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https://issues.apache.org/jira/browse/SPARK-1406?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13964638#comment-13964638
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Sean Owen commented on SPARK-1406:
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Yes I understand transformations can be described in PMML. Do you mean parsing
a transformation described in PMML and implementing the transformation? Yes
that goes hand in hand with supporting import of a model in general.
I would merely suggest this is a step that comes after several others in order
of priority, like:
- implementing feature transformations in the abstract in the code base,
separately from the idea of PMML
- implementing some form of model import via JPMML
- implementing more functional in the Model classes to give a reason to want to
import an external model into MLlib
... and to me this is less useful at this point than export too. I say this
because the power of MLlib/Spark right now is perceived to be model building,
making it more producer than consumer at this stage.
> PMML model evaluation support via MLib
> --------------------------------------
>
> Key: SPARK-1406
> URL: https://issues.apache.org/jira/browse/SPARK-1406
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Thomas Darimont
>
> It would be useful if spark would provide support the evaluation of PMML
> models (http://www.dmg.org/v4-2/GeneralStructure.html).
> This would allow to use analytical models that were created with a
> statistical modeling tool like R, SAS, SPSS, etc. with Spark (MLib) which
> would perform the actual model evaluation for a given input tuple. The PMML
> model would then just contain the "parameterization" of an analytical model.
> Other projects like JPMML-Evaluator do a similar thing.
> https://github.com/jpmml/jpmml/tree/master/pmml-evaluator
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