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stat.ML2019★ 10 cited
Additive Bayesian Network Modelling with the R Package abn
Gilles Kratzer, Fraser Iain Lewis, Arianna Comin +2
The R package abn is designed to fit additive Bayesian models to observational datasets. It contains routines to score Bayesian networks based on Bayesian or information theoretic…
stat.ML2018
Information-Theoretic Scoring Rules to Learn Additive Bayesian Network Applied to Epidemiology
Gilles Kratzer, Reinhard Furrer
Bayesian network modelling is a well adapted approach to study messy and highly correlated datasets which are very common in, e.g., systems epidemiology. A popular approach to lear…
stat.ML2018
varrank: an R package for variable ranking based on mutual information with applications to observed systemic datasets
Gilles Kratzer, Reinhard Furrer
This article describes the R package varrank. It has a flexible implementation of heuristic approaches which perform variable ranking based on mutual information. The package is pa…