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rocc  

ROC Based Classification
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("rocc", "1.3")



Attach the package and use:
library("rocc")
Maintained by
Martin Lauss
[Scholar Profile | Author Map]
First Published: 2010-04-15
Latest Update: 2019-12-06
Description:
Functions for a classification method based on receiver operating characteristics (ROC). Briefly, features are selected according to their ranked AUC value in the training set. The selected features are merged by the mean value to form a meta-gene. The samples are ranked by their meta-gene value and the meta-gene threshold that has the highest accuracy in splitting the training samples is determined. A new sample is classified by its meta-gene value relative to the threshold. In the first place, the package is aimed at two class problems in gene expression data, but might also apply to other problems.
How to cite:
Martin Lauss (2010). rocc: ROC Based Classification. R package version 1.3, https://cran.r-project.org/web/packages/rocc. Accessed 16 Mar. 2025.
Previous versions and publish date:
1.0 (2010-04-15 15:49), 1.2 (2010-10-04 12:03)
Other packages that cited rocc R package
View rocc citation profile
Other R packages that rocc depends, imports, suggests or enhances
Complete documentation for rocc
Functions, R codes and Examples using the rocc R package
Some associated functions: o.rocc . p.rocc . tr.rocc . 
Some associated R codes: o.rocc.R . p.rocc.R . tr.rocc.R .  Full rocc package functions and examples
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