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

Abhik Shah, Peter Woolf; 10(Feb):159--162, 2009.

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.

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] [code][mloss.org]