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https://issues.apache.org/jira/browse/SPARK-4259?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-4259.
----------------------------------
       Resolution: Fixed
    Fix Version/s: 1.3.0

Issue resolved by pull request 4254
[https://github.com/apache/spark/pull/4254]

> Add Power Iteration Clustering Algorithm with Gaussian Similarity Function
> --------------------------------------------------------------------------
>
>                 Key: SPARK-4259
>                 URL: https://issues.apache.org/jira/browse/SPARK-4259
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Fan Jiang
>            Assignee: Fan Jiang
>              Labels: features
>             Fix For: 1.3.0
>
>
> In recent years, power Iteration clustering has become one of the most 
> popular modern clustering algorithms. It is simple to implement, can be 
> solved efficiently by standard linear algebra software, and very often 
> outperforms traditional clustering algorithms such as the k-means algorithm.
> Power iteration clustering is a scalable and efficient algorithm for 
> clustering points given pointwise mutual affinity values.  Internally the 
> algorithm:
> computes the Gaussian distance between all pairs of points and represents 
> these distances in an Affinity Matrix
> calculates a Normalized Affinity Matrix
> calculates the principal eigenvalue and eigenvector
> Clusters each of the input points according to their principal eigenvector 
> component value
> Details of this algorithm are found within [Power Iteration Clustering, Lin 
> and Cohen]{www.icml2010.org/papers/387.pdf}



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