Machine Learning

Anomaly Detection

Identifying unusual observations that differ significantly from normal patterns.

Anomaly detection finds observations, events or behaviours that do not match the expected pattern. Depending on the task, anomalies may represent fraud, equipment failure, cyberattacks, medical abnormalities or data-quality issues.

Methods range from statistical thresholds and clustering to isolation forests and neural networks. The main difficulty is that anomalies are often rare, diverse and poorly labelled.

Also in Machine Learning

Supervised Learning Unsupervised Learning K-Means K-Nearest Neighbours Logistic Regression Linear Regression

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