The Mythos of Model Interpretability
The Mythos of Model Interpretability
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DOI:
10.1145/3233231
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发表时间:
2018-10-01
影响因子:
22.7
通讯作者:
Lipton, Zachary C.
中科院分区:
文献类型:
--
作者:
Lipton, Zachary C.
Supervised machine-learning models boast remarkable predictive capabilities. But can you trust your model? Will it work in deployment? What else can it tell you about the world?