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: | 0.4.3 |
| 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: | 2024-04-12 |
| DOI: | 10.32614/CRAN.package.mcboost |
| Author: | Florian Pfisterer |
| 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.pdf |
| Vignettes: |
MCBoost - Basics and Extensions MCBoost - Health Survey Example |
Downloads:
| Package source: | mcboost_0.4.3.tar.gz |
| Windows binaries: | r-devel: mcboost_0.4.3.zip, r-release: mcboost_0.4.3.zip, r-oldrel: mcboost_0.4.3.zip |
| macOS binaries: | r-release (arm64): mcboost_0.4.3.tgz, r-oldrel (arm64): mcboost_0.4.3.tgz, r-release (x86_64): mcboost_0.4.3.tgz, r-oldrel (x86_64): mcboost_0.4.3.tgz |
| Old sources: | mcboost archive |
Linking:
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