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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-19357) Parallel Model Evaluation for ML Tuning
Date Thu, 02 Feb 2017 00:05:51 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19357?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-19357:
------------------------------------

    Assignee:     (was: Apache Spark)

> Parallel Model Evaluation for ML Tuning
> ---------------------------------------
>
>                 Key: SPARK-19357
>                 URL: https://issues.apache.org/jira/browse/SPARK-19357
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML
>            Reporter: Bryan Cutler
>
> This is a first step of the parent task of Optimizations for ML Pipeline Tuning to perform
model evaluation in parallel.  A simple approach is to naively evaluate with a possible parameter
to control the level of parallelism.  There are some concerns with this:
> * excessive caching of datasets
> * what to set as the default value for level of parallelism.  1 will evaluate all models
in serial, as is done currently. Higher values could lead to excessive caching.



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