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supervisedPRIM: Supervised Classification Learning and Prediction using Patient Rule Induction Method (PRIM)

The Patient Rule Induction Method (PRIM) is typically used for "bump hunting" data mining to identify regions with abnormally high concentrations of data with large or small values. This package extends this methodology so that it can be applied to binary classification problems and used for prediction.

Version: 2.0.0
Depends: R (≥ 3.1.1), stats, prim (≥ 1.0.16)
Suggests: kernlab, testthat
Published: 2016-10-01
DOI: 10.32614/CRAN.package.supervisedPRIM
Author: David Shaub [aut, cre]
Maintainer: David Shaub <davidshaub at gmx.com>
BugReports: https://github.com/dashaub/supervisedPRIM/issues
License: GPL-3
URL: https://github.com/dashaub/supervisedPRIM
NeedsCompilation: no
Materials: README NEWS
CRAN checks: supervisedPRIM results

Documentation:

Reference manual: supervisedPRIM.pdf

Downloads:

Package source: supervisedPRIM_2.0.0.tar.gz
Windows binaries: r-devel: supervisedPRIM_2.0.0.zip, r-release: supervisedPRIM_2.0.0.zip, r-oldrel: supervisedPRIM_2.0.0.zip
macOS binaries: r-release (arm64): supervisedPRIM_2.0.0.tgz, r-oldrel (arm64): supervisedPRIM_2.0.0.tgz, r-release (x86_64): supervisedPRIM_2.0.0.tgz, r-oldrel (x86_64): supervisedPRIM_2.0.0.tgz
Old sources: supervisedPRIM archive

Linking:

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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.