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supervisedPRIM  

Supervised Classification Learning and Prediction using Patient Rule Induction Method (PRIM)
View on CRAN: Click here


Download and install supervisedPRIM package within the R console
Install from CRAN:
install.packages("supervisedPRIM")

Install from Github:
library("remotes")
install_github("cran/supervisedPRIM")

Install by package version:
library("remotes")
install_version("supervisedPRIM", "2.0.0")



Attach the package and use:
library("supervisedPRIM")
Maintained by
David Shaub
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-08-22
Latest Update: 2016-10-01
Description:
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.
How to cite:
David Shaub (2016). supervisedPRIM: Supervised Classification Learning and Prediction using Patient Rule Induction Method (PRIM). R package version 2.0.0, https://cran.r-project.org/web/packages/supervisedPRIM. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:10), 1.0.1 (2016-08-22 10:00)
Other packages that cited supervisedPRIM R package
View supervisedPRIM citation profile
Other R packages that supervisedPRIM depends, imports, suggests or enhances
Complete documentation for supervisedPRIM
Functions, R codes and Examples using the supervisedPRIM R package
Some associated functions: predict.supervisedPRIM . supervisedPRIM . 
Some associated R codes: ensemblePRIM.R . supervisedPRIM-package.R . supervisedPRIM.R .  Full supervisedPRIM package functions and examples
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