Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

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. PEBL is released under the MIT open-source license, can be installed from the Python Package Index and is available at http://pebl-project.googlecode.com. [abs] [ pdf ][ bib ] [ code ] © JMLR 2009. (edit, beta)