anomaliesevents
Anomaliesevents is a term used to describe irregular or rare events that depart from expected patterns in data streams or observational records. The concept is applied across disciplines to identify occurrences that may indicate system faults, fraud, natural phenomena, or other noteworthy deviations from normal behavior.
Anomaliesevents are typically categorized into three broad types: point anomalies, contextual anomalies, and collective anomalies. Point
Detection methods for anomaliesevents combine statistical, machine learning, and domain-specific approaches. Common techniques include statistical thresholds,
Applications span finance, cybersecurity, manufacturing, healthcare, telecommunications, and environmental monitoring. In finance, anomaliesevents can signal fraud