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### 🚀 The feature, motivation and pitch
I propose the addition of a conformal prediction framework to the PyTorch library. This framework would include the implementation of split conformal predictio…
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Problem: CatBoost is a great library, but it currently lacks reliable modern uncertainty quantification that is rather easy to implement using conformal prediction. https://github.com/valeman/awesome-…
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> [!NOTE]
> If you have a request to support a specific method, or would like to see priority of one of the listed methods, please open a separate issue, so it won't get buried in this thread. Base…
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Problem: XGBoost is a great library, but it currently lacks reliable modern uncertainty quantification that is rather easy to implement using conformal prediction. https://github.com/valeman/awesome-…
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https://colab.research.google.com/github/aangelopoulos/conformal_classification/blob/master/example.ipynb
Adapt the above to regression
Maybe also implement it as a wrapper for analyzing how mis…
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# Feature Request
**Describe the Feature Request**
Looking at the documentation it seems like Fortuna implements Inductive Confomal Prediction. I couldn't understand if you are using a mondrian ap…
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Hi @Jianguo99,
I am new to conformal prediction, and I have a multitask, multi-output model that performs both classification and regression for a specific problem. Is it possible to use this kind …
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Understanding the quality of a prediction is a very important use case which is not supported by scikit-learn. Quartile Regression is about as close as it gets. The formal solution to this is conforma…
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Hello,
do I understand correctly that Mondrian Cross-Conformal Prediction is not implemented in the pipelines ?
Thanks!