I'm using Python's module to calculate the VIF for my variables to be used in a binary logistic regression. I'm completely following this post to do this: https://etav.github.io/python/vif_factor_python.html.
With my data, I got a VIF of 1600+ for the intercept, which looks very weird for me (I have used VIF in R before but never seen it). Is it something normal or should I do something about it? Other variables seems normal except for one that has a slightly higher VIF.
To add more context, my response variable is highly unbalanced, it's mostly (~99%) 0 and only 1% positive. I got a feeling that this might be the case since the intercept is all one's.
Any suggestions, helps are welcomed! Please let me know if you need more content as well.