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mcboost: Multi-Calibration Boosting

Implements 'Multi-Calibration Boosting' (2018) <https://proceedings.mlr.press/v80/hebert-johnson18a.html> and 'Multi-Accuracy Boosting' (2019) <doi:10.48550/arXiv.1805.12317> for the multi-calibration of a machine learning model's prediction. 'MCBoost' updates predictions for sub-groups in an iterative fashion in order to mitigate biases like poor calibration or large accuracy differences across subgroups. Multi-Calibration works best in scenarios where the underlying data & labels are unbiased, but resulting models are. This is often the case, e.g. when an algorithm fits a majority population while ignoring or under-fitting minority populations.

Version:0.4.4
Depends:R (≥ 3.1.0)
Imports:backports,checkmate (≥ 2.0.0),data.table (≥ 1.13.6),mlr3 (≥ 0.10),mlr3misc (≥ 0.8.0),mlr3pipelines (≥ 0.3.0),R6 (≥ 2.4.1),rmarkdown,rpart,glmnet
Suggests:curl,lgr,formattable,tidyverse,PracTools,mlr3learners,mlr3oml,neuralnet,paradox,knitr,ranger,xgboost,covr,testthat (≥ 3.1.0)
Published:2025-07-24
DOI:10.32614/CRAN.package.mcboost
Author:Florian PfistererORCID iD [aut], Susanne DandlORCID iD [ctb], Christoph KernORCID iD [ctb], Carolin Becker [ctb], Bernd BischlORCID iD [ctb], Sebastian Fischer [ctb, cre]
Maintainer:Sebastian Fischer <sebf.fischer at gmail.com>
BugReports:https://github.com/mlr-org/mcboost/issues
License:LGPL (≥ 3)
URL:https://github.com/mlr-org/mcboost
NeedsCompilation:no
Citation:mcboost citation info
Materials:README,NEWS
CRAN checks:mcboost results

Documentation:

Reference manual:mcboost.html ,mcboost.pdf
Vignettes:MCBoost - Basics and Extensions (source,R code)
MCBoost - Health Survey Example (source,R code)

Downloads:

Package source: mcboost_0.4.4.tar.gz
Windows binaries: r-devel:mcboost_0.4.4.zip, r-release:mcboost_0.4.4.zip, r-oldrel:mcboost_0.4.4.zip
macOS binaries: r-release (arm64):mcboost_0.4.4.tgz, r-oldrel (arm64):mcboost_0.4.4.tgz, r-release (x86_64):mcboost_0.4.4.tgz, r-oldrel (x86_64):mcboost_0.4.4.tgz
Old sources: mcboost archive

Linking:

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