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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-20723) Random Forest Classifier should expose intermediateRDDStorageLevel similar to ALS
Date Sat, 13 May 2017 06:37:04 GMT

     [ https://issues.apache.org/jira/browse/SPARK-20723?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-20723:
------------------------------------

    Assignee: Apache Spark

> 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
>            Assignee: Apache Spark
>            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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