Timeline for Penalising Error above a certain Threshold
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 22, 2023 at 18:00 | history | tweeted | twitter.com/StackStats/status/1617220573016330243 | ||
| Jan 20, 2023 at 9:26 | comment | added | Stephan Kolassa | You would need to figure out how the penalty compares to any other costs, or the $L^1$/$L^2$ loss. If the $L^p$ loss of any prediction is irrelevant, you can simply use a loss function that is stepwise per your penalty. Otherwise, it makes sense to use a combined loss. Per my answer, what I am advocating getting a good a grip on your actual loss as possible, and then including that as a loss function in fitting. (Per Richard's comments to my answer, you could also go for full density predictions and then extract the optimal point prediction from that using your cost function.) | |
| Jan 20, 2023 at 8:41 | comment | added | paolopazzo | I have edited my question to make a more general problem, thanks to your comment, that made me realize that makes obviously more sense to pay different amount depending on the amount of the error | |
| Jan 20, 2023 at 8:19 | history | edited | paolopazzo | CC BY-SA 4.0 | added 728 characters in body |
| Jan 19, 2023 at 15:45 | answer | added | Stephan Kolassa | timeline score: 3 | |
| Jan 19, 2023 at 10:59 | comment | added | Stephan Kolassa | Is the penalty the same if your error is 50% as if it is 11%? That will make a difference to what cost function you want. Also any other cost drivers. I would find it hard to believe there are absolutely no other cost or profit considerations than just not exceeding the threshold (because if so, here is your penalty-minimizing solution: simply go out of business, then you will never pay a penalty). Getting the "best" cost function will likely depend on many other influences, which you will need to understand first. Ideally, the cost function should reflect the true costs you incur. | |
| Jan 19, 2023 at 9:27 | history | asked | paolopazzo | CC BY-SA 4.0 |