Bidirectional Tree-Structured LSTM with Head Lexicalization
Table 1: Test set accuracies for sentiment classification tasks.
['Model', '5-class Root', '5-class Phrase', 'binary Root', 'binary Phrase']
The BiConTree model can further improve the classification accuracies by 0.7 points (fine-grained) and 1.3 points (binary) compared to the unidirectional bottom-up lexicalized ConTree LSTM model, respectively. There is no significant difference between different models, as consistent with the observation of \newciteli2015tree. To our knowledge, these are the best reported results for this sentiment classification task until now.