Poikkeamatunnistuksen
Poikkeamatunnistus, also known as anomaly detection or outlier detection, is a data analysis technique used to identify rare items, events, or observations that deviate significantly from the majority of the data. These deviations are often referred to as anomalies, outliers, novelties, or exceptions. The core idea behind poikkeamatunnistus is that unusual patterns are unlikely to occur within a typical dataset.
The purpose of poikkeamatunnistus can vary widely. In some applications, the goal is to identify and remove
Various methods exist for poikkeamatunnistus, broadly categorized into statistical approaches, machine learning algorithms, and rule-based systems.
The effectiveness of poikkeamatunnistus depends heavily on the nature of the data and the specific application.