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LogicForest (version 2.1.1)

Logic Forest

Description

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) .

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Version

Install

install.packages('LogicForest')

Monthly Downloads

264

Version

2.1.1

License

GPL-3

Maintainer

Melica Nikahd

Last Published

March 13th, 2024

Functions in LogicForest (2.1.1)

p.combos

Internal Logic Forest Functions
logforest

Logic Forest
pimp.import

Internal Logic Forest Functions
prime.imp

Internal Logic Forest Functions
TTab

Internal Logic Forest Functions
LF.data

LF.data
pimp.mat

Internal Logic Forest Functions
Perms

Internal Logic Forest Functions
proportion.positive

Internal Logic Forest Functions