Evaluating lightfm models for some items only
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Description
Just a question, is there a way to evaluate the lightfm models, e.g. precision@k, auc, recall@k but for some selected items only? Is there a way to mask the items that I don't want tinclude in the evaluation and indicate this in the parameters of lightfm.evaluation.precision_at_k() function?
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Start by reading the lightfm.evaluation.precision_at_k() API and the related auc and recall@k evaluation functions mentioned in the issue. Determine whether item selection or masking is already supported by their parameters. Done would require a clearly defined approach for evaluating only selected items, along with documented behavior or tests for the requested use case.
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
- Needs clarification
- Newbie friendliness
- 25/100