Dependent Cluster Mapping (DCMAP): Optimal clustering of directed acyclic graphs for statistical inference

A Directed Acyclic Graph (DAG) can be partitioned or mapped into clusters to support and make inference more computationally efficient in Bayesian Network (BN), Markov process and other models. However, optimal partitioning with an arbitrary cost function is challenging, especially in statistical inference as the local cluster cost is dependent on both nodes within a cluster, and the mapping of clusters connected via parent and/or child nodes, which we call dependent clusters. We propose a novel algorithm called DCMAP for …

bayesian cluster clustering cost cs.ds dag function graph graphs inference mapped mapping markov network partitioning process statistical stat.ml support