The authors define interpretability for machine learning, specify when it is required, and propose a taxonomy for its rigorous evaluation while identifying open research questions.
Mind the gap: A generative approach to interpretable feature selection and extraction
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Towards A Rigorous Science of Interpretable Machine Learning
The authors define interpretability for machine learning, specify when it is required, and propose a taxonomy for its rigorous evaluation while identifying open research questions.