密集数据挖掘的模糊方法

M. Buscema, P. Sacco
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引用次数: 0

摘要

对于许多空间过程,自然需要根据现有的观测散点找出起源点;例如,根据犯罪现场的实际分布,找出罪犯的大本营,或者流行病的爆发源。我们介绍了一种基于拓扑加权质心(TWC)概念的新方法,该方法允许人们在观测较少或对底层数据生成过程理解不深的相对棘手的情况下也能得出强有力的推论。在本文中,我们考虑在小维度定性数据集的基础上重建全球政治和经济关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fuzzy approach to intensive data mining
For many spatial processes, there is a natural need to find out the point of origin on the basis of the available scatter of observations; think for instance of finding out the home-base of a criminal given the actual distribution of crime scenes, or the outbreak source of an epidemics. We introduce a new methodology based on the notion of Topological Weighted Centroid (TWC) that allows one to draw powerful inferences also in relatively intractable cases with few observations or a poorly understood underlying data generating process. In this paper we consider reconstruction of global political and economic relationships on the basis of a small-dimensional qualitative dataset.
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