<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Logic Forest</dc:title>
  <dc:title>R package LogicForest version 2.1.4</dc:title>
  <dc: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) &lt;doi:10.1093/bioinformatics/btq354&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 2.10)</dc:relation>
  <dc:relation>Imports: LogicReg, methods, survival, utils</dc:relation>
  <dc:relation>Suggests: data.table</dc:relation>
  <dc:creator>Melica Nikahd &lt;melica.nikahd@osumc.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Bethany Wolf [aut],
  Melica Nikahd [ctb, cre],
  Andrew Gothard [ctb],
  Madison Hyer [ctb]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2026-04-03</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=LogicForest</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.LogicForest</dc:identifier>
</oai_dc:dc>
