In sklearn.metrics.f1_score, the f1 score has a parameter called "average". What does macro, micro, weighted, and samples mean? Please elaborate, because in the documentation, it was not explained properly. Or simply answer the following: Why is "samples" best parameter for multilabel classification? Why is micro best for an imbalanced dataset? what's the difference between weighted and macro? Continue reading...
