Erich Schubert created SPARK-23528:
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Summary: 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
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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