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https://issues.apache.org/jira/browse/FLINK-1728?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Till Rohrmann updated FLINK-1728:
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Issue Type: New Feature (was: Improvement)
> 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: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Labels: ML
>
> 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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