logicDT: Identifying Interactions Between Binary Predictors

A global statistical learning method which tries to find the best set of predictors and interactions between predictors for modeling binary or quantitative response data. Several search algorithms and ensembling techniques are implemented allowing for finetuning the method to the specific problem. Interactions with single quantitative covariables can be properly taken into account by also splitting after those or by fitting local four parameter logistic models.

Version: 1.0.2
Imports: graphics, stats, utils
Published: 2022-04-26
Author: Michael Lau ORCID iD [aut, cre]
Maintainer: Michael Lau <michael.lau at hhu.de>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
CRAN checks: logicDT results


Reference manual: logicDT.pdf


Package source: logicDT_1.0.2.tar.gz
Windows binaries: r-devel: logicDT_1.0.2.zip, r-release: logicDT_1.0.2.zip, r-oldrel: logicDT_1.0.2.zip
macOS binaries: r-release (arm64): logicDT_1.0.2.tgz, r-oldrel (arm64): logicDT_1.0.2.tgz, r-release (x86_64): logicDT_1.0.2.tgz, r-oldrel (x86_64): logicDT_1.0.2.tgz
Old sources: logicDT archive


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