Library for Bayesian Networks [closed]

Question

Hello fellow Number crunchers

As the headline suggests, I am looking for a library for learning and inference of Bayesian Networks. I have already found some, but I am hoping for a recommendation.

Requirements in a quick overview:

• preferably written in Java or Python
• configuration (also of the network itself) is a) possible and b) possible via code (and not solely via a GUI).
• source code available
• project is still maintained
• the more powerful, the better

Which one do you recommend ?

Answer 1

Have a look at Weka. It's kind of popular in my neck of the woods... It's open-source and written in Java.

This will tell you about bayesian networks in Weka, from the abstract:

• Structure learning of Bayesian networks using various hill climbing (K2, B, etc) and general-purpose (simulated annealing, tabu search) algorithms.
• Local score metrics implemented; Bayes, BDe, MDL, entropy, AIC.
• Global score metrics implemented; leave one out cv, k-fold cv and cumulative cv.
• Conditional independence based causal recovery algorithm available.
• Parameter estimation using direct estimates and Bayesian model averaging.
• GUI for easy inspection of Bayesian networks.