Timeline for Custom (Asymmetric?) Loss Function for Tabular Regression: Preferring underestimation
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| Jul 13, 2022 at 20:56 | comment | added | Alberto | @nlh you can use the MSE that I've posted in the answer below (and add in front of that a coefficient with different based on the case x>0 or x<0) | |
| Jul 13, 2022 at 19:12 | comment | added | nlh | Thanks @AlbertoSinigaglia. The linked answer, suggests a piecewise loss function based on what I think is MSE? (or just SE?). I'd lose the ratio-based approach of RMSLE. Is there a way to create "piecewise" RMSLE? | |
| Jul 13, 2022 at 18:56 | comment | added | nlh | Thank you for the welcome @Dave. I don't yet have an exact answer. But I can tell you more about the business problem and perhaps reason it out: Users of the model are aiming to purchase for resale and make a profit. The cost of over-predicting is a potential loss -- if the actual price is 100 and prediction is 110, you would lose 10. If the actual price is 100 and prediction is 90, you would lose 0 (and potentially profit 10). So the business cost of predicting too low is a missed opportunity, and the business cost of predicting too high is an actual loss. Hope this is helpful. | |
| Jul 13, 2022 at 18:01 | comment | added | Alberto | maybe stats.stackexchange.com/questions/255652/…? | |
| Jul 13, 2022 at 17:26 | answer | added | Alberto | timeline score: 1 | |
| Jul 13, 2022 at 16:58 | comment | added | Dave | Welcome to Cross Validated! Do you have some sense of by how much overpredictions are worse than underpredictions? For instance, predicting $5$ dollars too low is equivalent to predicting $X$ dollars too high. Is $X=1?$ Is $X=4.99?$ | |
| S Jul 13, 2022 at 16:51 | review | First questions | |||
| Jul 13, 2022 at 20:47 | |||||
| S Jul 13, 2022 at 16:51 | history | asked | nlh | CC BY-SA 4.0 |