I want to obtain the prediction intervals of my xgboost model which I am using to solve a regression problem. I am using the python code shared on this blog, and not really understanding how the quantile parameters affect the model (I am using the suggested parameter values on the blog). When I apply this code to my data, I obtain nonsense results, such as negative predictions for my target values while my target values are always over 10K. I don't understand how should this code vary according to my data and would really appreciate any help.
Differences in my data to the data that is used on the blog are:
- My distribution is Poisson like.
- I have over 100 features.
Note: I tried tuning the delta, threshold and var parameters, but they don't seem to have a controllable effect on the results and predictions remains nonsense.