lenskit / lenskit/lenskit-codex
Support training once for multiple test sets
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1
- Forks
- 0
- PR merge metrics
- No merged PRs in 30d
Description
Some splits (like user sampling) have a single training set for multiple test sets. In such a setting, we only need to train the model once.
Contributor guide
No contributing guide indexed for this repository
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 tracing how user-sampling splits are represented and how training is invoked for each test set. Identify where the shared training set causes repeated model training. Done means one model is trained for the shared training set while all associated test sets are still evaluated.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 52/100