tidyverts / tidyverts/fabletools
Graceful failure when forecasting a mable
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- Dominant language
- R
- Stars
- 98
- Forks
- 37
- PR merge metrics
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Description
Currently running forecast on a mable fails if any of the models errors out when being forecasted. Is there a way to either drop it completely or return some "NULL forecast" from such a model?
We run batches of 1000 models which take about 20 minutes to compute and then immediately the whole job fails with an error on just one bad model.
Basically, a feature similar to a bad model train function returning a NULL model instead of killing the entire process.
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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.
Research direction
Start from the forecast operation on a mable and compare its failure behavior with the bad-model train function described in the issue. Determine whether a failed model should be dropped or represented by a NULL forecast, then verify that one bad model no longer aborts a batch of forecasts.
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Assessment
- Tech stack
- r
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100