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KMeans-clustering

KNN Algorithm

Given a set of points & a positive integer K > 0 , we return K lists of points (clusters) according to the classical K-Means Algorithm

The initialization step which is done is called KNN ++

The code is improved with two accelerations proposed in the paper :

Phillips S.J. (2002) Acceleration of K-Means and Related Clustering Algorithms. In: Mount D.M., Stein C. (eds) Algorithm Engineering and Experiments. ALENEX 2002. Lecture Notes in Computer Science, vol 2409. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45643-0_13

to execute

Mark run in the target of build.xml & simply execute the ant

experimentation

Given this set of points :

kMean

We obtain :

kMean_after

And after a (very harsh) benchmark of tests :

122142_55111ms

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