Sentiment Analysis Using Averaged Weighted Word Vector Features
Table 2: Accuracies of Methods After Ensemble for IMDB dataset
['[BOLD] Methods', '[BOLD] Ensemble-1', '[BOLD] Ensemble-2']
We see that the WARV model is included in all the ensembles with the highest success rates. The NBSVM and CNN methods also contribute to the performance in the models formed of more than two classifiers. We observe that the success rates we obtain outperform those in Mesnil by about three percent. Especially when our WARV and Wang’s NBSVM methods are ensembled, we obtain the state of art result (95.6%).