Introduction

This is the code that reproduces experiments in (paper)

Requirements

The code is tested on python3.6 and pytorch 1.5. Also requires scipy, sklearn, PIL packages to run.

Running the code

To run the code without post-training recalibration, use

python train.py --gpu=0 

To apply post-training recalibration, use

python train.py --gpu=0 --recalibrate

You can also apply group recalibration for a certain feature, for example

python train.py --gpu=0 --recalibrate --group_idx=2 

recalibrates the subgroups partitioned by the second input feature. The partition currently is based on greater or less than the median.

You can use the code in plot.ipynb to reproduce the calibration error comparison plot between different methods.