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https://issues.apache.org/jira/browse/SPARK-3703?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14627233#comment-14627233
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Joseph K. Bradley commented on SPARK-3703:
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Currently, none of these generic ensembles are targeted for 1.5. I definitely
want to add them at some point, but I hesitate to suggest working on them since
we have such limited time for reviewing. Improvements to existing ensembles
are higher priority right now. For that, I'd suggest one of these:
* [SPARK-6684]
* [SPARK-7674], adding stats for ensembles following the example set for linear
regression
> Ensemble learning methods
> -------------------------
>
> Key: SPARK-3703
> URL: https://issues.apache.org/jira/browse/SPARK-3703
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Joseph K. Bradley
>
> This is a general JIRA for coordinating on adding ensemble learning methods
> to MLlib. These methods include a variety of boosting and bagging
> algorithms. Below is a general design doc for ensemble methods (currently
> focused on boosting). Please comment here about general discussion and
> coordination; for comments about specific algorithms, please comment on their
> respective JIRAs.
> [Design doc for ensemble methods |
> https://docs.google.com/document/d/1J0Q6OP2Ggx0SOtlPgRUkwLASrAkUJw6m6EK12jRDSNg/]
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