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https://issues.apache.org/jira/browse/SPARK-8402?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-8402:
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    Assignee: Meethu Mathew  (was: Apache Spark)

> DP means clustering 
> --------------------
>
>                 Key: SPARK-8402
>                 URL: https://issues.apache.org/jira/browse/SPARK-8402
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Meethu Mathew
>            Assignee: Meethu Mathew
>              Labels: features
>
> At present, all the clustering algorithms in MLlib require the number of 
> clusters to be specified in advance. 
> The Dirichlet process (DP) is a popular non-parametric Bayesian mixture model 
> that allows for flexible clustering of data without having to specify apriori 
> the number of clusters. 
> DP means is a non-parametric clustering algorithm that uses a scale parameter 
> 'lambda' to control the creation of new clusters["Revisiting k-means: New 
> Algorithms via Bayesian Nonparametrics" by Brian Kulis, Michael I. Jordan].
> We have followed the distributed implementation of DP means which has been 
> proposed in the paper titled "MLbase: Distributed Machine Learning Made Easy" 
> by Xinghao Pan, Evan R. Sparks, Andre Wibisono.



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