Advances, Systems and Applications
Table 1 Achieved Results (%) using binary classification of anomalies
From: Cloud-based multiclass anomaly detection and categorization using ensemble learning
Algorithms | Accuracy | Precision | Recall | F1-score |
|---|---|---|---|---|
Decision Tree classifier | 91.86 | 91.65 | 99.78 | 95.54 |
XGBoost | 93.34 | 93.38 | 99.59 | 96.39 |
Random Forest classifier | 93.57 | 93.59 | 99.63 | 96.52 |
Gradient Boosting classifier | 94.40 | 94.72 | 99.36 | 96.99 |
Machine Ensemble | 97.06 | 98.39 | 98.45 | 98.45 |