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年10月01日
Author: David Shaub [aut, cre]
Maintainer: David Shaub <davidshaub at gmx.com>
License: GPL-3
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: supervisedPRIM results

Documentation:

Downloads:

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

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