Removing categorical predictors with mode frequency above certain threshold Is there a rule of thumb for dropping certain categorical predictors if the most frequent value in the column is above a certain threshold? For example, should I drop a column/predictor if more than 95% of the values are the same category?
What would be the proper way of dealing with such kind of columns? Should the rare values be checked with the target variable?

I don't think it is possible to come up with a good, general rule of thumb for this.
Imagine a disease/condition that is perfectly determined by variation in one gene and is very rare. Suppose 0.01% of the population has the disease; it is caused by an allele that is also only present in that 0.01% of the population (to simplify a bit). It would not make sense to ignore the gene predicting the disease just because 99.99% of the values were identical - that 0.01% is incredibly important! In this case that little variation in the data would lead to a perfect predictions of disease incidence.
So at the very least, a decision about whether to omit such a predictor should consider the causal connection to the response, as well as the distribution of the response.
