# Is logistic regression called “logistic” because it uses the logistic loss or the logistic function?

I've always assumed that logistic regression is called "logistic" because the model directly uses the logistic function.

However, these Stanford notes seem to imply that the name comes from the logistic loss:

The different loss functions lead to different machine learning procedures; in particular, the logistic loss ϕlogistic is logistic regression, the hinge loss ϕhinge gives rise to so-called support vector machines, ...

This doesn't seem quite correct to me, since

1. You could use logistic loss with a different model, e.g. a neural network
2. You could use a different loss with logistic regression, e.g. hinge loss

Or am I missing something?