Learning Document Embeddings by Predicting N-grams for Sentiment Classification of Long Movie Reviews
Table 6: Different model ensemble results. R: RNN-LM. N: NBSVM.
['[BOLD] Model', '[BOLD] Alone', '[BOLD] +R', '[BOLD] +N', '[BOLD] +R+N']
Without much surprise, a new state-of-the-art result is obtained by replacing PV to our model. Note that combining with or without RNN-LM do not affect results much. One reason for this may be that RNN-LM becomes burdensome when combined with more robust model since RNN-LM alone only achieves 86.6 percent in terms of accuracy.