The classification performance metrics for the four classification algorithms after processing the lemmatized data to merge the Non-Terrorist and Unrelated tweets into one class
| KNN | BNB | SVM-OAA | SVM-OAO | |
|---|---|---|---|---|
| Overall accuracy | 76.4% | 76.05% | 82.6% | 81.5% |
| F1-score | 69.6% | 77.3% | 83.2% | 82.5% |
| Precision | 64.2% | 74.7% | 82.2% | 80.7% |
| Recall | 76.6% | 80.1% | 84.3% | 83.5% |
| KNN | BNB | SVM-OAA | SVM-OAO | |
|---|---|---|---|---|
| Overall accuracy | 76.4% | 76.05% | 81.5% | |
| F1-score | 69.6% | 77.3% | 82.5% | |
| Precision | 64.2% | 74.7% | 80.7% | |
| Recall | 76.6% | 80.1% | 83.5% |
Note(s): The F1-score, precision and recall metrics used class terrorist as the true positive
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