/PartialOrdinalShapley

Official code for our paper "Data valuation: The partial ordinal Shapley value for machine learning"

Primary LanguagePythonMIT LicenseMIT

Data valuation: The partial ordinal Shapley value for machine learning

Code for implementation of "Data valuation: The partial ordinal Shapley value for machine learning".

This repository builds on the DataShapley repository and contains implementations of TMC, CMC and CTMC algorithm.

Dataset

Requirments

Python, NumPy, Tensorflow 1.12, Scikit-learn, Matplotlib

Example command

args:

  • dataset_name: Name of dataset (['wine', 'cancer', 'adult_s'])
  • results_path: path for saving results
  • tol: Truncated factor
  • ratio: ratio for CMC and CTMC
  • noise: ratio of noisy label
$ python3 main.py --dataset_name cancer --tol 0.05 --start_run 0 --num_run 5 --noise 0.2

Reference

If you find our code useful for your research, please cite our paper.

@misc{liu2023data,
      title={Data valuation: The partial ordinal Shapley value for machine learning}, 
      author={Jie Liu and Peizheng Wang and Chao Wu},
      year={2023},
      eprint={2305.01660},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}