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Posted to issues@spark.apache.org by "zhengruifeng (Jira)" <ji...@apache.org> on 2019/09/17 09:05:00 UTC

[jira] [Created] (SPARK-29118) Avoid redundant computation in GMM.transform

zhengruifeng created SPARK-29118:
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             Summary: Avoid redundant computation in GMM.transform
                 Key: SPARK-29118
                 URL: https://issues.apache.org/jira/browse/SPARK-29118
             Project: Spark
          Issue Type: Improvement
          Components: ML
    Affects Versions: 3.0.0
            Reporter: zhengruifeng


In SPARK-27944, the computation for output columns with empty name is skipped.

Now, I find that we can furthermore optimize GMM.transform by directly obtaining the prediction(double) from its probabilty prediction(vector), like what ProbabilisticClassificationModel and ClassificationModel do.



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