论文标题
对称和最佳概率到期性转换的概括
A generalization of the symmetrical and optimal probability-to-possibility transformations
论文作者
论文摘要
可能性和概率理论是处理不确定性的替代方法和互补方法，这在过去几年中引起了人们对将概率分布转变为可能性分布的方法的兴趣，而是相反。本文研究了两个可能性转化的两个众所周知的离散概率的优势和缺点：最佳转换和对称转换，并提出了一种新的可能性转化的参数家族，从而使它们概括并减轻它们的缺点，从而显示了实际应用的巨大潜力。本文还基于模糊子概念引入了针对概率分布的新颖模糊度量，并提出了将其应用于文本作者身份归因问题的广义转换实用性的经验验证。
Possibility and probability theories are alternative and complementary ways to deal with uncertainty, which has motivated over the last years an interest for the study of ways to transform probability distributions into possibility distributions and conversely. This paper studies the advantages and shortcomings of two well-known discrete probability to possibility transformations: the optimal transformation and the symmetrical transformation, and presents a novel parametric family of probability to possibility transformations which generalizes them and alleviate their shortcomings, showing a big potential for practical application. The paper also introduces a novel fuzzy measure of specificity for probability distributions based on the concept of fuzzy subsethood and presents a empirical validation of the generalized transformation usefulness applying it to the text authorship attribution problem.
