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0 votes
in Machine Learning by (4.2k points)

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 ?

1 Answer

+1 vote
by (6.8k points)

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.

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