The theory of belief functions is based on two ideas: the idea of obtaining degrees of belief for one question from subjective probabilities for a related question, and Dempster's rule for combining such degrees of belief when they are based on independent items of evidence.
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Jun 8, 2017 · It is demonstrated that the so-called "conditional" belief function is not a belief function given an event but rather a belief function given ...
The theory of belief functions, also referred to as evidence theory or Dempster–Shafer theory (DST), is a general framework for reasoning with uncertainty.
A belief function, in the context of Computer Science, refers to a mathematical representation of uncertainty that can be applied to continuous frames of ...
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Sep 10, 2024 · WHAT DOES A BELIEF FUNCTION BELIEVE IN ? 3. In this paper we assume that DST notions like basic probability assignment or mass ; marginalization ...
Sep 2, 2024 · A belief function by using a known probability distribution on some situation to associate it with another situation where probabilities are unknown.
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Can anyone help me with this probability/belief function? - Reddit
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Jul 7, 2022 · Imagine you're considering your belief of an event/proposition, and all the evidence you have is 6 sources who each present their belief of ...
Oct 27, 2019 · A formal framework for representing and reasoning with uncertain information. Also known as Dempster-Shafer (DS) theory or Evidence theory.
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The theory of belief functions is a generalization of the Bayesian theory of subjective probability judgement.
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[PDF] Belief functions and possibility measures. - Glenn Shafer
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The set of belief functions is actually a subset of the set of lower probability measures, but the two languages use different canonical examples and hence use ...