The Mythos of Model Interpretability The Mythos of Model Interpretability
Paper summary This paper 1. Explains why we want "interpretability" and hence what it can mean, depending on what we want. 2. Properties of interpretable models 3. Gives examples It is easy to read. A must-read for everybody who wants to know about interpretability of models! ## Why we want interpretability * Trust * Intelligibility: Confidence in models accuracy vs * Transparency: Understanding the model ## How to achieve interpretability * Post-hoc explanations (saliency maps) * t-SNE
The Mythos of Model Interpretability
Zachary C. Lipton
arXiv e-Print archive - 2016 via arXiv
Keywords: cs.LG, cs.AI, cs.CV, cs.NE, stat.ML


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