Towards A Rigorous Science of Interpretable Machine Learning · HackerPapers discussions

Towards A Rigorous Science of Interpretable Machine Learning — mentioned by 1_over_n

Sat, 04 Jan 2020 23:48:37 GMT

This is a great point. There is a general lack of understanding about what it means for models to be interpretable & explainable. These words get thrown around often by people who don't understand the definition, and also the trade off with accuracy. Some papers i found interesting on the subject: https://arxiv.org/abs/1606.03490 https://arxiv.org/abs/1707.03886 https://arxiv.org/abs/1806.07552 https://arxiv.org/abs/1702.08608 (i found this was a good sumary of the issues)

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Towards A Rigorous Science of Interpretable Machine Learning — mentioned by jclos

Thu, 19 Jul 2018 12:30:27 GMT

Interpretable ML [1] is a small online book on interpretable methods. Even if the content itself is rather shallow, it has links to a lot of more focused papers on the topic. Towards A Rigorous Science of Interpretable Machine Learning is one of the most thorough papers on interpretable ML that I have come across. The main author, Finale Doshi-Velez, has a done a lot of interesting work on interpretability [3]. [1] https://christophm.github.io/interpretable-ml-book/ [2] https://arxiv.org/abs/1702.08608 [3] https://finale.seas.harvard.edu/publications

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