FuzzyProbSim: Fuzzy probability as similarity measure

A. Ralescu, S. Visa, Stefana Popovici
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Abstract

This study investigates a unified robust measures of similarity applicable in many domains and across many dimensions of data. Given a distance or discrepancy measure on a domain, the similarity of two values in this domain is defined as the probability that any pair of values from that domain are more different (at a larger distance) than these two values are. Fuzzy sets are introduced to make this definition more sensitive to quantitative difference. Combination across domains is also discussed.
FuzzyProbSim:模糊概率作为相似性度量
本研究探讨了一种适用于许多领域和跨多个数据维度的统一的健壮的相似性度量。给定一个域上的距离或差异度量,该域中两个值的相似性被定义为该域中任何一对值比这两个值更不同(距离更大)的概率。引入模糊集使该定义对数量差异更加敏感。还讨论了跨域组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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