I think the question is self-explanatory. But let's say you have a data with a few features with categorical data, and when building a model for example XGBoost you one-hot encode categorical features. Now you want to do prediction based on test data using the saved model. Obviously the test data needs to be one-hot encoded and need have similar features as training set. The question is whether it is possible to find a way not one-hot encode the test data and directly use it for prediction? Would this be somehow possible?
To me it appears that whatever comes in to my saved model need to be as it was used during training i.e. one-hot encoded features! But this is not neat, especially when building widgets and dashboards!
Any comments/hints are appreciated.