Text-based depression detection on sparse data
TABLE IX: Best performing pooling function across averaged 5-fold runs (μbest) regarding each embedding. Results on the dev set utilize the best average performing models on the CV set. Bold displays best performance on the dev/cv sets.
['Embedding', 'Pooling', 'Data', 'Pre', 'Rec', 'F1', 'Acc', 'MAE']
maxk=1,… ,100⎛⎝1FF=5∑f=1rkf(F1)⎞⎠ Here, the best pooling method generating the result is also displayed. As can be seen, for all features except fastText, mean-pooling indeed provides competitive performance on all data. The most stable feature is ELMo, which offers excellent performance on the held-out cv (F1 0.73, MAE 4.26) as well as development sets (F1 0.73, MAE 4.71).