Inference using the SVDD. Given a new sensor array response vector m, a trained and hyperparameter-tuned SVDD uses the decision rule in eqn 12 to categorically label it as an anomalous or normal response. While we do not use it here, the continuous anomaly score ||φ γ (m) -c|| 2 -R 2 loosely quantifies uncertainty (e.g., if large and positive, the observed vector m is far outside the hypersphere and thus highly likely to be anomalous).