I am a newbie currently learning data science from scratch and I have a rather stupid question to ask. I’m currently learning about binary classification, and I understand that the logistic function is a useful tool for this. I looked up the documentation and noticed that there are two logistic related functions I can import, i.e.
sklearn.linear_model.LogisticRegression. When and where should I use them, and what’s the difference?
On a broader note, what’s the difference between a metric and a model, and why is the log loss function a metric? Apologies if this question sounds completely nonsensical, but this is a genuine source of confusion for me!