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Posted to issues@spark.apache.org by "Sean R. Owen (Jira)" <ji...@apache.org> on 2021/08/24 12:39:00 UTC
[jira] [Updated] (SPARK-34415) Use randomization as a possibly
better technique than grid search in optimizing hyperparameters
[ https://issues.apache.org/jira/browse/SPARK-34415?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean R. Owen updated SPARK-34415:
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Labels: (was: pull-request-available)
> Use randomization as a possibly better technique than grid search in optimizing hyperparameters
> -----------------------------------------------------------------------------------------------
>
> Key: SPARK-34415
> URL: https://issues.apache.org/jira/browse/SPARK-34415
> Project: Spark
> Issue Type: New Feature
> Components: ML, MLlib
> Affects Versions: 3.0.1
> Reporter: Phillip Henry
> Assignee: Phillip Henry
> Priority: Minor
> Fix For: 3.2.0
>
>
> Randomization can be a more effective techinique than a grid search in finding optimal hyperparameters since min/max points can fall between the grid lines and never be found. Randomisation is not so restricted although the probability of finding minima/maxima is dependent on the number of attempts.
> Alice Zheng has an accessible description on how this technique works at [https://www.oreilly.com/library/view/evaluating-machine-learning/9781492048756/ch04.html]
> (Note that I have a PR for this work outstanding at [https://github.com/apache/spark/pull/31535] )
>
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