Description:

The Libra machine learning toolkit includes implementations of a variety of algorithms for learning and inference with Bayesian networks, Markov networks, and arithmetic circuits:

Learning algorithms -- Structure learning for BNs, ACs, and dependency networks; Chow-Liu algorithm; AC weight learning

Inference algorithms -- Mean field, belief propagation, max-product, Gibbs sampling, AC variable elimination, AC exact inference

Libra's strength is exploiting context-specific independence (such as decision tree CPDs) to allow exact inference in models with high treewidth.

Changes to previous version:

Version 0.4.0 (7/06/2011): * MF inference in DNs (mf -depnet) * Max-product algorithm for BNs and MNs (maxprod) * MPE inference in ACs (acquery -mpe) * Added support for UAI MN file format. * New fstats utility to get basic file statistics for most file types supported by Libra * And more!

BibTeX Entry: Download

Supported Operating Systems: Cygwin, Linux, Mac Os X

Data Formats: Ascii

Tags: Structure Learning, Approximate Inference, Bayesian Networks, Markov Random Fields, Dependency Networks, Arithmetic Circuits, Exact Inference, Markov Networks

Archive: download here

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