I have a multiclass classification problem. Further, an instance can be assigned to exactly one class. My dataset is highly imbalanced. I know that accuracy is not a good metric to use in this case because one can simply predict the high frequent class and get a good score. I understand that micro F1 is better than macro F1 for multiclass classification problem but it turns out that the micro F1 score is the same as accuracy score. So, the whole idea of looking into alternative metric (i.e. micro F1) instead of accuracy has gone full circle.
Should I be using macro F1 instead?