
will be a mistake.
And I found that some supervised algorithms support evaluate method in
models: LiR,LoR,GLR.
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