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Supervised learning using Boltzmann Bayes model inference, which extends naive Bayes model to include interactions. Enables classification of data into multiple response groups based on a large number of discrete predictors that can take factor values of heterogeneous levels. Either pseudolikelihood or mean field inference can be used with L2 regularization, crossvalidation, and prediction on new data. Woo et al. (2016) <doi:10.1186/s1286401628713>.
Package details 


Author  Jun Woo [aut, cre] (<https://orcid.org/0000000332202064>), Jinhua Wang [ctb] 
Maintainer  Jun Woo <[email protected]> 
License  GPL (>= 2) 
Version  0.3.0 
Package repository  View on CRAN 
Installation 
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