Technical requirements

The material in this chapter relies on using Elasticsearch version 7.9 or above. The figures in this chapter have been generated using Elasticsearch 7.10. Code snippets and code examples used in this chapter are under the chapter10 folder in the book's GitHub repository: https://github.com/PacktPublishing/Machine-Learning-with-Elastic-Stack-Second-Edition.

Discovering how outlier detection works

Outlier detection can offer insights into datasets by discovering which points are different or unusual, but how does outlier detection in the Elastic Stack work? To understand how outlier detection functionality can be constructed, let's start by thinking conceptually about how you would design the algorithm, and then see how our conceptual ideas can be formalized into the four separate algorithms that make up the outlier detection ensemble in Elasticsearch.

Suppose for a second that we have a two-dimensional set of weight and circumference measurements...