Flexible Tool for Bias Detection, Visualization, and Mitigation
All cutoffs
Calculate fairness metrics in groups
Ceteris paribus cutoff
Choose metric
Confusion matrix
Disparate impact remover
Expand Fairness Object
Fairness check regression
Fairness check
Fairness heatmap
Fairness PCA
Fairness radar
Group confusion matrices
Group metric
Group model performance
Metric scores
Performance and fairness
Plot all cutoffs
Ceteris paribus cutoff plot
Plot chosen metric
Plot fairness object
Plot fairmodels
Plot Heatmap
Plot fairness object
Plot fairness PCA
Plot fairness radar
Plot fairness regression object
Plot group metric
Plot metric scores
Plot fairness and performance
Stack metrics
Plot stacked Metrics
Pre-process data
Print all cutoffs
Print ceteris paribus cutoff
Print chosen metric
Print fairness heatmap
Print Fairness Object
Print fairness PCA
Print fairness radar
Print Fairness Regression Object
Print group metric
Print metric scores data
Print performance and fairness
Print stacked metrics
Regression metrics
Resample
Reweight
Reject Option based Classification pivot
Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented. Package also supports calculating fairness metrics for regression models. Find more details in (Wiśniewski, Biecek (2021)) <doi:10.48550/arXiv.2104.00507>.