title: Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data.
abstract: In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing.
authors.affiliation: Department of Chemical Engineering, 3320 G.G. Brown, Ann Arbor, MI 48103, USA.
authors.forename: Abhik
authors.initials: A
authors.lastname: Shah
authors.forename: Peter
authors.initials: P
authors.lastname: Woolf