Transcription of Learning Bayesian Networks with the bnlearn R …
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Learning Bayesian Networks with the bnlearn R …
JSSJ ournal of Statistical SoftwareMMMMMM YYYY, Volume VV, Issue Bayesian Networks with thebnlearnRPackageMarco ScutariUniversity of PadovaAbstractbnlearnis anRpackage (R Development Core Team 2009) which includes several algo-rithms for Learning the structure of Bayesian Networks with either discrete or continuousvariables. Both constraint-based and score-based algorithms are implemented, and canuse the functionality provided by thesnowpackage (Tierneyet ) to improve theirperformance via parallel computing. Several network scores and conditional independencealgorithms are available for both the Learning algorithms and independent use. Advancedplotting options are provided by theRgraphvizpackage (Gentryet ).Keywords: Bayesian Networks ,R, structure Learning algorithms, constraint-based algorithms,score-based algorithms, conditional independence IntroductionIn recent years Bayesian Networks have been used in many fields, from On-line AnalyticalProcessing (OLAP) performance enhancement (Margaritis 2003) to medical service perfor-mance analysis (Acidet ), gene expression analysis (Friedmanet ), breastcancer prognosi
2 Learning Bayesian Networks with the bnlearn R Package to construct the Bayesian network. Both discrete and continuous data are supported. Fur-
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