ABSTRACT
Outlier detection, also known as anomaly detection, is a technique used to identify observations in a dataset that deviate significantly from the majority of the data. These observations are often referred to as “outliers” or “anomalies”. Outlier detection is useful in a variety of fields such as finance, healthcare, and cybersecurity, for identifying unusual patterns, fraud, or errors in data.
