A successful example of machine learning-based anomaly detection for predictive maintenance comes from San Diego Gas & Electric. This public utility company faced a widespread energy leakage problem.

Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the ...

Within the larger family of unsupervised learning algorithms for anomaly detection there are different approaches to take including clustering algorithms, isolation forests, local outlier factors ...

For example, the combination of clustering, anomaly detection, and deep learning allows for cybersecurity systems to have a greater degree of accuracy and confidence in what could be considered as ...