I made different tests on an imbalanced dataset and got these results:
Model 1 = train test validation split + Cross Validation(cv=10) --> f1'micro' 0,95
Model 2 = train test split + smote method for imbalanced data. No Cross Validation -->f1'micro' 0,97
model 3 = train test validation + smote method --> f1'micro' 0,97
model 4 = train test + smote --> f1'micro' 0,98.
I used f1 micro as metric. Can I compare these models with f1 micro or should I take another one like f1 macro? or just the accuracy_score?