- Tytuł:
- Contextual probability
- Autorzy:
- Wang, H.
- Powiązania:
- https://bibliotekanauki.pl/articles/307791.pdf
- Data publikacji:
- 2003
- Wydawca:
- Instytut Łączności - Państwowy Instytut Badawczy
- Tematy:
-
mathematical foundations
knowledge representation
machine learning
uncertainty
data mining - 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.
- Źródło:
-
Journal of Telecommunications and Information Technology; 2003, 3; 92-97
1509-4553
1899-8852 - Pojawia się w:
- Journal of Telecommunications and Information Technology
- Dostawca treści:
- Biblioteka Nauki
Artykuł