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modelcardr  

Machine Learning Prediction Auditing and Model Card Reporting
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("modelcardr", "0.1.0")



Attach the package and use:
library("modelcardr")
Maintained by
Georgios P. Georgiou
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-30
Latest Update: 2026-07-30
Description:
Audits predictions from fitted machine learning models without requiring retraining or access to the fitted model object. It supports binary classification, multiclass classification, and regression, providing performance metrics with bootstrap confidence intervals, calibration and threshold analyses, residual diagnostics, subgroup comparisons, user-defined acceptance criteria, risk warnings, and self-contained reports. For binary-classification and regression models, the package can also assemble and render structured model cards documenting intended use, evaluation data, performance, subgroup results, assumptions, and limitations. The model-card reporting approach is described by Mitchell et al. (2019) "Model Cards for Model Reporting" <doi:10.1145/3287560.3287596>.
How to cite:
Georgios P. Georgiou (2026). modelcardr: Machine Learning Prediction Auditing and Model Card Reporting. R package version 0.1.0, https://cran.r-project.org/web/packages/modelcardr. Accessed 24 Oct. 2026.
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