Request for different opt_crit Values
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- Dominant language
- R
- Stars
- 588
- Forks
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- Avg merge
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- Merged PRs (30d)
- 1
Description
I am wondering if it is possible to add new error metrics to optimize forecasts on. RMSLE is a powerful metric for forecasts that should get penalized less for missing high or by high %.
RMSLE is defined quite well here: https://hrngok.github.io/posts/metrics/#:~:text=Root%20Mean%20Squared%20Logaritmic%20Error%20(RMSLE)&text=It%20is%20the%20Root%20Mean,possible%200%20(zero)%20values.
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Research direction
The issue names no files, tests, or entry points. Start by locating the existing opt_crit values and forecast error metric definitions, then determine how RMSLE would fit the optimization interface; done means RMSLE can be selected and is covered by appropriate tests.
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Assessment
- Tech stack
- r
- Domain
- analytics, data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100