Python Tool for BN Structure Learning (Greedy
Posted: Mon Feb 16, 2026 10:55 amFor Bayesian Network (BN) structure learning, I utilized the pgmpy Python library, specifically the HillClimbSearchalgorithm with BICScore.
Tool Details:
•Library: pgmpy
•Method: HillClimbSearch
•Scoring Metric: BIC (Bayesian Information Criterion)
Brief Overview:
HillClimbSearch in pgmpy implements a greedy hill climbing approach for Bayesian Network structure learning. The algorithm iteratively evaluates local structural modifications (edge additions, removals, reversals) and selects the change that maximizes the scoring function. In this analysis, BICScore was used to balance model fit and complexity, helping prevent overfitting while identifying plausible dependency relationships among variables.
Tool Details:
•Library: pgmpy
•Method: HillClimbSearch
•Scoring Metric: BIC (Bayesian Information Criterion)
Brief Overview:
HillClimbSearch in pgmpy implements a greedy hill climbing approach for Bayesian Network structure learning. The algorithm iteratively evaluates local structural modifications (edge additions, removals, reversals) and selects the change that maximizes the scoring function. In this analysis, BICScore was used to balance model fit and complexity, helping prevent overfitting while identifying plausible dependency relationships among variables.