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

Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2014/10/28 08:10:34 UTC

[jira] [Commented] (SPARK-4111) [MLlib] Implement regression model evaluation metrics

    [ https://issues.apache.org/jira/browse/SPARK-4111?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14186496#comment-14186496 ] 

Sean Owen commented on SPARK-4111:
----------------------------------

Is this more than just MAE / RMSE / R2? It might be handy to have a little utility class for these although they're almost one-liners already.

> [MLlib] Implement regression model evaluation metrics
> -----------------------------------------------------
>
>                 Key: SPARK-4111
>                 URL: https://issues.apache.org/jira/browse/SPARK-4111
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>    Affects Versions: 1.2.0
>            Reporter: Yanbo Liang
>
> Supervised machine learning include classification and regression. There is classification metrics (BinaryClassificationMetrics) in MLlib, we also need regression metrics to evaluate the regression model and tunning parameter.



--
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