Anomaly detection identifies rare instances in data from "summary" of Machine Learning by Ethem Alpaydin
Anomaly detection is a crucial task in machine learning that involves identifying rare instances in a dataset. These rare instances, also known as anomalies, differ significantly from the majority of the data points in terms of their characteristics or behaviors. Anomalies may represent critical events that require immediate attention or further investigation, such as fraudulent activities, manufacturing defects, or system failures. To detect anomalies, machine learning algorithms are trained on normal instances to learn the underlying patterns and relationships in the data. Once trained, the algorithms can then identify instances that deviate significantly from these learned patterns as anomalies. Anomaly...
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