K-means有注释版本

  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。(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 and classify the objects closest to them. Iteratively, the values of centroid of clusters are updated one by one until the best clustering results are obtained.)