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Add more metrics
The idea is to add more metrics taking as basis torchmetrics and tf metrics implementation.
Guidelines
- For implementation purposes reference to accuracy. Take into account each metric needs and update and compute method as does torchmetrics implementation.
- Some of metrics can inherit from modules such as Mean, Reduce, Metric while others need an implementation from scratch.
- Must add unit test for numerical equivalence with respect to torchmetrics or tf metrics
Regression metrics
- [ ] R2
- [ ] Root mean squared error
- [ ] Mean squared error
- [ ] Cosine similarity
Classification metrics
- [ ] IOU
- [ ] ROC
- [ ] Specificity
- [ ] AUC
- [ ] Precision and recall
- [ ] Cohen kappa
- [ ] Confusion matrix
- [ ] Hamming distance
If you want to work on a metric, feel free to "claim" it via a comment here so others know you are working on it. Additionally feel free to add as many metrics as desired, even from other tasks such as audio, language, image, etc.
I will take Mean squared error. I will post here any or in discord the challenges or doubts I face.