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staccuracy  

Standardized Accuracy and Other Model Performance Metrics
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("staccuracy", "0.2.2")



Attach the package and use:
library("staccuracy")
Maintained by
Chitu Okoli
[Scholar Profile | Author Map]
First Published: 2024-10-03
Latest Update: 2024-10-03
Description:
Standardized accuracy (staccuracy) is framework for expressing accuracy scores such that 50% represents a reference level of performance and 100% is 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.
How to cite:
Chitu Okoli (2024). staccuracy: Standardized Accuracy and Other Model Performance Metrics. R package version 0.2.2, https://cran.r-project.org/web/packages/staccuracy. Accessed 03 Apr. 2025.
Previous versions and publish date:
0.1.0 (2024-10-03 21:10), 0.2.0 (2024-11-06 13:50)
Other packages that cited staccuracy R package
View staccuracy citation profile
Other R packages that staccuracy depends, imports, suggests or enhances
Complete documentation for staccuracy
Functions, R codes and Examples using the staccuracy R package
Full staccuracy package functions and examples
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