A K-Means++ Clustering Implementation for VTK

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A K-Means++ Clustering Implementation for VTK

David Doria, “A K-Means++ Clustering Implementation for VTK“. The VTK Journal, September 2010

 

K-Means clustering is an excellent technique for clustering points when the number of clusters is known. We present a implementation (vtkKMeanClustering) of the algorithm written in a VTK context. We also implement the K-Means++ initialization method which finds the global optimum much more frequently than a naive/random initialization.

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