Table 2. Classification report of supervised learning models.
| Classifiers | Accuracy | Precision | Recall | F-score |
|---|---|---|---|---|
| Random forest | 93.9% | 89.69% | 90.67% | 90.11% |
| Support vector machine | 91.4% | 85.17% | 87.74% | 86.29% |
| Logistic regression | 93.0% | 91.29% | 93.44% | 92.54% |
| Stochastic gradient descent | 90.8% | 83.33% | 84.77% | 84.32% |
| Voting classifier | 92.6% | 91.34% | 92.66% | 91.97% |
| Decision tree | 92.7% | 89.59% | 90.57% | 90.01% |
| Gradient boosting machine | 87.7% | 80.97% | 83.35% | 81.99% |
| Extra tree classifier | 93.8% | 89.89% | 90.87% | 90.34% |
| Long short term memory (LSTM) | 91.6% | 89.17% | 90.74% | 90.09% |
| Convolutional neural network (CNN) | 96.6% | 95.57% | 97.74% | 96.45% |