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Hello, thank you very much for your great package. I have a quick question, where does the equation for calculate_p come from? It seems to be roughly just comparing the input predicted probabilities (i.e., softmax values) to the rank-ordering of the calibration non-conformity scores. This kind of makes sense, but does this really correspond to a p-value necessarily? Is there a reference for this?
You find in-depth background in:
Vovk, V., Gammerman, A. and Shafer, G., 2005. Algorithmic learning in a random world. Springer
Here is a recent introduction:
Angelopoulos, A. N., & Bates, S. (2023). Conformal prediction: A gentle introduction. Foundations and Trends® in Machine Learning, 16(4), 494-591.
Best regards,
Henrik
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