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Two classification ensemble methods based on logic regression models. LogForest() uses a bagging approach to construct an ensemble of logic regression models. LBoost() uses a combination of boosting and crossvalidation to construct an ensemble of logic regression models. Both methods are used for classification of binary responses based on binary predictors and for identification of important variables and variable interactions predictive of a binary outcome. Wolf, B.J., Slate, E.H., Hill, E.G. (2010) <doi:10.1093/bioinformatics/btq354>.
Package details 


Author  Bethany Wolf [aut], Melica Nikahd [ctb, cre], Madison Hyer [ctb] 
Maintainer  Melica Nikahd <melica.nikahd@osumc.edu> 
License  GPL3 
Version  2.1.1 
Package repository  View on CRAN 
Installation 
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