Published August 3, 2021 | Version v.0.3.3
Software Open

mcboost: Multi-Calibration Boosting for R

Authors/Creators

  • 1. LMU Munich
  • 2. University of Mannheim
  • 3. Princeton University
  • 4. UC Berkely

Description

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.

Files

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Additional details

Related works

Is continued by
https://github.com/mlr-org/mcboost (URL)