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From "Erich Schubert (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-23528) Expose vital statistics of GaussianMixtureModel
Date Tue, 27 Feb 2018 22:00:00 GMT
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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