通过对K-均值算法的编程实现，加强对该算法的理解和认识。提高自身的知识水平和编程能力，认识模式识别在生活中的应用。

算法思想K-均值算法的主要思想是先在需要分类的数据中寻找K组数据作为初始聚类中心，然后计算其他数据距离这三个聚类中心的距离，将数据归入与其距离最近的聚类中心，之后再对这K个聚类的数据计算均值，作为新的聚类中心，继续以上步骤，直到新的聚类中心与上一次的聚类中心值相等时结束算法。-By programming K- means algorithm implementation, strengthen understanding and awareness of the algorithm. Improve their level of knowledge and programming skills, understanding of pattern recognition in life. The main idea thought K- means algorithm is the first in the classification of the data needed to find K sets of data as the initial cluster centers, and other data to calculate the distance　the cluster center of the three, the data included in its closest poly class center, after which the K clustering of these data to calculate the mean, as a new cluster centers, continue the above steps until the new cluster centers and cluster centers on a value equal to the end of the algorithm.