Learning Bayesian Networks with the bnlearn R Package

Abstract

bnlearn is an R package which includes several algorithms for learning the structure of Bayesian networks with either discrete or continuous variables. Both constraint-based and score-based algorithms are implemented, and can use the functionality provided by the snow package to improve their performance via parallel computing. Several network scores and conditional independence algorithms are available for both the learning algorithms and independent use. Advanced plotting options are provided by the Rgraphviz package.

22 pages, 4 pictures

References in corpus (2)

• Estimating high-dimensional directed acyclic graphs with the PC-algorithm
• A Transformational Characterization of Equivalent Bayesian Network Structures

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