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Posted to issues@spark.apache.org by "George Dittmar (JIRA)" <ji...@apache.org> on 2015/09/05 07:22:45 UTC
[jira] [Commented] (SPARK-9961) ML prediction abstractions should
have defaultEvaluator fields
[ https://issues.apache.org/jira/browse/SPARK-9961?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14731810#comment-14731810 ]
George Dittmar commented on SPARK-9961:
---------------------------------------
Can you expand on what you mean by Evaluator? Just looking for something to eval how good predictions are?
> ML prediction abstractions should have defaultEvaluator fields
> --------------------------------------------------------------
>
> Key: SPARK-9961
> URL: https://issues.apache.org/jira/browse/SPARK-9961
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Joseph K. Bradley
>
> Predictor and PredictionModel should have abstract defaultEvaluator methods which return Evaluators. Subclasses like Regressor, Classifier, etc. should all provide natural evaluators, set to use the correct input columns and metrics. Concrete classes may later be modified to
> The initial implementation should be marked as DeveloperApi since we may need to change the defaults later on.
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