R Observatory: Metrics for ROCit version 2.1.2

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

ROCit

2.1.2

Performance Assessment of Binary Classifier with Visualization

4packages depend

25.6Kdownloads / year

1.0%test coverage

13/13checks pass

Overview

About

Maintained by Md Riaz Ahmed KhanFirst published 2019-01-313 releasesCRAN page ↗

Sensitivity (or recall or true positive rate), false positive rate, specificity, precision (or positive predictive value), negative predictive value, misclassification rate, accuracy, F-score- these are popular metrics for assessing performance of binary classifier for certain threshold. These metrics are calculated at certain threshold values. Receiver operating characteristic (ROC) curve is a common tool for assessing overall diagnostic ability of the binary classifier. Unlike depending on a certain threshold, area under ROC curve (also known as AUC), is a summary statistic about how well a binary classifier performs overall for the classification task. ROCit package provides flexibility to easily evaluate threshold-bound metrics. Also, ROC curve, along with AUC, can be obtained using different methods, such as empirical, binormal and non-parametric. ROCit encompasses a wide variety of methods for constructing confidence interval of ROC curve and AUC. ROCit also features the option of constructing empirical gains table, which is a handy tool for direct marketing. The package offers options for commonly used visualization, such as, ROC curve, KS plot, lift plot. Along with in-built default graphics setting, there are rooms for manual tweak by providing the necessary values as function arguments. ROCit is a powerful tool offering a range of things, yet it is very easy to use.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("ROCit", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-rocit

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-ROCit

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-ROCit

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 1.9 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 0.01

1.0%

Coverage · measured lines

100%

Documentation · exports

4

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 188 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 33% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 79%
Return-value docs: 56%
References docs: 11%

Downloads

25.6K

CRAN downloads in the past year

Rank #3,194 · ~70/day · ~2.1K/mo

Releases R versions

Daily download trend is not available in this view yet.

96830 days

3.7K90 days

25.6K1 year

Compare downloads with other packages →

Also on1.6K r2u14 autocran1.3K conda_forge

Dependencies

Declared dependencies

3 external dependencies (excludes base and recommended)

Depends (0)

none

Imports (4)

statsgraphicsutilsmethods

LinkingTo (0)

none

Suggests (3)

testthat knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

4direct

0indirect

ROCModels Rprofet adjROC DataVisualizations

Code & Tests

Datasets

People & History

People (2)

Maintainer (1)

Md Riaz Ahmed Khan

Author, Maintainer

Authors (2)

Md Riaz Ahmed Khan

Author, Maintainer

Thomas Brandenburger

Author

Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
2.1.2Latest
2024-05-16 · current release · diff ↗
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
2.1.1
2020-06-14 · diff ↗
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
1.1.1
2019-01-31
R
R 3.5.0 released · 2018-04-23

Package metadata

First published: 2019-01-31
Total releases: 3 / 7 yrs
License: GPL-3 OSI
Bundled data: 30 KB / 2 files
Download size: 169 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ROCit")

Format

Khan, M. R. A., & Brandenburger, T. (2024). ROCit: Performance Assessment of Binary Classifier with Visualization (Version 2.1.2) [Computer software]. https://doi.org/10.32614/CRAN.package.ROCit

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ROCit version 2.1.2 [Data set]. HJJB, LLC. Data release v2026-08-15. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-15, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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