tensorflow / tensorflow/recommenders
How to know better evaluation metrics for Retrieval or Rank will translate into better actual recommendations in the case of MovieLens dataset?
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- Dominant language
- Python
- Stars
- 2k
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Description
In the tutorials of Tensorflow Recommenders, top_k_categorical_accuracy is used for the evaluation of Retrieval, and mse for Rank. Do we have examples that show better evaluation metrics translate into better movie recommendations in the case of MovieLens dataset?
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Research direction
Review the TensorFlow Recommenders tutorials that use top_k_categorical_accuracy for Retrieval and MSE for Ranking, along with the MovieLens example. Determine what experiment or documentation example would demonstrate whether improved offline metrics produce better recommendations; done means the relationship is shown with reproducible results and clear interpretation.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100