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 [aut], Susanne Dandl [ctb], Christoph Kern [ctb], Carolin Becker [ctb], Bernd Bischl [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 resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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