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https://issues.apache.org/jira/browse/SPARK-8402?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14589392#comment-14589392
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Meethu Mathew commented on SPARK-8402:
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Could anyone please assign this ticket to me ?
> 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
> 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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