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Is there any categorical encoding technique for credit ratings that take into account the kind of non linear nature of the notches of the credit ratings?

The literature standard is the ordinal one unless I have missed something. Some other papers have tried probit and logistic/exponential encoding (?)

Any ideas are really welcome

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Other than the ones you have mentioned, James-Stein encoding (a target-based encoder) could be a possible idea.

James-Stein encoding was used in this paper titled "Machine Learning approach for Credit Scoring".

Also, this Kaggle website lists 11 categorical encoders. Notably, "Weight Of Evidence" is quoted as a commonly used target-based encoder in credit scoring.

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