Additivity of uncertainty measures on credal sets

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چکیده

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Additivity of uncertainty measures on credal sets

A general way of representing incomplete information is to use closed and convex sets of probability distributions, which are also called credal sets. Each credal set is associated with uncertainty, whose amount is quantified by an appropriate uncertainty measure. One of the requisite properties of uncertainty measures is the property of additivity, which is associated with the concept of indep...

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Measures of divergence on credal sets

When there is uncertainty about the values of a variable, it is possible to have different pieces of information about it. This can be due to the fact that they represent the points of view of different agents and these agents have followed different criteria when codify the pieces of information by means of numbers. The aim of this paper is to provide tools for the comparison of these represen...

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Application of uncertainty measures on credal sets on the naive Bayesian classifier

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Disaggregated total uncertainty measure for credal sets

We present a new approach to measure uncertainty/information applicable to theories based on convex sets of probability distributions, also called credal sets. A definition of a total disaggregated uncertainty measure on credal sets is proposed in this paper motivated by recent outcomes. This definition is based on the upper and lower values of Shannon’s entropy for a credal set. We justify the...

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Sets of Desirable Gambles and Credal Sets

Sets of desirable gambles were proposed by Walley [7] as a general theory of imprecise probability. The main reasons for this are: it is a very general model, including as particular cases most of the existing theories for imprecise probability; it has a deep and simple axiomatic justification; and mathematical definitions are natural and intuitive. However, there is still a lot of work to be d...

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ژورنال

عنوان ژورنال: International Journal of General Systems

سال: 2005

ISSN: 0308-1079,1563-5104

DOI: 10.1080/03081070500396915