In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probabi...
A protocol for the elicitation of imprecise probabilities based on linear programming is applied to the case of two continuous variables. Two medical experts were elicited. The re...
In this paper we consider decision making under hierarchical imprecise uncertainty models and derive general algorithms to determine optimal actions. Numerical examples illustrate...
Based on the coherence principle of de Finetti and a related notion of generalized coherence (g-coherence), we adopt a probabilistic approach to uncertainty based on conditional p...
Veronica Biazzo, Angelo Gilio, Giuseppe Sanfilippo
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this pa...