Publication details
Conference Paper (Czech conference)
How Sir Harold Jeffreys would create a belief function based on data
, ,
: Proceedings of the 13th Workshop on Uncertainty Processing (WUPES’25), p. 92-103 , Eds: Studený Milan, Ay Nihat, Capotorti Andrea, Csirmaz László, Jiroušek Radim, Kleiter Gernot D., Shenoy Prakash P.
: Workshop on Uncertainty Processing - WUPES 2025 /13./, (Třešť, CZ, 20250604)
: belief function, learning, confidence interval
: http://library.utia.cas.cz/separaty/2025/MTR/jirousek-0636593.pdf
: https://wupes.utia.cas.cz/2025/Proceedings.pdf#page=101
(eng): Not all normalized nonnegative monotone set functions are belief functions. This paper investigates ways to modify them to obtain a belief function that preserves some of their properties. The problem is motivated by an approach to data-based learning of belief function models. The approach is based on the idea that classical methods of mathematical statistics can provide estimates of lower bounds for unknown probabilities. Thus, methods of mathematical statistics can be used to obtain a reasonable rough estimate, which is further elaborated to obtain a desired belief function model.
: BA
: 10102