How do you carry forecast uncertainty into downstream decisions without reducing it to an arbitrary confidence threshold?
This story is from 2026-09-13. It is preserved in the archive; the latest stories are on the live feed.
I’m working on a forecasting setup where the prediction is ultimately used to make a downstream decision. A common approach seems to be: But choosing X can feel arbitrary, and it also throws away information about the shape or magnitude of the uncertainty. How do you handle this in practice? Do you…
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- 2026-09-13 16:35 · r/learnmachinelearning
How do you carry forecast uncertainty into downstream decisions without reducing it to an arbitrary confidence threshold?