[
https://issues.apache.org/jira/browse/SPARK-10097?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley resolved SPARK-10097.
---------------------------------------
Resolution: Fixed
Fix Version/s: 1.5.0
Issue resolved by pull request 8290
[https://github.com/apache/spark/pull/8290]
> ML Evaluator should indicate if metric should be maximized or minimized
> -----------------------------------------------------------------------
>
> Key: SPARK-10097
> URL: https://issues.apache.org/jira/browse/SPARK-10097
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Joseph K. Bradley
> Assignee: Feynman Liang
> Fix For: 1.5.0
>
>
> ML Evaluator currently requires that metrics be maximized (bigger is better).
> That is counterintuitive for some metrics. Currently, we hackily negate
> some metrics in RegressionEvaluator, which is weird. Instead, we should:
> * Return the metric as expected (e.g., "rmse" should return RMSE, not its
> negation).
> * Provide an indicator of whether the metric should be maximized or minimized.
> Model selection algorithms can use the indicator as needed.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
