Hi,
I am doing some work which requires me to calculate the final prediction(classification) by using each residual tree individually. Right now I am using the predict function (using output_margin = True) to get the un-transformed margin for each residual tree, I am then summing these margin values to get a final value which is then passed in the logit function. This seems to be incorrect as my accuracy value is very low compared to the baseline model (which is the original XGBoost prediction method.), even though the logloss value is better in my model. So, my question is, is my approach correct or do I need to use the leaf probabilities using the predict_leaf option? Please let me know
Thanks