Item cold-start prediction
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- Dominant language
- Python
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Description
When prediction with Lightfm model fitted with item-features for a new item, what should the item-id be in the predict function? In fact it is working with 0, is that the right approach and if yes what is the reasoning behind?. What if we want to predict for several new items?
Thanks in advance.
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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.
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Research direction
Start with the LightFM model's predict function and the item-features handling described in the issue. Determine how item IDs should be supplied for one or several new items, and whether using 0 is supported and why. Document the confirmed cold-start behavior and its rationale.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100