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https://issues.apache.org/jira/browse/SPARK-1547?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14149918#comment-14149918
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Joseph K. Bradley commented on SPARK-1547:
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[~hector.yee] I strongly agree about keeping ensembles general enough to work
with any weak learning algorithm. This is difficult now because of the lack of
a general class hierarchy, but that will be easier after the [current API
redesign|https://issues.apache.org/jira/browse/SPARK-1856]. Starting with
trees, and later generalizing once the new API is available, will be great.
> Add gradient boosting algorithm to MLlib
> ----------------------------------------
>
> Key: SPARK-1547
> URL: https://issues.apache.org/jira/browse/SPARK-1547
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.0.0
> Reporter: Manish Amde
> Assignee: Manish Amde
>
> This task requires adding the gradient boosting algorithm to Spark MLlib. The
> implementation needs to adapt the gradient boosting algorithm to the scalable
> tree implementation.
> The tasks involves:
> - Comparing the various tradeoffs and finalizing the algorithm before
> implementation
> - Code implementation
> - Unit tests
> - Functional tests
> - Performance tests
> - Documentation
> [Ensembles design document (Google doc) |
> https://docs.google.com/document/d/1J0Q6OP2Ggx0SOtlPgRUkwLASrAkUJw6m6EK12jRDSNg/]
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