A Python-based implementation of Bayesian network structure learning using mutual information and Minimum Description Length (MDL) scoring. This project constructs probabilistic graphical models from real-world data and evaluates their performance in representing dependencies among variables.
python data-science bayesian-network graph-theory probabilistic-graphical-models causal-inference structure-learning mutual-information explainable-ai xai dependency-modeling mdl-scoring
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Updated
Mar 20, 2025 - Jupyter Notebook