K-means solves the problem of clustering, taking the Euclidean distance as the similarity measure, which is the optimal classification of the V of the J of the initial clustering center vector, which makes the uation index is the smallest. In the algorithm, the error square and criterion function is used as the criterion function of clustering.

K-means聚类算法分析\KMeans.m
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K-means聚类算法分析

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