tensorflow / tensorflow/probability
How to deal with imbalanced data?
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Description
I'm new to TFP and probabilistic models. With deterministic NNs, I could balance my data by oversampling. However, my intuition says one shouldn't do this with probabilistic networks.
Currently, I'm working on a regression problem with imbalanced data. I'd like to attempt TFP for this. Are there any guidelines or references to deal with this?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
The issue names no files, tests, or entry points. Start by reviewing the question about oversampling imbalanced regression data in TFP and identify whether project documentation or references address it; done would be a maintainer-approved guideline or reference.
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Assessment
- Tech stack
- machine-learning
- Domain
- data, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100