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https://issues.apache.org/jira/browse/SPARK-2429?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14357389#comment-14357389
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RJ Nowling commented on SPARK-2429:
-----------------------------------
[~josephkb] I think it would be great to get the new implementation into Spark
but we need a champion for it. [[email protected]] did some great work,
and I've been trying to shepard the work but we need a committer who wants to
bring it in. If you want to do that, then I can step back and let you and
[[email protected]] bring this across the finish line.
> Hierarchical Implementation of KMeans
> -------------------------------------
>
> Key: SPARK-2429
> URL: https://issues.apache.org/jira/browse/SPARK-2429
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: RJ Nowling
> Assignee: Yu Ishikawa
> Priority: Minor
> Labels: clustering
> Attachments: 2014-10-20_divisive-hierarchical-clustering.pdf, The
> Result of Benchmarking a Hierarchical Clustering.pdf,
> benchmark-result.2014-10-29.html, benchmark2.html
>
>
> Hierarchical clustering algorithms are widely used and would make a nice
> addition to MLlib. Clustering algorithms are useful for determining
> relationships between clusters as well as offering faster assignment.
> Discussion on the dev list suggested the following possible approaches:
> * Top down, recursive application of KMeans
> * Reuse DecisionTree implementation with different objective function
> * Hierarchical SVD
> It was also suggested that support for distance metrics other than Euclidean
> such as negative dot or cosine are necessary.
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