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probcal  

Calibration of Binary and Multiclass Probabilities
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("probcal", "0.2.0")



Attach the package and use:
library("probcal")
Maintained by
Pedro Rafael Diniz Marinho
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-09
Latest Update: 2026-07-09
Description:
Provides S3 calibrators, metrics, and diagnostics for binary and multiclass probability calibration. Binary methods include Platt scaling, temperature scaling, beta calibration, histogram binning, and isotonic regression. Multiclass methods include temperature scaling, vector scaling, Dirichlet calibration, and a one-vs-rest wrapper for the binary calibrators. A calibration-inference layer adds debiased calibration errors, bootstrap confidence intervals, and a kernel calibration hypothesis test for binary and multiclass predictions, including the strong (canonical) multiclass case. Methods follow Platt (1999, ISBN:9780262194488), Zadrozny and Elkan (2002) <doi:10.1145/775047.775151>, Guo et al. (2017) <https://proceedings.mlr.press/v70/guo17a.html>, Kull et al. (2017) <doi:10.1214/17-EJS1338SI>, Kull et al. (2019) <doi:10.48550/arXiv.1910.12656>, Widmann et al. (2019) <doi:10.48550/arXiv.1910.11385>, and Kumar et al. (2019) <doi:10.48550/arXiv.1909.10155>.
How to cite:
Pedro Rafael Diniz Marinho (2026). probcal: Calibration of Binary and Multiclass Probabilities. R package version 0.2.0, https://cran.r-project.org/web/packages/probcal. Accessed 24 Oct. 2026.
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