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LogicForest  

Logic Forest
View on CRAN: Click here


Download and install LogicForest package within the R console
Install from CRAN:
install.packages("LogicForest")

Install from Github:
library("remotes")
install_github("cran/LogicForest")

Install by package version:
library("remotes")
install_version("LogicForest", "2.1.1")



Attach the package and use:
library("LogicForest")
Maintained by
Melica Nikahd
[Scholar Profile | Author Map]
First Published: 2010-07-25
Latest Update: 2024-03-13
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) .
How to cite:
Melica Nikahd (2010). LogicForest: Logic Forest. R package version 2.1.1, https://cran.r-project.org/web/packages/LogicForest. Accessed 17 Feb. 2025.
Previous versions and publish date:
1.0 (2010-07-25 13:06), 2.0.0 (2012-07-23 10:35), 2.1.0 (2014-09-19 00:46)
Other packages that cited LogicForest R package
View LogicForest citation profile
Other R packages that LogicForest depends, imports, suggests or enhances
Complete documentation for LogicForest
Functions, R codes and Examples using the LogicForest R package
Full LogicForest package functions and examples
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