I want to predict real estate prices using several Machine Learning algorithms. My dataset contains numerical and categorical predictors. I already eliminated the outliers of numerical variables. Now I'm wondering on how to deal with "outliers" (i.e., imbalanced classes) of the categorical variables but I could not find anything on this topic. Do I have to deal with the imbalanced classes (outliers) at all or is it only relevant for classification tasks?
Side note, if important: I encoded the categorical variables using one-hot encoding.