- Tytuł:
- Contextual probability
- Autorzy:
- Wang, H.
- Tematy:
-
mathematical foundations
knowledge representation
machine learning
uncertainty
data mining - Pokaż więcej
- Wydawca:
- Instytut Łączności - Państwowy Instytut Badawczy
- Powiązania:
- https://bibliotekanauki.pl/articles/307791.pdf  Link otwiera się w nowym oknie
- 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.
- Dostawca treści:
- Biblioteka Nauki
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