In machine learning, people talk about objective function, cost function, loss function. Are they just different names of the same thing? When to use them? If they are not always refer to the same thing, what are the differences?
Machine Learning – Objective Function, Cost Function, and Loss Function Differences
artificial intelligencemachine learningterminology
Best Answer
These are not very strict terms and they are highly related. However:
Long story short, I would say that:
A loss function is a part of a cost function which is a type of an objective function.
All that being said, thse terms are far from strict, and depending on context, research group, background, can shift and be used in a different meaning. With the main (only?) common thing being "loss" and "cost" functions being something that want wants to minimise, and objective function being something one wants to optimise (which can be both maximisation or minimisation).