Model biased towards low frequency data?
With structured data, you have in general 4 challenges:

(1) Missing data

(2) Outliers

(3) Cardinality

(4) Rare values (as a rule of thumb &lt;5%)

Rare values in categorical variables tend to cause over-fitting, particularly in tree based methods. Ph.D. Data Scientist Soledad Galli has an amazing course on the subject (Udemy: "Feature Engineering". Below a screenshot from her course, but to be fair to her, I'm not going to post the solution.