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ICML2021 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking.

Python 97.97% Emacs Lisp 2.03%

metacal's Introduction

Meta-Cal

This repository implements our ICML2021 paper: Meta-Cal: Well-controlled Post-hoc Calibration by Ranking.

installation

git clone https://github.com/maxc01/metacal
cd metacal
poetry install

usage

See the test code.

cd metacal/tests/
python test_metacal.py

note

As we’ve mentioned in the main paper:

To ensure the independence assumption, the training data of Meta-Cal should be different from the data set used to train the multi-class classifier.

citation

@inproceedings{Ma2021a,
  TITLE = {Meta-Cal: Well-controlled Post-hoc Calibration by Ranking},
  AUTHOR = {Ma, Xingchen and Blaschko, Matthew B.},
  BOOKTITLE = {International Conference on Machine Learning},
  YEAR = {2021},
}

metacal's People

Contributors

maxc01 avatar

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