When using the python / sklearn API of xgboost are the probabilities obtained via the
predict_proba method "real probabilities" or do I have to use
logit:rawand manually calculate the sigmoid function?
I wanted to experiment with different cutoff points. Currently using
sklearn:XGBClassifier the probabilities returned from the
prob_a method rather resemble 2 classes and not a continuous function where changing the cut-off point impacts the final scoring.
Is this the right way to obtain probabilities for experimenting with the cutoff value?