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Posted to issues@flink.apache.org by "Chesnay Schepler (JIRA)" <ji...@apache.org> on 2019/02/28 22:58:09 UTC
[jira] [Closed] (FLINK-1749) Add Boosting algorithm for ensemble
learning to machine learning library
[ https://issues.apache.org/jira/browse/FLINK-1749?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Chesnay Schepler closed FLINK-1749.
-----------------------------------
Resolution: Won't Do
Closing since flink-ml is effectively frozen.
> Add Boosting algorithm for ensemble learning to machine learning library
> ------------------------------------------------------------------------
>
> Key: FLINK-1749
> URL: https://issues.apache.org/jira/browse/FLINK-1749
> Project: Flink
> Issue Type: New Feature
> Components: Library / Machine Learning
> Reporter: Till Rohrmann
> Priority: Major
> Labels: ML
>
> Boosting [1] can help to create strong learners from an ensemble of weak learners and thus improving its performance. Widely used boosting algorithms are AdaBoost [2] and LogitBoost [3]. The work of I. Palit and C. K. Reddy [4] investigates how boosting can be efficiently realised in a distributed setting.
> Resources:
> [1] [http://en.wikipedia.org/wiki/Boosting_%28machine_learning%29]
> [2] [http://en.wikipedia.org/wiki/AdaBoost]
> [3] [http://en.wikipedia.org/wiki/LogitBoost]
> [4] [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6035709]
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