Package: staccuracy 0.2.2

staccuracy: Standardized Accuracy and Other Model Performance Metrics

Standardized accuracy (staccuracy) is a 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.

Authors:Chitu Okoli [aut, cre]

staccuracy_0.2.2.tar.gz
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staccuracy_0.2.2.tar.gz(r-4.5-noble)staccuracy_0.2.2.tar.gz(r-4.4-noble)
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staccuracy.pdf |staccuracy.html
staccuracy/json (API)
NEWS

# Install 'staccuracy' in R:
install.packages('staccuracy', repos = c('https://tripartio.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tripartio/staccuracy/issues

Pkgdown site:https://tripartio.github.io

On CRAN:

Conda:

4.18 score 1 stars 2 packages 4 scripts 304 downloads 14 exports 21 dependencies

Last updated 30 days agofrom:a112bf9df3. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 25 2025
R-4.5-winOKMar 25 2025
R-4.5-macOKMar 25 2025
R-4.5-linuxOKMar 25 2025
R-4.4-winOKMar 25 2025
R-4.4-macOKMar 25 2025
R-4.4-linuxOKMar 25 2025
R-4.3-winOKMar 25 2025
R-4.3-macOKMar 25 2025

Exports:aucrocmadmaereg_aucrocrmsesa_diffsa_mae_madsa_rmse_sdsa_wmae_madsa_wrmse_sdstaccuracywin_maewin_rmsewinsorize

Dependencies:clicpp11dplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr