Terminology in machine learning: exogenous features vs external features I am currently writing a scientific paper and do not know whether to call some of my input features of my neural network either external or exogenous.
My neural network receives as input features like the outside temperature, which are completely independent of the mapped mathematical function.
Are these independent features called exogenous or external? When is which term used?
Exogenous simply means a value that is determined outside the context of your model &amp; is then imposed on your model. Endogenous means the model determines the value.
I don't know about &quot;external&quot; as this word seems to depend on context. But you would be right to say these variables are exogenous.