What is the role of feature engineering in anomaly detection?

Can you explain the role of feature engineering in anomaly detection?

Feature engineering is crucial in anomaly detection as it helps in transforming raw data into meaningful features that improve model performance.

What types of features are typically engineered for anomaly detection?

Common features include statistical measures, time-based features, and domain-specific indicators that highlight unusual patterns.

How does feature selection impact the effectiveness of anomaly detection?

Feature selection helps in reducing noise and focusing on the most relevant features, which enhances the model's ability to detect anomalies.

Can you give an example of a feature that might be useful in detecting fraud?

Sure! A feature like the frequency of transactions within a specific time frame can be indicative of fraudulent behavior.