Outlier Detection: Techniques and Applications A Data Mining Perspective /

• Main Authors: Ranga Suri, N. N. R. (Author, http://id.loc.gov/vocabulary/relators/aut), Murty M, Narasimha (http://id.loc.gov/vocabulary/relators/aut), Athithan, G. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Intelligent Systems Reference Library, 155
• Subjects: Computational intelligence.; Data mining.; Sociophysics.; Econophysics.; Computational Intelligence.; Data Mining and Knowledge Discovery.; Data-driven Science, Modeling and Theory Building.

This book, drawing on recent literature, highlights several methodologies for the detection of outliers and explains how to apply them to solve several interesting real-life problems. The detection of objects that deviate from the norm in a data set is an essential task in data mining due to its sig...

Table of Contents:

• Introduction
• Outlier Detection
• Research Issues in Outlier Detection
• Computational Preliminaries
• Outlier Detection in Categorical Data
• Outliers in High Dimensional Data.