Text Classification using Capsules
Table 4: Text classification accuracies for seven benchmark datasets. Results for CapsNet-* and CNN-non-static are the average accuracies of five consecutive runs. CNN-non-static, marked with an asterisk, are results from a replication code of kim2014convolutional. Other results are from the corresponding references.
['Model', '20news', 'Reuters10', 'MR (2004)', 'MR (2005)', 'TREC-QA', 'MPQA', 'IMDb']
We believe this is due to the higher complexity of the second layer, which is a feature map utilizing convolutions.