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https://issues.apache.org/jira/browse/SPARK-8547?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15195682#comment-15195682
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Nan Zhu commented on SPARK-8547:
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FYI, we released a solution to integrate XGBoost with Spark directly
http://dmlc.ml/2016/03/14/xgboost4j-portable-distributed-xgboost-in-spark-flink-and-dataflow.html
> xgboost exploration
> -------------------
>
> Key: SPARK-8547
> URL: https://issues.apache.org/jira/browse/SPARK-8547
> Project: Spark
> Issue Type: New Feature
> Components: ML, MLlib
> Reporter: Joseph K. Bradley
>
> There has been quite a bit of excitement around xgboost:
> [https://github.com/dmlc/xgboost]
> It improves the parallelism of boosting by mixing boosting and bagging (where
> bagging makes the algorithm more parallel).
> It would worth exploring implementing this within MLlib (probably as a new
> algorithm).
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