Till Rohrmann created FLINK-1749:
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Summary: 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: Machine Learning Library
Reporter: Till Rohrmann
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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