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:
The question is about the meaning of the average parameter in sklearn.metrics.f1_score.
As you can see from the code:
average=micro says the function to compute f1 by considering total true positives, false negatives and false positives (no matter of the prediction for each label in the dataset)average=macro says the function to compute f1 for each label, and returns the average without considering the proportion for each label in the dataset.average=weighted says the function to compute f1 for each label, and returns the average considering the proportion for each label in the dataset.average=samples says the function to compute f1 for each instance, and returns the average. Use it for multilabel classification.