Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/16654
@srowen I think I had not clarify my thoughts. WSSSE and Loglikelihood are
algorithm-specific metrics.
For example:
WSSSE dont make sense for clustering algorithms like DBSCAN,
GMM's Loglikelihood is even different from MixtureModels of other
distribution: Given a RDD[Int] representing clusterID or RDD[Array[Double]]
representing cluster probability distribution, we can not design a general
method to compute the Loglikelihood.
Some general clustering metrics are listed in
http://scikit-learn.org/stable/modules/classes.html#module-sklearn.metrics.cluster,
but wssse and loglikelihood are not in it.
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