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k-means-clustering

于 2012-09-20 发布 文件大小:13KB
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  用C语言程序通过先随机选取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。(C Programming Language by first randomly selected the K object as initial cluster centers. And then calculate the distance between each object and each seed cluster center, and assign each object to its nearest cluster center. Cluster centers, and the object assigned to them on behalf of a clustering. Once all the objects are assigned to each cluster cluster centers will be based on the existing object clustering is recalculated.)

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