Why only Micro-F-1? Class Weighting of Measures for Relation Classification

Relation classification models are conventionally evaluated using only a single measure, e.g., micro-F-1, macro-F-1 or AUC. In this work, we analyze weighting schemes, such as micro and macro, for imbalanced datasets. We introduce a framework for weighting schemes, where existing schemes are extremes, and two new intermediate schemes. We show that reporting results of different weighting schemes better highlights strengths and weaknesses of a model.