Is support Ranking Loss?
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- Dominant language
- Python
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Description
❓ Is it possible to expand support for Ranking Loss, such as Listwise Ranking Loss or Pairwise Ranking Loss, as well as Mixed Loss (MSE+Ranking)
If not supported, how to customize the loss function outside the framework and configure it to be called using qlib in YAML
The existing MSE for predicting section TopK cannot take into account the relative ranking relationship between instruments, and the effect is not very good.
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First steps
- Read the whole issue, then the project's contributing guide.
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- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing Qlib's existing MSE-based prediction setup and the YAML configuration path mentioned in the issue. Determine how Listwise Ranking Loss, Pairwise Ranking Loss, and mixed MSE-plus-ranking loss would fit, and document a concrete supported configuration or customization boundary.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- fintech-quant, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100