Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text DatasetsSupported by organization x.
Table 3: P values and win/draw/lose of pairwise comparison of QBC-based methods.
['[EMPTY]', 'BERT', 'FT', 'FT_T', 'LDA', 'TF-IDF', 'TF']
This shows the win/loss/tie count for each pair of representations and the p-value from the related significance test. The table demonstrate that all embedding-based methods are significantly different from methods based on TF, TF-IDF and LDA with p<0.05. However, embedding-based methods do not have significant difference between each other. Remarkably, BERT achieves the most wins as compared to any other representations.