Table 7.
Sentiment accuracy comparison on polynomial dataset
| Algorithm | Train–test split percentage | 10-FCV | ||||||
|---|---|---|---|---|---|---|---|---|
| 10% | 20% | 30% | 40% | 50% | 60% | 70% | ||
| KNN | 57.02 | 59.55 | 61.46 | 62.79 | 63.72 | 64.09 | 64.95 | 66.50 |
| DT | 54.08 | 54.94 | 54.89 | 54.72 | 55.47 | 55.25 | 55.73 | 55.49 |
| SVM | 61.73 | 65.29 | 67.56 | 69.09 | 70.69 | 71.00 | 71.97 | 73.91 |
| NB | 54.14 | 57.27 | 57.90 | 58.90 | 60.69 | 60.08 | 60.89 | 61.69 |
| Voting | 58.48 | 61.19 | 62.98 | 64.60 | 65.93 | 65.81 | 66.76 | 68.30 |
| Bagging (KNN) | 56.37 | 59.06 | 60.52 | 62.17 | 63.32 | 63.62 | 64.37 | 66.54 |
| Bagging (DT) | 54.36 | 54.96 | 54.56 | 55.22 | 55.47 | 55.25 | 55.87 | 55.56 |
| Bagging (SVM) | 61.72 | 65.28 | 67.56 | 68.98 | 70.72 | 70.96 | 71.97 | 73.87 |
| Bagging (NB) | 54.17 | 57.18 | 58.00 | 58.97 | 60.74 | 60.08 | 61.03 | 61.92 |