文件名称:ClusterAnalysis_2014.11.4
- 所属分类：
- 控制台(字符窗口)编程
- 资源属性：
- [Windows] [Visual.Net] [源码]
- 上传时间：
- 2016-08-09
- 文件大小：
- 32.02mb
- 下载次数：
- 0次
- 提 供 者：
- 周**
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
模式识别的聚类分析。K均值聚类算法是先随机选取K个对象作为初始的聚类中心。然后计算每个对象与各个种子聚类中心之间的距离，把每个对象分配给距离它最近的聚类中心。聚类中心以及分配给它们的对象就代表一个聚类。一旦全部对象都被分配了，每个聚类的聚类中心会根据聚类中现有的对象被重新计算。这个过程将不断重复直到满足某个终止条件。终止条件可以是没有（或最小数目）对象被重新分配给不同的聚类，没有（或最小数目）聚类中心再发生变化，误差平方和局部最小。-Pattern recognition clustering analysis. K-means clustering algorithm is to randomly K objects as the initial cluster centers. Then calculate the distance of each object and each seed cluster centers, assigning each object to its distance the nearest cluster center. Cluster centers and the object assigned to them on behalf of a cluster. Once all the objects are assigned, the cluster centers of each cluster will be recalculated based on the existing cluster object. This process is repeated until a termination condition is satisfied. Termination condition may not be (or smallest numbers) is reassigned to a different target cluster, no (or a minimum number) and then change the cluster centers, and a local minimum squared error.
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