Description: K-Means algorithm accepts input amount of K then the object n data is divided into k cluster so that the obtained clustering meet: high similarity in the same cluster while in different cluster object similarity is smaller. Cluster similarity is the use of the mean of each cluster obtained by objects in a center (center of gravity) to calculate.
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kMeansCluster.m
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