2018/06/20 by Ivo Düntsch, Günther Gediga, Düntsch, Ivo +3
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Multi-Criteria Decision Making #Rough Sets and Fuzzy Logic #cs.AI
paper · pdf · doi:10.48550/arxiv.1806.07685
arxiv created 2018/06/20 · openalex publication_date 2018/06/20 · arxiv updated 2018/06/21 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
In this exploratory article, we draw attention to the common formal ground among various estimators such as the belief functions of evidence theory and their relatives, approximation quality of rough set theory, and contextual probability. The unifying concept will be a general filter function composed of a basic probability and a weighting which varies according to the problem at hand. To compare the various filter functions we conclude with a simulation study with an example from the area of item response theory.