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Tree-Based Credal Networks for Classification
Reliable Computing, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zaffalon, Marco, Fagiuoli, Enrico
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Thirty years of credal networks: Specification, algorithms and complexity
International Journal of Approximate Reasoning, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Denis Deratani Mauá +1 more
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2010
We have seen that in many cases it suffices to restrict attention to convex sets of probability functions, and even, in the case of objective Bayesianism, often a single probability function. This restriction will be important in what follows, since it will allow us to exploit the computational machinery of probabilistic networks—in particular credal ...
Rolf Haenni +3 more
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We have seen that in many cases it suffices to restrict attention to convex sets of probability functions, and even, in the case of objective Bayesianism, often a single probability function. This restriction will be important in what follows, since it will allow us to exploit the computational machinery of probabilistic networks—in particular credal ...
Rolf Haenni +3 more
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Approximate inferring of goal-oriented credal network
2007 International Conference on Wavelet Analysis and Pattern Recognition, 2007Approximate inferring approach of Credal network based on ant colony algorithms is put forward. Considering network inferring of goal-oriented in Bayesian network for the variable decision-maker is interested in given some evidence, the paper gives arithmetic for acquiring equivalent Credal network structure of goal-oriented.
null Yu-Ling Li, null Qi-Zong Wu
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Probability-Possibility Transformations: Application to Credal Networks
2015This paper deals with belief graphical models and probability-possibility transformations. It first analyzes some properties of transforming a credal network into a possibilistic one. In particular, we are interested in satisfying some properties of probability-possibility transformations like dominance and order preservation.
Benferhat, Salem +2 more
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Application of credal network on evaluating emergency capacity
Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology, 2011By analyzing existing evaluation method of emergency capacity, the paper pointed out the inadequacy of existing methods and gave an evaluating model on emergency capacity based on Credal Network. It better expressed the uncertainty and complexity of the system by interval probability, and taked inference and diagnosis on the system. In the end, it gave
Zonggeng Zhao, Dingshi Sun, Yanan Wang
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Reliable Knowledge-Based Adaptive Tests by Credal Networks
2017An adaptive test is a computer-based testing technique which adjusts the sequence of questions on the basis of the estimated ability level of the test taker. We suggest the use of credal networks, a generalization of Bayesian networks based on sets of probability mass functions, to implement adaptive tests exploiting the knowledge of the test developer
Francesca Mangili +2 more
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Inference in credal networks using multilinear programming
2004A credal network is a graphical tool for representation and manipulation of uncertainty, where probability values may be imprecise or indeterminate. A credal network associates a directed acyclic graph with a collection of sets of probability measures; in this context, inference is the computation of tight lower and upper bounds for conditional ...
de Campos, C. P., Cozman, F. G.
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Markov conditions and factorization in logical credal networks
International Journal of Approximate ReasoningzbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fabio G. Cozman +5 more
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Inference in Credal Networks Through Integer Programming
2007A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation.
de Campos, C. P., Cozman, F. G.
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