Summary: 7th International Symposium on Imprecise Probability: Theories and Applications, Innsbruck, Austria, 2011
Likelihood-Based Naive Credal Classifier
Alessandro Antonucci
IDSIA, Lugano
alessandro@idsia.ch
Marco E. G. V. Cattaneo
Department of Statistics, LMU Munich
cattaneo@stat.uni-muenchen.de
Giorgio Corani
IDSIA, Lugano
giorgio@idsia.ch
Abstract
The naive credal classifier extends the classical naive
Bayes classifier to imprecise probabilities, substitut-
ing the imprecise Dirichlet model for the uniform
prior. As an alternative to the naive credal classi-
fier, we present a likelihood-based approach, which
extends in a novel way the naive Bayes towards impre-
cise probabilities, by considering any possible quan-
tification (each one defining a naive Bayes classifier)

Source: Antonucci, Alessandro - Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA)
Corani, Giorgio - Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA)

Collections: Computer Technologies and Information Sciences