Opis wydania
Contextual probability, Journal of Telecommunications and Information Technology, 2003, nr 3
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Opis : In this paper we present a new probability function G that generalizes the classical probability function. A mass function is an assignment of basic probability to some context (events, propositions). It represents the strength of support for some contexts in a domain. A context is a subset of the basic elements of interest in a domain – the frame of discernment. It is a medium to carry the “probabilistic” knowledge about a domain. The G function is defined in terms of a mass function under various contexts. G is shown to be a probability function satisfying the axioms of probability. Therefore G has all the properties attributed to a probability function. If the mass function is obtained from probability function by normalization, then G is shown to be a linear function of probability distribution and a linear function of probability. With this relationship we can estimate probability distribution from probabilistic knowledge carried in some contexts without any model assumption.
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