What is the difference between anomaly detection and outlier detection?

What is the difference between anomaly detection and outlier detection?

Anomaly detection identifies patterns that do not conform to expected behavior, while outlier detection focuses on identifying data points that differ significantly from the rest.

Can you give me an example of each?

Sure! Anomaly detection might be used in fraud detection to spot unusual transaction patterns, while outlier detection could identify a single data point in a dataset that is much higher or lower than the others.

Are the techniques used for both the same?

Not necessarily. Anomaly detection often uses machine learning models, while outlier detection can be done using statistical methods.

Which one is more important in data analysis?

It depends on the context. Anomaly detection is crucial for identifying unexpected events, while outlier detection is important for ensuring data quality.