[D] Using proportion in place of 0 or 1 to binary-valued feature for classification prediction (Xgboost model)
Want to get some input. I have modeled buy propensity with search event data. One user can generate many search events. The model was XGBoost with features both real-valued and binary.
Now, if i want to predict buy propensity per user, is it possible just to aggregate the data for that user and feed that to the model? One worry is because aggregation can return proportion for binary feature that expects 0 or 1 instead. It seems like XGBoost is not like linear model that makes some assumptions about the data. But, still what do you think? Is it fine to do this?