I have a dataset with 5 classes. About 98% of the dataset belong to class 5. Classes 1-4 share equally about 2% of the dataset. However, it is highly important, that classes 1-4 are correctly classified.

The accuracy is not a good measure of performance for my task. I found lots of information on metrics for imbalanced binary classification tasks but not on multiclass problems.

Which performance metrics should I use for such a task?

* TP, TN, FP, FN
* Precision
* Sensitivity
* Specificity
* F-score
* ROC-AUC (micro, macro, samples, weighted)