• Corpus ID: 233394448

Sampling Permutations for Shapley Value Estimation

@article{Mitchell2022SamplingPF,
  title={Sampling Permutations for Shapley Value Estimation},
  author={Rory Mitchell and Joshua N. Cooper and Eibe Frank and Geoffrey Holmes},
  journal={ArXiv},
  year={2022},
  volume={abs/2104.12199}
}
Game-theoretic attribution techniques based on Shapley values are used to interpret black-box machine learning models, but their exact calculation is generally NP-hard, requiring approximation methods for non-trivial models. As the computation of Shapley values can be expressed as a summation over a set of permutations, a common approach is to sample a subset of these permutations for approximation. Unfortunately, standard Monte Carlo sampling methods can exhibit slow convergence, and more… 

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