gpleiss / equalized_odds_and_calibration Goto Github PK
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License: MIT License
Code and data for the experiments in "On Fairness and Calibration"
License: MIT License
When testing the equalized odds algorithm on my data, I checked the metrics. I found that it only diminishes the difference between FP rates, but it actually greatly increased the difference for FN rates. This does not seem allign with Equalized Odds, AFAIK.
Original group 0 model:
Group size: 943.000
Prediction Accuracy: 0.690
FP rate: 0.113
FN rate: 0.196
Original group 1 model:
Group size: 641.000
Prediction Accuracy: 0.771
FP rate: 0.062
FN rate: 0.167
Equalized odds group 0 model:
Group size: 943.000
Prediction Accuracy: 0.652
FP rate: 0.063
FN rate: 0.285
Equalized odds group 1 model:
Group size: 641.000
Prediction Accuracy: 0.761
FP rate: 0.076
FN rate: 0.162
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