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Computer implemented scalable, incremental and parallel clustering based on weighted divide and conquer
Computer implemented scalable, incremental and parallel clustering based on weighted divide and conquer
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机译:基于加权分而治之的计算机实现的可伸缩,增量和并行集群
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摘要
A technique that uses a weighted divide and conquer approach for clustering a set S of n data points to find k final centers. The technique comprises 1) partitioning the set S into P disjoint pieces S1, . . . , SP; 2) for each piece Si, determining a set Di of k intermediate centers; 3) assigning each data point in each piece Si to the nearest one of the k intermediate centers; 4) weighting each of the k intermediate centers in each set Di by the number of points in the corresponding piece Si assigned to that center; and 5) clustering the weighted intermediate centers together to find said k final centers, the clustering performed using a specific error metric and a clustering method A.
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机译:一种使用加权分治法的技术,对n个数据点的集合S进行聚类,以找到k个最终中心。该技术包括:1)将集合S划分为P个不相交的块S 1 Sub>,...。 。 。 ,S P Sub>; 2)对于每个S i Sub>,确定k个中间中心的集合D i Sub>; 3)将每个S i Sub>中的每个数据点分配给k个中间中心中最接近的一个; 4)通过分配给该中心的相应片段S i Sub>中的点数对每个集合D i Sub>中的k个中间中心进行加权;和5)将加权的中间中心聚类在一起以找到所述k个最终中心,使用特定误差度量和聚类方法A执行聚类。
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