NVIDIA-Merlin / NVIDIA-Merlin/Merlin
Session-based quick start: Support pointwise prediction tasks
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 907
- Forks
- 129
- PR merge metrics
- No merged PRs in 30d
Description
- Support pointwise predictions taking as input sequential and non-sequential features (e.g. for ranking models or cart abandonment).
- Whether the targets are binary or regression are going to be inferred from the schema.
- The user needs to choose whether the sequential model is targeted for next-item prediction or for pointwise predictions. The script will not allow both types of predictions in a MTL 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 the session-based quick-start script and its sequential-model configuration. Trace how schema information could distinguish binary targets from regression and how the script selects next-item versus pointwise prediction. Done means pointwise prediction supports sequential and non-sequential features without allowing both prediction modes in one MTL setup.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100