Predictive and Causal Implications of using Shapley Value for Model Interpretation

Sisi Ma, Roshan Tourani. Predictive and Causal Implications of using Shapley Value for Model Interpretation. In Thuc Duy Le, Lin Liu 0003, Kun Zhang 0001, Emre Kiciman, Peng Cui 0001, Aapo Hyvärinen, editors, Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), San Diego, CA, USA, 24 August 2020. Volume 127 of Proceedings of Machine Learning Research, pages 23-38, PMLR, 2020. [doi]

@inproceedings{MaT20-3,
  title = {Predictive and Causal Implications of using Shapley Value for Model Interpretation},
  author = {Sisi Ma and Roshan Tourani},
  year = {2020},
  url = {http://proceedings.mlr.press/v127/ma20a.html},
  researchr = {https://researchr.org/publication/MaT20-3},
  cites = {0},
  citedby = {0},
  pages = {23-38},
  booktitle = {Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), San Diego, CA, USA, 24 August 2020},
  editor = {Thuc Duy Le and Lin Liu 0003 and Kun Zhang 0001 and Emre Kiciman and Peng Cui 0001 and Aapo Hyvärinen},
  volume = {127},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}