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
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

Downloads:

Reference manual: supervisedPRIM.pdf
Package source: supervisedPRIM_2.0.0.tar.gz
Windows binaries: r-devel: supervisedPRIM_2.0.0.zip, r-devel-gcc8: supervisedPRIM_2.0.0.zip, r-release: supervisedPRIM_2.0.0.zip, r-oldrel: supervisedPRIM_2.0.0.zip
OS X binaries: r-release: supervisedPRIM_2.0.0.tgz, r-oldrel: supervisedPRIM_2.0.0.tgz
Old sources: supervisedPRIM archive

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