RMSE for Explicit Data
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- Dominant language
- Python
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Description
The documentation homepage says,
"LightFM is a Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback."
But if it can work with explicit feedback, why no RMSE or MAE metrics are provided in model evaluation(**https://making.lyst.com/lightfm/docs/lightfm.evaluation.html**)? Only ranking metrics are provided. Does this mean actually LightFM only can work with implicit data?
Contributor guide
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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 with the documentation homepage and the LightFM evaluation documentation at making.lyst.com/lightfm/docs/lightfm.evaluation.html. Verify how explicit feedback is supported and whether the absence of RMSE or MAE is intentional; the documentation is done when it clearly explains this relationship and the available evaluation metrics.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100