Order-free Learning Alleviating Exposure Bias in Multi-label Classification
Table 3: Performance comparisons on Reuters-21578
['Models SVM', 'Models SVM', 'maF1', 'miF1', 'ebF1', 'ACC', 'HA', 'Average']
These results demonstrate again the superiority of OCD and the performance gains afforded by the MTL framework. Since there are over 80% of test samples only have one label in this corpus, to truly know the effect of proposed approaches to multi-label classification , we also provide results only on test samples with more than one label in the Section Analysis of Reuters-21758 in Appendix.