Bayesian Networks - The Pythonic Way

To this point in the project the Bayesian Networks have been implemented without using a library. NetworkX has been used for representing the underlying graph structure but everything from that point up has been implemented by hand.

In an aim to follow the "pythonic way" I have begun looking into existing libraries to implement the Bayesian Network. The goal of this investigation is that that using an existing package would decrease the development time of this project.

After some initial research I have created a short list of the various libraries that will be considered in greater depth.

PBNT – Python Bayesian Network Toolbox

http://pbnt.berlios.de/

Pebl - Python Environment for Bayesian Learning

https://github.com/abhik/pebl

PyBayes

https://github.com/strohel/PyBayes

Orange

http://orange.biolab.si/

Pymc

https://github.com/pymc-devs/pymc

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