# Effective and efficient structure learning with pruning and model averaging strategies

@article{Constantinou2021EffectiveAE, title={Effective and efficient structure learning with pruning and model averaging strategies}, author={Anthony C. Constantinou and Yang Liu and Neville Kenneth Kitson and Kiattikun Chobtham and Zhi-gao Guo}, journal={ArXiv}, year={2021}, volume={abs/2112.00398} }

: Learning the structure of a Bayesian Network (BN) with score-based solutions involves exploring the search space of possible graphs and moving towards the graph that maximises a given objective function. Some algorithms offer exact solutions that guarantee to return the graph with the highest objective score, while others offer approximate solutions in exchange for reduced computational complexity. This paper describes an approximate BN structure learning algorithm, which we call Modelβ¦Β

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