k-means algorithm to accept input k then n data object is divided into k-clustering in order to make available to the cluster to meet: the same objects in clustering high similarity and objects in different clustering the similarity smaller. Cluster similarity is the use of the clustering of objects by means of a

Packet : 23825791k_means.rar filelist
k平均算法\iris_te.mat
k平均算法\iris_tr.mat
k平均算法\k_means.m
k平均算法

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