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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/04/13 03:13:25 UTC

[jira] [Updated] (SPARK-14084) Parallel training jobs in model selection

     [ https://issues.apache.org/jira/browse/SPARK-14084?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley updated SPARK-14084:
--------------------------------------
    Target Version/s: 2.1.0  (was: 2.0.0)

> Parallel training jobs in model selection
> -----------------------------------------
>
>                 Key: SPARK-14084
>                 URL: https://issues.apache.org/jira/browse/SPARK-14084
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>    Affects Versions: 2.0.0
>            Reporter: Xiangrui Meng
>
> In CrossValidator and TrainValidationSplit, we run training jobs one by one. If users have a big cluster, they might see speed-ups if we parallelize the job submission on the driver. The trade-off is that we might need to make multiple copies of the training data, which could be expensive. It is worth testing and figure out the best way to implement it.



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