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Outlier Analysis

Authors: Aggarwal, Charu C.

  • Provides all the fundamental algorithms for outlier analysis in great detail including those for advanced data types, including specific insights into when and why particular algorithms work effectively
  • Discusses the latest ideas in the field such as outlier ensembles, matrix factorization, kernel methods, and neural networks
  • Covers theoretical and practical aspects of outlier analysis including specific practical details for accurate implementation
  • Offers numerous illustrations and exercises for classroom teaching, including a solution manual
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eBook $59.99
price for USA
  • ISBN 978-3-319-47578-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
price for USA
  • ISBN 978-3-319-47577-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories:

  • Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods.
  • Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data.
  • Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner.
  • The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching. 

About the authors

Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his undergraduate degree in Computer Science from the Indian Institute of Technology at Kanpur in 1993 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 1996. He has published more than 300 papers in refereed conferences and journals, and has applied for or been granted more than 80 patents. He is author or editor of 15 books, including textbooks on data mining, recommender systems, and outlier analysis. Because of the commercial value of his patents, he has thrice been designated a Master Inventor at IBM. He has received several internal and external awards, including the EDBT Test-of-Time Award (2014) and the IEEE ICDM Research Contributions Award (2015). He has also served as program or general chair of many major conferences in data mining. He is a fellow of the SIAM, ACM, and the IEEE, for “contributions to knowledge discovery and data mining algorithms.”

Table of contents (13 chapters)

  • An Introduction to Outlier Analysis

    Aggarwal, Charu C.

    Pages 1-34

  • Probabilistic and Statistical Models for Outlier Detection

    Aggarwal, Charu C.

    Pages 35-64

  • Linear Models for Outlier Detection

    Aggarwal, Charu C.

    Pages 65-110

  • Proximity-Based Outlier Detection

    Aggarwal, Charu C.

    Pages 111-147

  • High-Dimensional Outlier Detection: The Subspace Method

    Aggarwal, Charu C.

    Pages 149-184

Buy this book

eBook $59.99
price for USA
  • ISBN 978-3-319-47578-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
price for USA
  • ISBN 978-3-319-47577-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Outlier Analysis
Authors
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-47578-3
DOI
10.1007/978-3-319-47578-3
Hardcover ISBN
978-3-319-47577-6
Edition Number
2
Number of Pages
XXII, 466
Number of Illustrations and Tables
65 b/w illustrations, 13 illustrations in colour
Topics