structure.learning: Structure learning algorithms

Description Available Constraint-Based Learning Algorithms Available Score-based Learning Algorithms Available Hybrid Learning Algorithms Other (Constraint-Based) Local Discovery Algorithms Pairwise Mutual Information Algorithms

Description

Overview of the structure learning algorithms implemented in bnlearn, with the respective reference publications.

Available Constraint-Based Learning Algorithms

bnlearn includes two implementations of each algorithm: a vanilla implementation, and a parallel one that requires a running cluster set up with the makeCluster function from the parallel package.

Available Score-based Learning Algorithms

Available Hybrid Learning Algorithms

Other (Constraint-Based) Local Discovery Algorithms

These algorithms learn the structure of the undirected graph underlying the Bayesian network, which is known as the skeleton of the network. Therefore by default all arcs are undirected, and no attempt is made to detect their orientation. They are often used in hybrid learning algorithms.

Pairwise Mutual Information Algorithms

These algorithms learn approximate network structures using only pairwise mutual information.

All these algorithms have two implementations (vanilla and parallel) like other constraint-based algorithms.


bnlearn documentation built on Sept. 7, 2021, 1:07 a.m.