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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/08/03 22:02:04 UTC

[jira] [Updated] (SPARK-2429) Hierarchical Implementation of KMeans

     [ https://issues.apache.org/jira/browse/SPARK-2429?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley updated SPARK-2429:
-------------------------------------
    Target Version/s: 1.6.0  (was: 1.5.0)

> 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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