Anomaly Detection on Telemetry dataset synthetic (Layer 1)
100AccuracyQML + Random Forest
Evaluation results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| QML + Random ForestArchitecture=Quantum-Machine Learning2025.12 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | |
| Serial DQNN + DNNArchitecture=Serial2025.12 | 98.8 | 99.29 | 98.37 | 98.17 | 99.37 | 98.72 | 98.87 | |
| Parallel DQNN + DNNArchitecture=Parallel2025.12 | 98.13 | 99.35 | 97.1 | 96.69 | 99.43 | 98 | 98.25 | |
| Naive Bayes2025.12 | 87.87 | 90.98 | 85.53 | 82.51 | 92.67 | 86.54 | 88.96 | |
| SVM2025.12 | 79.17 | 78.5 | 79.74 | 77.01 | 81.1 | 77.75 | 80.41 | |
| Logistic Regression2025.12 | 79.13 | 78.33 | 79.84 | 77.22 | 80.85 | 77.77 | 80.34 | |
| Isolation Forest2025.12 | 52.07 | 49.63 | 75.17 | 94.99 | 13.59 | 65.2 | 23.02 | |
| RL Agent2025.12 | 52.07 | 43.42 | 52.53 | 4.65 | 94.56 | 8.41 | 67.54 |