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LogicForest (version 2.1.5)

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

313

Version

2.1.5

License

GPL-3

Maintainer

Melica Nikahd

Last Published

August 28th, 2026

Functions in LogicForest (2.1.5)

TTab

Truth table
logforest

Logic Forest & Logic Survival Forest
build.interactions

Building Interactions
predict.logforest

Predict Outcomes Using a Logic Forest Model
print.logforest

Print Method for Logic Forest Models
print.LFprediction

Print Method for Logic Forest Predictions
Perms

Generate All Permutations of N Variables
pimp.import

Predictor Importance – Variables and Interactions
pimp.mat.bin

Predictor Importance Matrix – Classification
p.combos

Generate All Combinations of N Variables with a Specified Conjunction Value
frame.logreg2

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

Predictor Importance Matrix – Regression
find.ctree

Find Complement of a Logic Regression Tree
proportion.positive

Proportion Positive Predictions
prime.imp

Extract Prime Variable Interactions from a Logic Regression Tree
predict.logreg2

Predict Method for Logic Regression Objects (Internal)