Hi,
I have an issue and googling it did not help so far …
I am using XGBoost Linear Model Learner with objective set to binary logistic for a binary classification task.
My understanding is that the model is a logistic regression. (what is difference between reg:logistic and binary:logistic? · Issue #521 · dmlc/xgboost · GitHub)
The model consists of coefficients + intercept.
But when I “manually” (in excel) try to calculate propabilities, I do not get the same propabilities compared to what the XGBoost Predictor calculates.
Formula I am using is:
exp(sum coefficients incl. intercept) / (1+exp(sum coefficients incl. intercept))
I can perfectly recalculate propabilities manually for a logistic regression model build with Weka Logistic (3.7) or H2O generalized linear model builder.
So unsure what might be the issue.
Thx for any help!
Best,
Mat