You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Phillip Henry (Jira)" <ji...@apache.org> on 2021/02/10 08:49:00 UTC

[jira] [Created] (SPARK-34415) Use randomization as a possibly better technique than grid search in optimizing hyperparameters

Phillip Henry created SPARK-34415:
-------------------------------------

             Summary: 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


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] )

 



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org