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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 7: AAAI-21 Technical Tracks 7

On the Tractability of SHAP Explanations

February 1, 2023

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Authors

Guy Van den Broeck

UCLA


Anton Lykov

UCLA


Maximilian Schleich

University of Washington


Dan Suciu

University of Washington


DOI:

10.1609/aaai.v35i7.16806


Abstract:

SHAP explanations are a popular feature-attribution mechanism for explainable AI. They use game-theoretic notions to measure the influence of individual features on the prediction of a machine learning model. Despite a lot of recent interest from both academia and industry, it is not known whether SHAP explanations of common machine learning models can be computed efficiently. In this paper, we establish the complexity of computing the SHAP explanation in three important settings. First, we consider fully-factorized data distributions, and show that the complexity of computing the SHAP explanation is the same as the complexity of computing the expected value of the model. This fully-factorized setting is often used to simplify the SHAP computation, yet our results show that the computation can be intractable for commonly used models such as logistic regression. Going beyond fully-factorized distributions, we show that computing SHAP explanations is already intractable for a very simple setting: computing SHAP explanations of trivial classifiers over naive Bayes distributions. Finally, we show that even computing SHAP over the empirical distribution is #P-hard.

Topics: AAAI

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HOW TO CITE:

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu On the Tractability of SHAP Explanations Proceedings of the AAAI Conference on Artificial Intelligence (2021) 6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu On the Tractability of SHAP Explanations AAAI 2021, 6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu (2021). On the Tractability of SHAP Explanations. Proceedings of the AAAI Conference on Artificial Intelligence, 6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu. On the Tractability of SHAP Explanations. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu. 2021. On the Tractability of SHAP Explanations. "Proceedings of the AAAI Conference on Artificial Intelligence". 6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu. (2021) "On the Tractability of SHAP Explanations", Proceedings of the AAAI Conference on Artificial Intelligence, p.6505-6513

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu, "On the Tractability of SHAP Explanations", AAAI, p.6505-6513, 2021.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu. "On the Tractability of SHAP Explanations". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu. "On the Tractability of SHAP Explanations". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 6505-6513.

Guy Van den Broeck||Anton Lykov||Maximilian Schleich||Dan Suciu. On the Tractability of SHAP Explanations. AAAI[Internet]. 2021[cited 2023]; 6505-6513.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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