KMeansClustering

Various K Means Clustering methods in Java

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BSD 
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28 KB
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DEVELOPED BY:
KMeansClustering Team
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Home \ Development \ Libraries
KMeansClustering is a free, open-source and Java based library that implements various methods of K Means Clustering.

One of the algorithms is Elkan K-Means Clustering, which uses triangle inequality to speed up assignment of points to their closest cluster.

K-Means KDTree Clustering is another implemented algorithm that speeds up the assignment of points to their closest cluster using a KD Tree.

Finally, the K-Means KD Forest Clustering method ca select assignments of points to their closest cluster using a forest of KD trees.

Last updated on November 1st, 2012

Runs on: Mac OS X (-)

requirements

#K Means Clustering #Clustering algorithm #K Means cluster #K Means #Cluster #Clustering #algorithm

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