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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 cross-validation 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 |
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Author | Bethany Wolf [aut], Melica Nikahd [ctb, cre], Madison Hyer [ctb] |
Maintainer | Melica Nikahd <melica.nikahd@osumc.edu> |
License | GPL-3 |
Version | 2.1.1 |
Package repository | View on CRAN |
Installation |
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