Machine Learning and Deep Learning Interpretability

Shapley value decomposition of a model, a pay-off concept from cooperative game theory.

Last updated on Sat, Jan 30, 2021 1 min read Machine Learning, Deep Learning

Molnar, C. (2020). Interpretable Machine Learning: A Guide for Making Black Box Models Explainable. https://christophm.github.io/interpretable-ml-book/

Joseph, A. (2019). Shapley regressions: A framework for statistical inference on machine learning models. In arXiv. https://doi.org/10.2139/ssrn.3351091

Camburu, O. M. (2020). Explaining Deep Neural Networks. In arXiv. https://arxiv.org/abs/2010.01496

Machine Learning ML Deep Learning DL

Machine Learning and Deep Learning Interpretability

Pak Shing Ho

Economist

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