Learning Bayesian networks with the bnlearn R Package

Journal article

bnlearn is an R package (R Development Core Team 2010) 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 (Tierney et al. 2008) to improve their performance via parallel computing. Several network scores and conditional independence algorithms are available for both the learning algorithms and ...

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Authors: Scutari, M

• Journal: Journal of Statistical Software
• Volume: 35
• Issue: 3
• Pages: 1-22
• Publication date: 2010-07-01
• EISSN: 1548-7660
• ISSN: 1548-7660
• Language: English
• Keywords: Bayesian networks; Constraint-based algorithms; Score-based algorithms; Conditional independence tests; R; Structure learning algorithms