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From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-8484) Add TrainValidationSplit to ml.tuning
Date Fri, 19 Jun 2015 17:29:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-8484?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiangrui Meng updated SPARK-8484:
---------------------------------
    Assignee:     (was: Xiangrui Meng)

> Add TrainValidationSplit to ml.tuning
> -------------------------------------
>
>                 Key: SPARK-8484
>                 URL: https://issues.apache.org/jira/browse/SPARK-8484
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: Xiangrui Meng
>
> Add TrainValidationSplit for hyper-parameter tuning. It randomly splits the input dataset
into train and validation and use evaluation metric on the validation set to select the best
model. It should be similar to CrossValidator, but simpler and less expensive.



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