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From "Till Rohrmann (JIRA)" <j...@apache.org>
Subject [jira] [Created] (FLINK-1728) Add random forest ensemble method to machine learning library
Date Wed, 18 Mar 2015 13:52:39 GMT
Till Rohrmann created FLINK-1728:
------------------------------------

             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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