输入：聚类个数k，以及包含 n个数据对象的数据库。输出：满足方差最小标准的k个聚类。处理流程： （1）从 n个数据对象任意选择 k 个对象作为初始聚类中心.

（2）根据每个聚类对象的均值（中心对象），计算每个对象与这些中心对象的距离；并根据最小距离重新对相应对象进行划分；（3）重新计算每个（有变化）聚类的均值（中心对象）

（4）循环（2）到（3）直到每个聚类不再发生变化为止-Input: number of clusters k, and n data object contains a database. Output: meet the standard minimum variance k-clustering. Processes: (1) n data objects from arbitrarily selected k object as initial cluster centers. (2) based on the mean of each cluster object (central object), calculated for each object and the distance to the object of these centers　and according to the minimum distance to re-divide the corresponding object　(3) re-calculated for each (a change) clustering means (central object) (4) Cycle (2) to (3) until no further change in each cluster until the