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https://issues.apache.org/jira/browse/SPARK-3702?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630453#comment-14630453
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Alexander Ulanov commented on SPARK-3702:
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[~josephkb] Hi, Joseph! Do you plan to add support for multivariate regression?
I need this for multi-layer perceptron. Multivariate regression interface might
be useful for other tasks. I've added an issue
https://issues.apache.org/jira/browse/SPARK-9120. Also I wonder if you plan to
add integer array parameters: https://issues.apache.org/jira/browse/SPARK-9118.
Both seems to be relatively easy to implement, the question is do you plan to
merge these features in the near future?
> Standardize MLlib classes for learners, models
> ----------------------------------------------
>
> Key: SPARK-3702
> URL: https://issues.apache.org/jira/browse/SPARK-3702
> Project: Spark
> Issue Type: Sub-task
> Components: MLlib
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
> Priority: Critical
>
> Summary: Create a class hierarchy for learning algorithms and the models
> those algorithms produce.
> This is a super-task of several sub-tasks (but JIRA does not allow subtasks
> of subtasks). See the "requires" links below for subtasks.
> Goals:
> * give intuitive structure to API, both for developers and for generated
> documentation
> * support meta-algorithms (e.g., boosting)
> * support generic functionality (e.g., evaluation)
> * reduce code duplication across classes
> [Design doc for class hierarchy |
> https://docs.google.com/document/d/1BH9el33kBX8JiDdgUJXdLW14CA2qhTCWIG46eXZVoJs]
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