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This scenario is the same as any other machine learning environment: The output is prediction with a % confidence score. This means the threshold can be set su
by dangero 10y ago
This scenario is the same as any other machine learning environment:
The output is prediction with a % confidence score. This means the threshold can be set such that worst case certain people need to be checked out by hand. Fallback to standard checkout means they still cut down quite a bit on the needed human interaction and they can set KPIs around improving those stats.
- antognini 10y agoWhile it's sometimes okay to interpret the output of a model as a confidence, you do so at your own peril because that's not really what the model is optimizing. There are often cases where the model outputs a very high "confidence", but the model uncertainty is (or should be) very high. This is generally the case anytime you give the model data that is very far (in some sense) from the data that it's been trained on.