Micro, Macro & Weighted Averages of F1 Score, Clearly Explained - KDnuggets

The F1 score (aka F-measure) is a popular metric for evaluating the performance of a classification model. In the case of multi-class classification, we adopt averaging methods for F1 score calculation, resulting in a set of different average scores (macro, weighted, micro) in the classification report. This article looks at the meaning of these averages, how to calculate them, and which one to choose for reporting. Note: Skip this section if you are already familiar with the concepts of precision, recall, and F1 score. Layman definition: Of all the positive predictions I made, how many of them are truly positive?