4 level classification with imbalance data - better to perform 2 binary predictions?

I have two binary variables, that I want to put in 4 different classes. Also, I have a small dataset (N=110) that is unbalanced (e.g., group 3 has only three observations) and I want to make predictions. Obviously the predictions that I did for the unbalanced dataset are pretty bad, because error rates for minority classes are 100%. However, I upsampled the dataset, and now I have the problem that minority classes get 0% error rate, but majority classes have …

binary classification data datascience predictions