I am currently using transaction amount as a feature in an XGBoost classification model designed to identify fraudulent transactions. Furthermore, transaction amount is bounded for this problem between 0 and 500. Using transaction amount as a feature does improve target class separability. However, I can't help but wonder if there is a better way to use this variable. To explain, I care more about getting the high transaction amount values correct than I do the low ones. However, the model does not currently comprehend that. I have taught the XGBoost algorithm that the positive class is in effect more important by adjusting scale_pos_weight, but I haven't thought of a way to teach the algorithm that high transaction amount values are more important.
EDIT: I wanted to provide a bit more detail. After some additional reading, I think what I may be looking for is some kind of custom objective function. Possibly something like what is being discussed here.