Research Article
[Retracted] A Deep Spiking Neural Network Anomaly Detection Method
Table 1
Anomalies detection performance metrics.
| Classifier | Accuracy (%) | RMSE | Precision | Recall | F-score | AUC |
| GLSM | 97.88 | 0.0710 | 0.987 | 0.987 | 0.987 | 0.9883 | Autoencoder | 95.92 | 0.0847 | 0.960 | 0.960 | 0.960 | 0.9798 | LSTM | 95.08 | 0.0891 | 0.951 | 0.951 | 0.952 | 0.9732 | CNN | 94.59 | 0.0928 | 0.946 | 0.946 | 0.947 | 0.9781 | One class SVM | 93.26 | 0.0933 | 0.933 | 0.934 | 0.933 | 0.9590 | Isolation forest | 92.51 | 0.0925 | 0.925 | 0.925 | 0.925 | 0.9519 |
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