When studying Linear Regression, I remember that Multicollinearity is something that impacts inference and not prediction, at least not always. Also, I noted that the assumptions tends to be neglected by those who are only interested in predictions.
Is there anything like that for Logistic Regression? I couldn't find any thread related to this question, except for this one. It helped me a little, but it doesn't quite answer my question. I mean, I'm not actually talking about causality, since that is not achieved by these regressions by themselves, but about coefficients interpretability and estimators.
Well, I hope the question is good enough, it doesn't break any rules, but I'm always skeptic when it's something that broad. If I missed something, I have no problem in deleting it. And I apologize in advance for that.