Table 5 Test accuracies of classification algorithms for three datasets
From: Optimization of sentiment analysis using machine learning classifiers
Classification algorithm | Data set | Test accuracy with 42 features of text (%age) | Test accuracy with 15 features of text (%age) |
|---|---|---|---|
Naïve Bayes | D1 | 85.127 | 78.814 |
D2 | 73.517 | 69.298 | |
D3 | 76.782 | 68.864 | |
J-48 | D1 | 87.622 | 85.452 |
D2 | 76.865 | 63.454 | |
D3 | 74.231 | 69.895 | |
BFTree | D1 | 84.982 | 80.232 |
D2 | 69.452 | 65.156 | |
D3 | 61.512 | 60.564 | |
OneR | D1 | 87.652 | 84.452 |
D2 | 76.563 | 72.788 | |
D3 | 65.876 | 63.521 |