swMATH ID: 39771
Software Authors: Florian Pfisterer, Susanne Dandl, Christoph Kern, Bernd Bischl
Description: R package mcboost: Multi-Calibration Boosting. Implements ’Multi-Calibration Boosting’ (2018) <https://proceedings.mlr.press/v80/hebert-johnson18a.html> and ’Multi-Accuracy Boosting’ (2019) <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.
Homepage: https://cran.r-project.org/web/packages/mcboost/index.html
Source Code:  https://github.com/cran/mcboost
Dependencies: R
Keywords: JOSS; Journal of Open Source Software; R; R package; mcboost; Multi-Calibration Boosting; Multi-Calibration
Related Software: Python; mlr3; R
Cited in: 0 Documents

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