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https://issues.apache.org/jira/browse/SPARK-23528?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16381842#comment-16381842
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Apache Spark commented on SPARK-23528:
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User 'mgaido91' has created a pull request for this issue:
https://github.com/apache/spark/pull/20701
> Expose vital statistics of GaussianMixtureModel
> -----------------------------------------------
>
> Key: SPARK-23528
> URL: https://issues.apache.org/jira/browse/SPARK-23528
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.2.1
> Reporter: Erich Schubert
> Priority: Minor
>
> Spark ML should expose vital statistics of the GMM model:
> * *Number of iterations* (actual, not max) until the tolerance threshold was
> hit: we can set a maximum, but how do we know the limit was large enough, and
> how many iterations it really took?
> * Final *log likelihood* of the model: if we run multiple times with
> different starting conditions, how do we know which run converged to the
> better fit?
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