Kmeans function
2016-08-23
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K-means algorithm accepts parameters k; prior input of n data objects are then divided into k clusters in order to make the access to the cluster to meet: high similarity of the object in the same cluster and less similarity between different objects in the cluster. Cluster similarity is the use of the cluster object is obtained by means of a "Center" (Center of gravity) is calculated. K-means algorithm is the most classical clustering method based on Division, is one of the top ten algorithms of data mining. The basic idea of k-means algorithm is: k points in space-centric clustering on objects closest to their classification. Through an iterative approach, successive values in cluster centers updated until you get the best cluster results.
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KMeans
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