Right now, I’m building a model that’s trying to classify car images according to their models. My problem with the current model is that it’s performing badly on certain classes. To elaborate further, there are two classes that are very similar and the model seems to mis-classify one of the classes into the other one, but not the other way around (A mostly classified as B while B is classified as B). I don’t think it is caused by uneven data distribution because when i perform the training, I ensure that all classes have more or less the same number of samples. Would anyone have any suggestions to solve this? Any idea would be great. Thanks!