[jira] [Created] (SPARK-3219) K-Means clusterer should support Bregman distance metrics

["Derrick Burns (JIRA)" <ji...@apache.org>]

Derrick Burns created SPARK-3219:
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             Summary: K-Means clusterer should support Bregman distance metrics
                 Key: SPARK-3219
                 URL: https://issues.apache.org/jira/browse/SPARK-3219
             Project: Spark
          Issue Type: Improvement
          Components: MLlib
            Reporter: Derrick Burns


The K-Means clusterer supports the Euclidean distance metric.  However, it is rather straightforward to support Bregman (http://machinelearning.wustl.edu/mlpapers/paper_files/BanerjeeMDG05.pdf) distance functions which would increase the utility of the clusterer tremendously.

I have modified the clusterer to support pluggable distance functions.  However, I notice that there are hundreds of outstanding pull requests.  If someone is willing to work with me to sponsor the work through the process, I will create a pull request.  Otherwise, I will just keep my own fork.



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