Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022

K. FeaselFinding Ghosts in Your Datahttps://doi.org/10.1007/978-1-4842-8870-2_9

9. Clustering and Anomalies

Kevin Feasel¹  

(1)

DURHAM, NC, USA

 

This first chapter of Part III also serves as a bridge between Part II, univariate analysis, and Part III, multivariate analysis. In this chapter, we will look at how we can use clustering techniques to solve the problem we ended Chapter 7 with: we can intuitively understand that in a dataset with values { 1, 2, 3, 50, 97, 98, 99 }, the value 50 is an outlier but our outlier detection engine steadfastly refuses to believe it.

This chapter will begin with a description of the concept of clustering. Then, we will look ...