I am running repeated K-fold Cross-Validation on my dataset using different models. My problem is a regression problem and I am counting on the error metric MAE. I do know that some models may behave better that others, but I cannot explain the drastic change in the behavior of the learning curves in each:
Specifically, I want to know what makes the learning curve for the gradient boost so bad. I assume its not learning anything. Is that normal ?