how the metrics R^2 (coefficient of determination) can be used to evaluate the model accracy?
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Description
dear professer:
I have been paying much attention on the dimension reduction technique, and recently, I try the architecure of parametric_umap with autencoding based on the Tf2.3 library. I want to the monitor the model accracy in the training process. How can i introduce the R^2 into the architecture of parametric_umap.
Looking forward to your reply.Thanks a lot.
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Research direction
Start by reading the parametric_umap architecture and its TensorFlow 2.3 training path; the issue does not name a file, test, or entry point. Clarify whether R² should be added as a training metric and define the expected monitoring behavior before implementation.
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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
- 15/100