I have a dataset in which class A has 99.8%, class B 0.1% and class C 0.1%. If I train my model on this dataset, it predicts always class A. If I do oversampling, it predicts the classes evenly. I want my model to predict class A around 98% of the time, class B 1% and class C 1%. How can I do that?