12. Copula-Based Outlier Detection (COPOD)

2022
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Author: Kevin Feasel
Published in: Finding Ghosts in Your Data
Publisher: Apress

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Abstract

This chapter delves into the innovative Copula-Based Outlier Detection (COPOD) method, a non-clustering technique for identifying multivariate outliers. It begins by defining copulas and their role in modeling joint probability distributions. The chapter then outlines the three-stage process of COPOD for detecting outliers using empirical cumulative distribution functions and empirical copulas. Practical implementation details are provided, including code snippets for integrating COPOD into existing outlier detection algorithms. The chapter also discusses updates to tests and the website to accommodate the new technique, showcasing the benefits of incorporating COPOD into an ensemble of outlier detection methods. Finally, it concludes with a reflection on the stability and potential improvements of the current multivariate outlier detection system.

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Metadata

Title: Copula-Based Outlier Detection (COPOD)
Author: Kevin Feasel
Publisher: Apress
Book: Finding Ghosts in Your Data
Print ISBN: 978-1-4842-8869-6

Electronic ISBN: 978-1-4842-8870-2

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-1-4842-8870-2_12