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LogicForest (version 2.1.4)

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

224

Version

2.1.4

License

GPL-3

Maintainer

Melica Nikahd

Last Published

April 3rd, 2026

Functions in LogicForest (2.1.4)

predict.logreg2

Predict Method for Logic Regression Objects (Internal)
TTab

Truth table
logforest

Logic Forest & Logic Survival Forest
build.interactions

Building Interactions
print.logforest

Print Method for Logic Forest Models
predict.logforest

Predict Outcomes Using a Logic Forest Model
print.LFprediction

Print Method for Logic Forest Predictions
pimp.mat.bin

Predictor Importance Matrix – Classification
pimp.mat.nonbin

Predictor Importance Matrix – Regression
Perms

Generate All Permutations of N Variables
find.ctree

Find Complement of a Logic Regression Tree
proportion.positive

Proportion Positive Predictions
frame.logreg2

Evaluate Predicted Values for Logic Regression Trees
prime.imp

Extract Prime Variable Interactions from a Logic Regression Tree
p.combos

Generate All Combinations of N Variables with a Specified Conjunction Value
pimp.import

Predictor Importance – Variables and Interactions