 Anomaly matching condition

Anomaly matching conditions refer to criteria or rules used to identify and assess anomalies or outliers within a dataset. Anomalies are data points that deviate significantly from the expected patterns or distribution of the data. The specific conditions and approaches for anomaly matching can vary based on the context in which they are applied, but they often involve statistical, machine learning, or heuristic methods.