k-means 算法接受参数 k ；然后将事先输入的n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。-K-means algorithm accept parameter k　Then will the n of prior input data object is divided into k clustering to make won clustering meet: the same clustering the object in the similarity is higher　And different clustering the object in the smaller similarity. Clustering similarity is using the cluster of the object in the mean gained a "center object" (the center of gravity) to calculate.