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Python code for Dirichlet calibration

Project description

Dirichlet Calibration Python implementation

This is a Python implementation of the Dirichlet Calibration presented in Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration at NeurIPS 2019.

Installation

# Clone the repository
git clone git@github.com:dirichletcal/dirichlet_python.git
# Go into the folder
cd dirichlet_python
# Create a new virtual environment with Python3
python3.6 -m venv venv
# Load the generated virtual environment
source venv/bin/activate
# Upgrade pip
pip install --upgrade pip
# Install all the dependencies
pip install -r requirements.txt
pip install --upgrade jaxlib

Unittest

python -m unittest discover dirichletcal

Cite

If you use this code in a publication please cite the following paper

@inproceedings{kull2019dircal,
  title={Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration},
  author={Kull, Meelis and Nieto, Miquel Perello and K{\"a}ngsepp, Markus and Silva Filho, Telmo and Song, Hao and Flach, Peter},
  booktitle={Advances in Neural Information Processing Systems},
  pages={12295--12305},
  year={2019}
}

Examples

You can find some examples on how to use this package in the folder examples

Project details


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Source Distribution

dirichletcal-0.2.dev1.tar.gz (10.8 kB view hashes)

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