tensorflow / tensorflow/recommenders
How can I add Mean Average Precision metric?
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- Python
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Description
Hello, I was reading several books on recommender systems and in the literature the mAP (Mean Average Precision) metric is used a lot and I wanted to know how I can implement it, in the tutorials and in the API only TopK Accuracy appears, I was wondering if anyone has already implemented mAP@K, thanks.
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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 by reviewing the tutorials and API references where TopK Accuracy is currently exposed. Define the expected mAP@K behavior and integration point; done means the metric is clearly specified and available consistently in the relevant tutorials and API.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100