pyAgrum

pyAgrum is a scientific C++ and Python open source library dedicated to Bayesian networks (BN) and other Probabilistic Graphical Models. Based on the C++ aGrUM library, it provides a high-level interface to the C++ part of aGrUM allowing to create, manage and perform efficient computations with Bayesian networks and others probabilistic graphical models : - Markov networks (MN), - influence diagrams (ID) and LIMIDs, credal networks (CN), - dynamic BN (dBN), - probabilistic relational models (PRM). Several topics have been added to pyAgrum (as pure python modules using pyAgrum) : - Scikit-learn-compliant probabilistic classifiers based on Bayesian networks, - Probabilistic causality (causal networks, do-calculus), - dynamic Bayesian network, - tools for explainability in Bayesian networks.