Research Article
Performance Assessment of Multiple Classifiers Based on Ensemble Feature Selection Scheme for Sentiment Analysis
Table 7
Comparison of performance of proposed approach with different literature using movie review dataset.
| | Dataset | Feature Selection Method | Classifier | Performance |
| Pang et al. | Internet movie database (IMDb) | N-gram features | SVM NB ME | 82.9 (Accuracy) 81.5 81.0 |
| Agarwal et al. | Movie (IMDb) Product (book, DVD, Electronics) | N-gram, IG,RSAR, Hybrid (IG+RSAR) | SVM NB | 87.7 (F-measure) 80.9 |
| Al-Moslmi et al. | Movie Reviews in the Malay Language | IG, CHI, Gini Index | SVM NB KNN | 85.33(F-measure) 80.88 74.68 |
| Kalaivani et al. | Movie (IMDb) | - - - - - - - - - - - - - - - - - - - - - | SVM NB KNN | 81.71 72.55 98.70 |
| Tripathy et al. | Movie (IMDb) | N-Gram features | SVM ME NB SGD | 88.94 88.48 86.23 85.11 |
| Our Approach | Movie (IMDb) | N-gram, Combination of Unigram & bigram with IG, CHI, Gini Index | SVM MNB KNN ME | 90.39 (F-measure) 88.04 86.03 87.13 |
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