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Posted to dev@flink.apache.org by "Till Rohrmann (JIRA)" <ji...@apache.org> on 2015/03/18 14:52:39 UTC
[jira] [Created] (FLINK-1728) Add random forest ensemble method to
machine learning library
Till Rohrmann created FLINK-1728:
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Summary: Add random forest ensemble method to machine learning library
Key: FLINK-1728
URL: https://issues.apache.org/jira/browse/FLINK-1728
Project: Flink
Issue Type: Improvement
Components: Machine Learning Library
Reporter: Till Rohrmann
Random forests are a well-established mean to mitigate the decision trees' weakness of overfitting. Therefore this would be a valuable contribution to Flink's machine learning library.
Google [1] describes some of the techniques they used to do ensemble learning of MapReduce. This could be helpful while implementing a distributed random forest.
Resources:
[1] http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36296.pdf
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