[
https://issues.apache.org/jira/browse/SPARK-23704?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Bryan Cutler updated SPARK-23704:
---------------------------------
Component/s: PySpark
> PySpark access of individual trees in random forest is slow
> -----------------------------------------------------------
>
> Key: SPARK-23704
> URL: https://issues.apache.org/jira/browse/SPARK-23704
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Affects Versions: 2.2.1
> Environment: PySpark 2.2.1 / Windows 10
> Reporter: Julian King
> Priority: Minor
>
> Making predictions from a randomForestClassifier PySpark is much faster than
> making predictions from an individual tree contained within the .trees
> attribute.
> In fact, the model.transform call without an action is more than 10x slower
> for an individual tree vs the model.transform call for the random forest
> model.
> See
> [https://stackoverflow.com/questions/49297470/slow-individual-tree-access-for-random-forest-in-pyspark]
> for example with timing.
> Ideally:
> * Getting a prediction from a single tree should be comparable to or faster
> than getting predictions from the whole tree
> * Getting all the predictions from all the individual trees should be
> comparable in speed to getting the predictions from the random forest
>
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
