前言
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一、K-means聚类算法原理
K-means算法首先从数据样本中选取K个点作为初始聚类中心;其次计算各个样本到聚类的距离，把样本归到离它最近的那个聚类中心所在的类:然后计算新形成的每个聚类的数据对象的平均值来得到新的聚类中心;最后重复以上步骤，直到相邻两次的聚类中心没有任何变化，说明样本调整结束，聚类准则函数达到最优。
二、K-means聚类算法的要点
1.选定某种距离作为数据样本间的相似性度量
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Original: https://blog.csdn.net/wenyusuran/article/details/119237100
Author: 文宇肃然
Title: MATLAB实战系列（三十八）-基于K-means聚类算法的MATLAB图像分割
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