when fitting a XGBRegressor, a Booster object can be passed via the model parameter. Before fitting a XGBRegressor, the predict method does not work, which makes sense. The Booster Object has a predict method that works well (you have to convert the features to a DMatrix, though).
I want to dress a Booster object to a XGBRegressor so that before fitting the predict method of the XGBRegressor works, using the one from the Booster and accepting non DMatrix features. In Code
booster = Booster().load_model('path_to_save') model = XGBRegressor(parameters) model.set_booster(booster) # <== that is the line I am looking to achieve model.predict(X) # so that this then works
Thank you very much!