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https://issues.apache.org/jira/browse/MAHOUT-1162?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ted Dunning resolved MAHOUT-1162.
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Resolution: Fixed
THis has been checked in.
> 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
> Fix For: 0.8
>
> Attachments: MAHOUT_1162_with_test.patch
>
>
> 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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