These past days, in college, we have been learning about NaiveBayes. Since it's a classification algorithm, I was wondering if I could evaluate NaiveBayes models the same way (using the same metrics) we evaluate other classification algorithms like SVM, LogisticRegression or DecisionTrees.
It makes sense to me to use metrics like precision, recall or F1-score to evaluate it. But I am doubting with metrics like the ROC curve or the PR-curve? Would it be correcto to evaluate my model using these type of curves? Or it doesn't make sense to build a ROC/PR-curve for NaiveBayes models?
Thanks a lot! :)