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https://issues.apache.org/jira/browse/SPARK-7409?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-7409.
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Resolution: Incomplete
> Designing multilabel abstractions for spark.ml
> ----------------------------------------------
>
> Key: SPARK-7409
> URL: https://issues.apache.org/jira/browse/SPARK-7409
> Project: Spark
> Issue Type: Brainstorming
> Components: ML
> Reporter: Joseph K. Bradley
> Priority: Major
> Labels: bulk-closed
>
> This JIRA is for discussing how to support multi-label prediction in the
> Pipelines API (spark.ml package). Some issues to figure out are:
> * Should there be abstractions?
> ** How should they relate to the existing single-label abstractions:
> Predictor, Classifier, Regressor?
> ** How much code sharing can the abstractions provide?
> * How should we support a mix of categorical and real-valued labels?
> * How do we support structure among the labels? There could be no known
> structure, a graphical structure, a chain structure, etc., depending on the
> application/model.
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