Comparison of the Bayesian Network Structure Learning Algorithms

Abstract

This paper compares selected Bayesian network structure-learning algorithms and discusses their suitability for discovering dependency structures in data. The study focuses on algorithmic differences, comparative performance, and implications for applications requiring probabilistic network modeling.