tensorflow / tensorflow/recommenders
DCN - RMSE vs BCELoss
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Description
In the DCN tutorial code (GitHub link), the loss function used is Root Mean Squared Error (RMSE). However, I believe thatBinary Cross-Entropy should be used instead.
In the original DCN paper, it specifically mentions that Binary Cross-Entropy was used as the loss function.
Could you explain why there is this difference between the tutorial and the paper?
Contributor guide
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 with docs/examples/dcn.ipynb and compare its RMSE setup with the original DCN paper's statement about Binary Cross-Entropy. Determine whether the tutorial and paper describe different targets or tasks, then document the rationale in the tutorial or clarify which loss should be used.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100