What are the best algorithms for anomaly detection?

What are the best algorithms for anomaly detection?

Some of the best algorithms for anomaly detection include Isolation Forest, One-Class SVM, and DBSCAN. Would you like to know more about any specific algorithm?

Can you explain how Isolation Forest works?

Isolation Forest works by isolating anomalies instead of profiling normal data points. It creates random partitions in the data, and anomalies are more likely to be isolated quickly due to their distinct characteristics.

What are the advantages of using One-Class SVM?

One-Class SVM is effective in high-dimensional spaces and can model complex decision boundaries. It's particularly useful when you have a lot of normal data but very few anomalies.

Are there any unsupervised methods for anomaly detection?

Yes, methods like K-Means clustering and Autoencoders are popular unsupervised techniques for anomaly detection. They can identify outliers without labeled data.