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From "Pallavi Palleti (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-153) Implement kmeans++ for initial cluster selection in kmeans
Date Tue, 09 Feb 2010 10:21:27 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12831391#action_12831391
] 

Pallavi Palleti commented on MAHOUT-153:
----------------------------------------

Forgot to mention. The above patch doesn't include test cases. Kindly review.

> Implement kmeans++ for initial cluster selection in kmeans
> ----------------------------------------------------------
>
>                 Key: MAHOUT-153
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-153
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Clustering
>    Affects Versions: 0.2
>         Environment: OS Independent
>            Reporter: Panagiotis Papadimitriou
>            Assignee: Ted Dunning
>             Fix For: 0.4
>
>         Attachments: Mahout-153.patch
>
>   Original Estimate: 336h
>  Remaining Estimate: 336h
>
> The current implementation of k-means includes the following algorithms for initial cluster
selection (seed selection): 1) random selection of k points, 2) use of canopy clusters.
> I plan to implement k-means++. The details of the algorithm are available here: http://www.stanford.edu/~darthur/kMeansPlusPlus.pdf.
> Design Outline: I will create an abstract class SeedGenerator and a subclass KMeansPlusPlusSeedGenerator.
The existing class RandomSeedGenerator will become a subclass of SeedGenerator.

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