Bayesian network structure learning by dynamic programming algorithm based on node block sequence constraints

Abstract The use of dynamic programming (DP) algorithms to learn Bayesian network structures is limited by their high space complexity and difficulty in learning the structure of large‐scale networks. Therefore, this study proposes a DP algorithm based on node block sequence constraints. The propose... View More