I have a dataset with an imbalanced binary target. One class accounts for about 94 % of the target variable. I used SMOTE to oversample the minority class but after the oversampling step when I train a Random Forest on the oversampled data and make predictions on the test set, it predicts the minority class for the whole test set. I can't seem to figure out where things went wrong or what the problem could be. Any help would be appreciated.