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https://issues.apache.org/jira/browse/SPARK-20228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15957411#comment-15957411
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Ansgar Schulze commented on SPARK-20228:
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Hi Sean, thanks for your comment!
Its not a problem that the results are not the same with the second
configuration but they are always much worse (about 20% more wrong predictions
for the test data set).
> Random Forest instable results depending on spark.executor.memory
> -----------------------------------------------------------------
>
> Key: SPARK-20228
> URL: https://issues.apache.org/jira/browse/SPARK-20228
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.1.0
> Reporter: Ansgar Schulze
>
> If I deploy a random forrest modeling with example
> spark.executor.memory 20480M
> I got another result as if i depoy the modeling with
> spark.executor.memory 6000M
> I excpected the same results but different runtimes.
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