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Variable Selection Bias in Classification Trees Based on Imprecise Probabilities [PDF]
, 2005 Classification trees based on imprecise probabilities provide an advancement of classical classification trees. The Gini Index is the default splitting criterion in classical classification trees, while in classification trees based on imprecise ...
Strobl, Carolin
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Resolving Peer Disagreements Through Imprecise Probabilities [PDF]
Noûs, 2018 AbstractTwo compelling principles, the Reasonable Range Principle and the Preservation of Irrelevant Evidence Principle, are necessary conditions that any response to peer disagreements ought to abide by. The Reasonable Range Principle maintains that a resolution to a peer disagreement should not fall outside the range of views expressed by the peers ...
Lee Elkin, G. Wheeler
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Forecasting with imprecise probabilities
International Journal of Approximate Reasoning, 2012 We review de Finetti’s two coherence criteria for determinate probabilities: coherence1defined in terms of previsions for a set of events that are undominated by the status quo – previsions immune to a sure-loss – and coherence2 defined in terms of forecasts for events undominated in Brier score by a rival forecast.
Seidenfeld, Teddy +2 more
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Kongzhi Yu Xinxi Jishu, 2023 Dynamic target tracking is a crucial technique for autonomous underwater vehicles (AUV), enabling key operations such as target detection and reconnaissance.
QIN Hongmao +4 more
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Imprecise Bayesian Networks as Causal Models
Information, 2018 This article considers the extent to which Bayesian networks with imprecise probabilities, which are used in statistics and computer science for predictive purposes, can be used to represent causal structure. It is argued that the adequacy conditions for
David Kinney
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Reasoning with imprecise probabilities
International Journal of Approximate Reasoning, 2007 This special issue of the International Journal of Approximate Reasoning (IJAR) grew out of the 4th International Symposium on Imprecise Probabilities and Their Applications (ISIPTA’05), held in Pittsburgh, USA, in July 2005 (http://www.sipta.org/isipta05). The symposium was organized by Teddy Seidenfeld, Robert Nau, and Fabio G.
Cano, A, Cozman, F, Lukasiewicz, T
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A statistical inference method for the stochastic reachability analysis. [PDF]
, 2005 The main contribution of this paper is the characterization of reachability problem associated to stochastic hybrid systems in terms of imprecise probabilities. This provides the connection between reachability problem and Bayesian statistics.
Bujorianu, L.M.
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Second-Order Risk Constraints in Decision Analysis
Axioms, 2014 Recently, representations and methods aimed at analysing decision problems where probabilities and values (utilities) are associated with distributions over them (second-order representations) have been suggested.
Love Ekenberg +3 more
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Computation with imprecise probabilities [PDF]
2008 IEEE International Conference on Information Reuse and Integration, 2008 Computation with imprecise probabilities is not an academic exercise—it is a bridge to reality. In the real world, imprecision of probabilities is the norm rather than exception. In large measure, real-world probabilities are perceptions of likelihood. Perceptions are intrinsically imprecise.
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A Generic Clustering-Based Algorithm for Approximating IOHMM Topology and Parameters
IEEE Access, 2021 In this paper, a novel generic clustering-based algorithm for approximating the topology and the parameters of discrete state space Input/Output Hidden Markov Models (IOHMMs) with continuous observation spaces is introduced. The algorithm can accommodate
Gerald Rocher +2 more
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