Sentiment Classification on Movie
0.9117AccuracyUnsupervised + Supervised Majority Voting (J-48, SVM, NB)
Evaluation results
| Method | Links | |
|---|---|---|
| Unsupervised + Supervised Majority Voting (J-48, SVM, NB)Feature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.9117 | |
| Supervised Majority Voting (J-48, SVM, NB)Feature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.9103 | |
| SVMFeature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.9098 | |
| J-48Feature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.8987 | |
| NBFeature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.8953 | |
| Unsupervised + Supervised Majority Voting (J-48, SVM, NB)Feature Technique=Pattern, Technique=3-feats2025.11 | 0.8536 | |
| Supervised Majority Voting (J-48, SVM, NB)Feature Technique=Pattern, Technique=3-feats2025.11 | 0.851 | |
| SVMFeature Technique=Pattern, Technique=3-feats2025.11 | 0.8467 | |
| J-48Feature Technique=Pattern, Technique=3-feats2025.11 | 0.8421 | |
| NBFeature Technique=Pattern, Technique=3-feats2025.11 | 0.8412 | |
| kNNFeature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.7473 | |
| Semi-supervisedFeature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.7228 | |
| kNNFeature Technique=Pattern, Technique=3-feats2025.11 | 0.7016 | |
| UnsupervisedFeature Technique=Unigram + MWE, Technique=3-feats2025.11 | 0.7012 | |
| Semi-supervisedFeature Technique=Pattern, Technique=3-feats2025.11 | 0.6586 | |
| UnsupervisedFeature Technique=Pattern, Technique=3-feats2025.11 | 0.6142 |