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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2015/07/10 09:42:04 UTC
[jira] [Resolved] (SPARK-3219) K-Means clusterer should support
Bregman distance functions
[ https://issues.apache.org/jira/browse/SPARK-3219?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-3219.
------------------------------
Resolution: Won't Fix
> K-Means clusterer should support Bregman distance functions
> -----------------------------------------------------------
>
> Key: SPARK-3219
> URL: https://issues.apache.org/jira/browse/SPARK-3219
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Derrick Burns
> Assignee: Derrick Burns
> Labels: clustering
>
> 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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