tensorflow / tensorflow/recommenders
[Question]: Using other metrics such as `AUC`.
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Description
In much of the literature / guides outside of this project AUC seems to be a popular metric for recommender systems. TF and Keras specifically has an implementation here.
However I am not sure on:
- is this a valid metric to use for retrieval when using this project?
- what hyperparams would be important to consider?
- would the use of this as
batch_metricmake sense?
Thanks in advance!
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Research direction
Start by reviewing the TensorFlow/Keras AUC implementation linked in the issue and the project's retrieval metrics and batch_metric entry points. Determine whether AUC applies here, which hyperparameters matter, and what evidence or documentation would be needed to consider the question resolved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- keras, 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