WisconsinAIVision / WisconsinAIVision/UniversalFakeDetect
How is the Nearest Neighbor method implemented?
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- Dominant language
- Python
- Stars
- 378
- Forks
- 58
- PR merge metrics
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Description
Thank you for your work.
The paper mentions the use of two methods, Nearest Neighbor and Linear Classification.
In the published code, I only found the implementation of Linear Classification and couldn't find how Nearest Neighbor is implemented. Is this part not disclosed?
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Start by comparing the paper's description of Nearest Neighbor with the published Python code, focusing first on the training and evaluation entry points. Determine whether a Nearest Neighbor implementation exists and, if so, identify where it is used. Done means documenting its location and behavior, or confirming that the released code does not include it.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100