mlr3fairness
0.4.0Fairness Auditing and Debiasing for 'mlr3'
Overview
Integrates fairness auditing and bias mitigation methods for the 'mlr3' ecosystem. This includes fairness metrics, reporting tools, visualizations and bias mitigation techniques such as "Reweighing" described in 'Kamiran, Calders' (2012) doi:10.1007/s10115-011-0463-8 and "Equalized Odds" described in 'Hardt et al.' (2016) https://papers.nips.cc/paper/2016/file/9d2682367c3935defcb1f9e247a97c0d-Paper.pdf. Integration with 'mlr3' allows for auditing of ML models as well as convenient joint tuning of machine learning algorithms and debiasing methods.
Install
Health
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-1713 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- WARNING2026-05-1012 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Downloads
Repository
Dependencies
Code & Tests
- Cyclomatic complexity
- 1.0 median / 5 max
- Test cases
- 71 / 0.43 per code line
- Documented parameters
- 100%
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
42 13 exported
Complexity
1.9 avg / 5 max
Call network
42 nodes / 14 edges
Test coverage has not been measured for this package yet; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
4 releases. Pick two to compare their code metrics. R releases are shown for context.
Package metadata
- First published
- 2022-05-12
- Total releases
- 4 / 4 yrs
- License
- LGPL-3 OSI
- Minimum R
- ≥ 3.4.0
- Bundled data
- 226 KB / 3 files
- Download size
- 540 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet