说明：  K-means算法是最为经典的基于划分的聚类方法，是十大经典数据挖掘算法之一。K-means算法的基本思想是：以空间中k个点为形心进行聚类，对最靠近他们的对象归类。通过迭代的方法，逐次更新各簇的形心的值，直至得到最好的聚类结果。（形心可以是实际的点、或者是虚拟点） 。
(K-means algorithm is the most classical partition-based clustering method and one of the ten classical data mining algorithms. The basic idea of K-means algorithm is to cluster k points in space as centroid and classify the objects closest to them. By iteration, the centroid values of each cluster are updated successively until the best clustering results are obtained. (Centroid can be a real point or a virtual point))