What are the different methods for outlier detection?

What are the different methods for outlier detection?

There are several methods for outlier detection, including statistical tests, clustering, and machine learning techniques. Would you like to know more about a specific method?

Can you explain the statistical methods?

Statistical methods often involve techniques like Z-scores, IQR (Interquartile Range), and Grubbs' test. These methods identify outliers based on statistical properties of the data.

What about machine learning methods?

Machine learning methods include algorithms like Isolation Forest, One-Class SVM, and Autoencoders. They learn patterns from the data to identify outliers.

Which method is the most effective?

The effectiveness of a method depends on the data and context. For example, Isolation Forest works well with high-dimensional data, while statistical methods are simpler and effective for smaller datasets.