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

Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/07/03 00:01:05 UTC

[jira] [Updated] (SPARK-3382) GradientDescent convergence tolerance

     [ https://issues.apache.org/jira/browse/SPARK-3382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley updated SPARK-3382:
-------------------------------------
    Assignee: Kai Sasaki

> GradientDescent convergence tolerance
> -------------------------------------
>
>                 Key: SPARK-3382
>                 URL: https://issues.apache.org/jira/browse/SPARK-3382
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>    Affects Versions: 1.1.0
>            Reporter: Joseph K. Bradley
>            Assignee: Kai Sasaki
>            Priority: Minor
>             Fix For: 1.5.0
>
>
> GradientDescent should support a convergence tolerance setting.  In general, for optimization, convergence tolerance should be preferred over a limit on the number of iterations since it is a somewhat data-adaptive or data-specific convergence criterion.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

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