Way to generate confidence interval for predictions?
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- Dominant language
- Python
- Stars
- 386
- Forks
- 36
- Avg merge
- 23h 24m
- Merged PRs (30d)
- 2
Description
Looking at glum, I don't currently see a way to generate confidence intervals for predictions on an input dataset, although I want to check here. By this, I mean something similar to the statsmodels ability to generate confidence intervals (as well as error values) for predictions on a given dataset by way of the PredictionResults class. Is there any equivalent way to do this in glum?
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First steps
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Research direction
No repository file or test is named. Start by checking glum's prediction APIs and compare their available outputs with statsmodels' get_prediction and PredictionResults references; done would mean a documented, tested way to obtain confidence intervals or error values for predictions on an input dataset.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100