Anomaly Detection
Fraud, equipment failure, network intrusions — the interesting class is often so rare that a supervised classifier never sees enough positive examples to learn from. Anomaly detection reframes the problem entirely: instead of learning what the rare class looks like, learn what normal looks like, and flag anything that deviates.