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From "Dan Filimon (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (MAHOUT-1162) Adding BallKMeans and StreamingKMeans classes
Date Fri, 29 Mar 2013 13:37:16 GMT

     [ https://issues.apache.org/jira/browse/MAHOUT-1162?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Dan Filimon updated MAHOUT-1162:
--------------------------------

    Attachment:     (was: MAHOUT_1162.patch)
    
> Adding BallKMeans and StreamingKMeans classes
> ---------------------------------------------
>
>                 Key: MAHOUT-1162
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1162
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Clustering
>    Affects Versions: 0.8
>            Reporter: Dan Filimon
>
> Adding BallKMeans and StreamingKMeans clustering algorithms.
> These both implement Iterable<Centroid> and thus return the resulting centroids
after clustering.
> BallKMeans implements:
> - kmeans++ initialization;
> - a normal k-means pass;
> - a trimming threshold so that points that are too far from the cluster they were assigned
to are not used in the new centroid computation.
> StreamingKMeans implements [http://books.nips.cc/papers/files/nips24/NIPS2011_1271.pdf]:
> - an online clustering algorithm that takes each point into account one by one
>   - for each point, it computes the distance to the nearest existing cluster
>   - if the distance is greater than a set distanceCutoff, it will create a new cluster,
otherwise it might be added to the cluster it's closest to (proportional to the value of the
distance / distanceCutoff)
>   - if there are too many clusters, the clusters will be *collapsed* (the same method
gets called, but the number of clusters is re-adjusted)
> - finally, *about as many* clusters as requested are returned (not precise!); this represents
a sketch of the original points.

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