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Posted to issues@spark.apache.org by "Peter Rudenko (JIRA)" <ji...@apache.org> on 2015/04/08 16:14:12 UTC
[jira] [Comment Edited] (SPARK-5114) Should Evaluator be a
PipelineStage
[ https://issues.apache.org/jira/browse/SPARK-5114?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14483335#comment-14483335 ]
Peter Rudenko edited comment on SPARK-5114 at 4/8/15 2:14 PM:
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+1 for should. For my use case (create pipeline from config file, sometimes there is need to do evaluation with several custom metrics (e.g. gini norm, etc.), sometimes there's no need to do evaluation, it would be done on other part of the system). Would be more flexible for if evaluator would be a part of pipeline.
was (Author: prudenko):
+1 for should. For my use case (create pipeline from config file, sometimes there is need to do evaluation with custom metrics (e.g. gini norm, etc.), sometimes there's no need to do evaluation, it would be done on other part of the system). Would be more flexible for if evaluator would be a part of pipeline.
> Should Evaluator be a PipelineStage
> -----------------------------------
>
> Key: SPARK-5114
> URL: https://issues.apache.org/jira/browse/SPARK-5114
> Project: Spark
> Issue Type: Question
> Components: ML
> Affects Versions: 1.2.0
> Reporter: Joseph K. Bradley
>
> Pipelines can currently contain Estimators and Transformers.
> Question for debate: Should Pipelines be able to contain Evaluators?
> Pros:
> * Evaluators take input datasets with particular schema, which should perhaps be checked before running a Pipeline.
> Cons:
> * Evaluators do not transform datasets. They produce a scalar (or a few values), which makes it hard to say how they fit into a Pipeline or a PipelineModel.
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