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https://issues.apache.org/jira/browse/SPARK-5114?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14483335#comment-14483335
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Peter Rudenko commented on SPARK-5114:
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+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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