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OneR: One Rule Machine Learning Classification Algorithm with Enhancements

Implements the One Rule (OneR) Machine Learning classification algorithm (Holte, R.C. (1993) <doi:10.1023/A:1022631118932>) with enhancements for sophisticated handling of numeric data and missing values together with extensive diagnostic functions. It is useful as a baseline for machine learning models and the rules are often helpful heuristics.

Version: 2.2
Depends: R (≥ 2.10)
Suggests: knitr, rmarkdown
Published: 2017-05-05
DOI: 10.32614/CRAN.package.OneR
Author: Holger von Jouanne-Diedrich
Maintainer: Holger von Jouanne-Diedrich <holger.jouanne-diedrich at h-ab.de>
BugReports: https://github.com/vonjd/OneR/issues
License: MIT + file LICENSE
URL: https://github.com/vonjd/OneR
NeedsCompilation: no
Materials: README NEWS
In views: MachineLearning
CRAN checks: OneR results

Documentation:

Reference manual: OneR.pdf
Vignettes: OneR - Establishing a New Baseline for Machine Learning Classification Models

Downloads:

Package source: OneR_2.2.tar.gz
Windows binaries: r-devel: OneR_2.2.zip, r-release: OneR_2.2.zip, r-oldrel: OneR_2.2.zip
macOS binaries: r-release (arm64): OneR_2.2.tgz, r-oldrel (arm64): OneR_2.2.tgz, r-release (x86_64): OneR_2.2.tgz, r-oldrel (x86_64): OneR_2.2.tgz
Old sources: OneR archive

Reverse dependencies:

Reverse imports: tidybins

Linking:

Please use the canonical form https://CRAN.R-project.org/package=OneR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.