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LogicForest (version 2.1.3)

Logic Forest

Description

Logic Forest is an ensemble machine learning method that identifies important and interpretable combinations of binary predictors using logic regression trees to model complex relationships with an outcome. Wolf, B.J., Slate, E.H., Hill, E.G. (2010) .

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Version

Install

install.packages('LogicForest')

Monthly Downloads

213

Version

2.1.3

License

GPL-3

Maintainer

Melica Nikahd

Last Published

February 13th, 2026

Functions in LogicForest (2.1.3)

print.LFprediction

Print Method for Logic Forest Predictions
prime.imp

Extract Prime Variable Interactions from a Logic Regression Tree
find.ctree

Find Complement of a Logic Regression Tree
Perms

Generate All Permutations of N Variables
build.interactions

Building Interactions
logforest

Logic Forest & Logic Survival Forest
predict.logforest

Predict Outcomes Using a Logic Forest Model
print.logforest

Print Method for Logic Forest Models
p.combos

Generate All Combinations of N Variables with a Specified Conjunction Value
TTab

Truth table
predict.logreg2

Predict Method for Logic Regression Objects (Internal)
pimp.import

Predictor Importance – Variables and Interactions
pimp.mat.bin

Predictor Importance Matrix – Classification
proportion.positive

Proportion Positive Predictions
frame.logreg2

Evaluate Predicted Values for Logic Regression Trees
pimp.mat.nonbin

Predictor Importance Matrix – Regression