[jira] [Commented] (SPARK-20723) Random Forest Classifier should expose intermediateRDDStorageLevel similar to ALS

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-20723?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16009171#comment-16009171 ] 

Apache Spark commented on SPARK-20723:
--------------------------------------

User 'phatak-dev' has created a pull request for this issue:
https://github.com/apache/spark/pull/17972

> Random Forest Classifier should expose intermediateRDDStorageLevel similar to ALS
> ---------------------------------------------------------------------------------
>
>                 Key: SPARK-20723
>                 URL: https://issues.apache.org/jira/browse/SPARK-20723
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>    Affects Versions: 2.3.0
>            Reporter: madhukara phatak
>            Priority: Minor
>
> Currently Random Forest implementation cache as the intermediatery data using *MEMORY_AND_DISK* storage level. This creates issues in low memory scenarios. So we should expose an expert param *intermediateStorageLevel* which allows user to customise the storage level. This is similar to als options like specified in below jira
> https://issues.apache.org/jira/browse/SPARK-14412



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