What is anomaly detection in machine learning?

What is anomaly detection in machine learning?

Anomaly detection is a technique used to identify unusual patterns or outliers in data that do not conform to expected behavior.

Can you give me some examples of where anomaly detection is used?

Sure! It's commonly used in fraud detection, network security, fault detection, and monitoring environmental changes.

What algorithms are typically used for anomaly detection?

Some popular algorithms include Isolation Forest, One-Class SVM, and DBSCAN, among others.

How do I choose the right algorithm for my data?

Choosing the right algorithm depends on the nature of your data, the type of anomalies you're looking for, and the computational resources available.