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https://issues.apache.org/jira/browse/SPARK-5114?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-5114:
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Description:
Pipelines can currently contain Estimators and Transformers.
Question for debate: Should Pipelines be able to contain Evaluators?
Pros:
* Schema check: Evaluators take input datasets with particular schema, which
should perhaps be checked before running a Pipeline.
* Intermediate results:
** If a Transformer removes a column (which is not done by built-in
Transformers currently but might be reasonable in the future), then the user
can never evaluate that column. (However, users could keep all columns around.)
** If users have to evaluate after running a Pipeline, then each evaluated
column may have to be re-materialized.
Cons:
* API: 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.
was:
Pipelines can currently contain Estimators and Transformers.
Question for debate: Should Pipelines be able to contain Evaluators?
Pros:
* Schema check: Evaluators take input datasets with particular schema, which
should perhaps be checked before running a Pipeline.
* Intermediate results:
** If a Transformer removes a column (which is not done by built-in
Transformers currently but might be reasonable in the future), then the user
can never evaluate that column. (However, users could keep all columns around.)
** If users have to evaluate after running a Pipeline, then each evaluated
column may have to be re-materialized.
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.
> 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:
> * Schema check: Evaluators take input datasets with particular schema, which
> should perhaps be checked before running a Pipeline.
> * Intermediate results:
> ** If a Transformer removes a column (which is not done by built-in
> Transformers currently but might be reasonable in the future), then the user
> can never evaluate that column. (However, users could keep all columns
> around.)
> ** If users have to evaluate after running a Pipeline, then each evaluated
> column may have to be re-materialized.
> Cons:
> * API: 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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