Medical-Event-Data-Standard / Medical-Event-Data-Standard/MEDS-DEV
We should support evaluation-only mode for pre-trained models distributed with weights
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 43
- Forks
- 10
- PR merge metrics
- No merged PRs in 30d
Description
Though this should not be the main focus of the benchmark, there is no reason it wouldn't work to just define a model with a predict step and no train step. This would be especially important as we add more of the stanford style models and the EHR Shot dataset (#203) which are more aligned with this approach.
Contributor guide
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 by locating how benchmark models currently define and invoke training and prediction, then review the evaluation path for pre-trained models with weights. Compare the requirements for the Stanford-style models and EHR Shot dataset in issue #203; done means a model can run evaluation with a predict step and no train step.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100