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mcboost  

Multi-Calibration Boosting
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mcboost", "0.4.3")



Attach the package and use:
library("mcboost")
Maintained by
Sebastian Fischer
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-09
Latest Update: 2022-08-18
Description:
Implements 'Multi-Calibration Boosting' (2018) and 'Multi-Accuracy Boosting' (2019) 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.
How to cite:
Sebastian Fischer (2021). mcboost: Multi-Calibration Boosting. R package version 0.4.3, https://cran.r-project.org/web/packages/mcboost. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.3.0 (2021-06-09 14:30), 0.3.3.0 (2021-08-03 11:50), 0.4.0 (2022-01-18 18:52), 0.4.1 (2022-04-25 15:10), 0.4.2 (2022-08-18 14:30)
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