Bayesian implicative analysis was proposed for summarizing the association in a 22 contingency table in terms possibly asymmetrical such as, e.g., presence of feature a implies, i...
In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet ...
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...