Corpus ID: 202660574

The Explanation Game: Explaining Machine Learning Models with Cooperative Game Theory

@article{Merrick2019TheEG,
  title={The Explanation Game: Explaining Machine Learning Models with Cooperative Game Theory},
  author={Luke Merrick and Ankur Taly},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.08128}
}

Luke Merrick, Ankur Taly

Published 2019

Mathematics, Computer Science

ArXiv

A number of techniques have been proposed to explain a machine learning (ML) model's prediction by attributing it to the corresponding input features. Popular among these are techniques that apply the Shapley value method from cooperative game theory. While existing papers focus on the axiomatic motivation of Shapley values, and efficient techniques for computing them, they neither justify the game formulations used nor address the uncertainty implicit in their methods' outputs. For instance… CONTINUE READING

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