Incorporate additional predictors into meta-forecast eval model by location into model-based evaluation
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- r
- Domain
- data, machine-learning
Research direction
Review the planned analyses and the existing meta-forecast evaluation model to identify which location-specific wastewater or demographic predictors are already available. Compare candidate predictors by location and define how their inclusion would be evaluated. Done means an agreed predictor set and evaluation approach are incorporated into the model.
Written by the indexing model from the issue text.
Description
Likely additional location specific confounders that are not currently included in the planned analyses.
Are there other predictors we might be able to include, either on the wastewater side of demographic side?
- Dominant language
- R
- Stars
- 4
- Forks
- 1
- Avg merge
- 1d 3h
- Merged PRs (30d)
- 7
Getting set up
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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