Learning Bayesian Networks with the bnlearn R Package
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Abstract
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 independent use. Advanced plotting options are provided by the Rgraphviz package (Gentry et al. 2010).
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Topics
Keywords
- R package
- Computer science
- Bayesian network
- Conditional independence
- Bayesian probability
- Artificial intelligence
- Machine learning
- Programming language
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