  Recent reports have described that learning Bayesian networks are highly
sensitive to the chosen equivalent sample size (ESS) in the Bayesian Dirichlet
equivalence uniform (BDeu). This sensitivity often engenders some unstable or
undesirable results. This paper describes some asymptotic analyses of BDeu to
explain the reasons for the sensitivity and its effects. Furthermore, this
paper presents a proposal for a robust learning score for ESS by eliminating
the sensitive factors from the approximation of log-BDeu.
