What are the different anomaly detection algorithms and how do they compare?

What are the main types of anomaly detection algorithms?

The main types include statistical methods, machine learning approaches, and clustering techniques.

How do supervised and unsupervised anomaly detection differ?

Supervised methods require labeled data to train the model, while unsupervised methods do not and identify anomalies based on patterns.

Can you give examples of algorithms in each category?

Sure! For statistical methods, you have Z-score and Grubbs' test. In machine learning, there's Isolation Forest and SVM. Clustering methods include DBSCAN and K-means.

Which algorithm is the most effective for real-time anomaly detection?

It often depends on the specific use case, but algorithms like Isolation Forest and LSTM networks are popular for real-time applications.