Walley’s Imprecise Dirichlet Model (IDM) for categorical data overcomes several fundamental problems which other approaches to uncertainty suffer from. Yet, to be useful in prac...
Abstract. This paper is concerned with the reliable inference of optimal treeapproximations to the dependency structure of an unknown distribution generating data. The traditional ...
Abstract. The naive credal classifier (NCC) extends naive Bayes classifier (NBC) to imprecise probabilities to robustly deal with the specification of the prior; NCC models a state...
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...