is multicollinearity a problem also in classification?
I was thinking about this very issue for some time. It seems like in machine learning, the multicollinearity is usually not such a big deal because it should not mess up the prediction power as such. It is problematic for estimation of the effects, for coefficients of the individual variables - hence, the problem with regression.
This post summarizes it quite well https://stats.stackexchange.com/a/168631/197070.