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staccuracy: Standardized Accuracy and Other Model Performance Metrics

Standardized accuracy (staccuracy) is framework for expressing accuracy scores such that 50% represents a reference level of performance and 100% is a perfect prediction. The 'staccuracy' package provides tools for creating staccuracy functions as well as some recommended staccuracy measures. It also provides functions for some classic performance metrics such as mean absolute error (MAE), root mean squared error (RMSE), and area under the receiver operating characteristic curve (AUCROC), as well as their winsorized versions when applicable.

Version: 0.2.0
Imports: cli, dplyr, purrr, rlang, stringr, tidyr
Suggests: testthat (≥ 3.0.0)
Published: 2024-11-06
DOI: 10.32614/CRAN.package.staccuracy
Author: Chitu Okoli ORCID iD [aut, cre]
Maintainer: Chitu Okoli <Chitu.Okoli at skema.edu>
BugReports: https://github.com/tripartio/staccuracy/issues
License: MIT + file LICENSE
URL: https://github.com/tripartio/staccuracy, https://tripartio.github.io/staccuracy/
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: staccuracy results

Documentation:

Reference manual: staccuracy.pdf

Downloads:

Package source: staccuracy_0.2.0.tar.gz
Windows binaries: r-devel: staccuracy_0.2.0.zip, r-release: staccuracy_0.2.0.zip, r-oldrel: staccuracy_0.2.0.zip
macOS binaries: r-release (arm64): staccuracy_0.2.0.tgz, r-oldrel (arm64): staccuracy_0.2.0.tgz, r-release (x86_64): staccuracy_0.2.0.tgz, r-oldrel (x86_64): staccuracy_0.2.0.tgz
Old sources: staccuracy archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.