This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The database is reorganised in a new form of representation called reduced database where data are treated as distributions on symbolic values.
J. F. Baldwin, E. Di Tomaso