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rationalization [2019/01/12 12:10]
admin
rationalization [2019/01/13 20:20] (current)
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 when a model has made a sizeable mistake. These findings emphasize the importance of studying how models are when a model has made a sizeable mistake. These findings emphasize the importance of studying how models are
 presented to people and empirically verifying that interpretable models achieve their intended effects on end users. presented to people and empirically verifying that interpretable models achieve their intended effects on end users.
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 +https://​arxiv.org/​abs/​1703.04730 Understanding Black-box Predictions via Influence Functions
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 +https://​christophm.github.io/​interpretable-ml-book/​proto.html
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