I have a model that has a categorical slot:
account_type: type: categorical values: - pro - basic
Initially, the value is None and sometimes it stays None and sometimes I set it to pro or basic. It is important in predicting dialog behavior. Does it impact Keras Policy’s predictive capability if I keep it like this vs. create another explicit category:
account_type: type: categorical values: - pro - basic - noaccount initial_value: noaccount
Are those two scenarios the same?