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Posted to issues@spark.apache.org by "RJ Nowling (JIRA)" <ji...@apache.org> on 2014/08/27 15:02:58 UTC
[jira] [Commented] (SPARK-2966) Add an approximation algorithm for
hierarchical clustering to MLlib
[ https://issues.apache.org/jira/browse/SPARK-2966?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14112223#comment-14112223 ]
RJ Nowling commented on SPARK-2966:
-----------------------------------
This is a duplicate of SPARK-2429. Please see the comments on that JIRA and Spark dev list archives for community discussion on preferred approaches (divisive, not agglomerative clustering).
> Add an approximation algorithm for hierarchical clustering to MLlib
> -------------------------------------------------------------------
>
> Key: SPARK-2966
> URL: https://issues.apache.org/jira/browse/SPARK-2966
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Yu Ishikawa
> Priority: Minor
>
> A hierarchical clustering algorithm is a useful unsupervised learning method.
> Koga. et al. proposed highly scalable hierarchical clustering altgorithm in (1).
> I would like to implement this method.
> I suggest adding an approximate hierarchical clustering algorithm to MLlib.
> I'd like this to be assigned to me.
> h3. Reference
> # Fast agglomerative hierarchical clustering algorithm using Locality-Sensitive Hashing
> http://dl.acm.org/citation.cfm?id=1266811
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