Facing with a multi-class classification task,

my question is:

are ROC and Precision-Recall (One-vs-All-Rest) curves useful to evaluate and visualize the performance of a model? or Confusion matrix, Precision, Recall, F-score (micro and macro) are enough?

What do you think about?


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