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Towards More Adequate Representation of Uncertainty: From Intervals to Set Intervals, with the Possible Addition of Probabilities and Certainty Degrees

机译:为了更充分的不确定性表示:从间隔到设定间隔,可以添加可能的概率和确定性

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In the ideal case of complete knowledge, for each property P{sub}i (such as "high fever", "headache", etc.), we know the exact set S{sub}i of all the objects that satisfy this property. In practice, we usually only have partial knowledge. In this case, we only know the set S{sub}i of all the objects about which we know that P{sub}i holds and the set S{sub}i about which we know that P{sub}i may hold (i.e., equivalently, that we have not yet excluded the possibility of P{sub}i). This pair of sets is called a set interval. Based on the knowledge of the original properties, we would like to describe the set S of all the values that satisfy some combination of the original properties: e.g., high fever and headache and not rash. In the ideal case when we know the exact set S{sub}i of all the objects satisfying each property, it is sufficient to apply the corresponding set operation (composition of union, intersection, and complement) to the known sets S{sub}i. In this paper, we describe how to compute the class S of all possible sets S.
机译:在完整知识的理想情况下,对于每个属性P {sub} i(如“高发烧”,“头痛”等),我们知道满足此属性的所有对象的确切集S {子} I 。在实践中,我们通常只有部分知识。在这种情况下,我们只知道所有对象的集合s {sub}我知道p {sub}我持有和设置的s {sub}我知道p {sub}我可能持有(即,等效地,我们尚未排除p {sub} i)的可能性。这对集被称为设置间隔。基于原始属性的知识,我们想描述满足原始属性的某种组合的所有值的集合:例如,高烧和头痛而不是皮疹。在理想的情况下,我们知道满足每个属性的所有对象的确切的SET {sub} I,可以将相应的设置操作(Union,交叉点和补码的组成)应用于已知的集合s {sub}。一世。在本文中,我们描述了如何计算所有可能集合S的类别。

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