XGBoost binary logistic -> calculate probabilities manually using the coefficients problem


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!


Hi @Jiraishin ,
Welcome to the KNIME Community!

Could you please share more details with us, such as your use case, the data (or some sample data if your data is confidential), and your KNIME workflow?

This would help us better understand the problem.

Thank you,

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