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首页> 外文期刊>Journal of applied and industrial mathematics >Exact Pseudopolynomial Algorithms for a Balanced 2-Clustering Problem
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Exact Pseudopolynomial Algorithms for a Balanced 2-Clustering Problem

机译:平衡2-聚类问题的精确伪多项式算法

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摘要

We consider the strongly NP-hard problem of partitioning a set of Euclidean points into two clusters so as to minimize the sum (over both clusters) of the weighted sum of the squared intracluster distances from the elements of the clusters to their centers. The weights of sums are the sizes of the clusters. The center of one cluster is given as input, while the center of the other cluster is unknown and determined as the average value over all points in the cluster (as the geometric center). Two variants of the problems are analyzed in which the cluster sizes are either given or unknown. We present and prove some exact pseudopolynomial algorithms in the case of integer components of the input points and fixed space dimension.
机译:我们考虑将一组欧几里得点划分为两个聚类的强烈NP难题,以使从聚类元素到它们的中心的聚类内距离的平方和的加权总和最小化(在两个聚类上)。和的权重是簇的大小。给出一个聚类的中心作为输入,而另一个聚类的中心未知,并确定为该聚类中所有点的平均值(作为几何中心)。分析了问题的两个变体,其中给定的簇大小或未知的簇大小。我们提出并证明了在输入点的整数分量和固定空间尺寸的情况下一些精确的伪多项式算法。

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