Till Rohrmann created FLINK-1727:
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Summary: Add decision tree to machine learning library
Key: FLINK-1727
URL: https://issues.apache.org/jira/browse/FLINK-1727
Project: Flink
Issue Type: Improvement
Components: Machine Learning Library
Reporter: Till Rohrmann
Decision trees are widely used for classification and regression tasks. Thus,
it would be worthwhile to add support for them to Flink's machine learning
library.
A streaming parallel decision tree learning algorithm has been proposed by
Ben-Haim and Tom-Tov [1]. This can maybe adapted to a batch use case as well.
[2] contains an overview of different techniques of how to scale inductive
learning algorithms up. A presentation of Spark's MLlib decision tree
implementation can be found in [3].
Resources:
[1] [http://www.jmlr.org/papers/volume11/ben-haim10a/ben-haim10a.pdf]
[2]
[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.46.8226&rep=rep1&type=pdf]
[3]
[http://spark-summit.org/wp-content/uploads/2014/07/Scalable-Distributed-Decision-Trees-in-Spark-Made-Das-Sparks-Talwalkar.pdf]
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