SpringerBriefs in Optimization

Robust Data Mining

Authors: Xanthopoulos, Petros, Pardalos, Panos M., Trafalis, Theodore B.

  • Summarizes the latest applications of robust optimization in data mining
  • An essential accompaniment for theoreticians and data miners
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eBook $34.99
price for USA (gross)
  • ISBN 978-1-4419-9878-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $49.95
price for USA
  • ISBN 978-1-4419-9877-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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  • Rental duration: 1 or 6 month
  • low-cost access
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About this book

Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.

This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents  the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems.

This brief will appeal to theoreticians and data miners working in this field.

Reviews

From the reviews:

“The goal of the book is to provide a guide for junior researchers interested in pursuing theoretical research in data mining and robust optimization and has been developed so that each chapter can be studied independent of the others.” (Hans Benker, Zentralblatt MATH, Vol. 1260, 2013)

Table of contents (6 chapters)

  • Introduction

    Xanthopoulos, Petros (et al.)

    Pages 1-7

  • Least Squares Problems

    Xanthopoulos, Petros (et al.)

    Pages 9-20

  • Principal Component Analysis

    Xanthopoulos, Petros (et al.)

    Pages 21-26

  • Linear Discriminant Analysis

    Xanthopoulos, Petros (et al.)

    Pages 27-33

  • Support Vector Machines

    Xanthopoulos, Petros (et al.)

    Pages 35-48

Buy this book

eBook $34.99
price for USA (gross)
  • ISBN 978-1-4419-9878-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $49.95
price for USA
  • ISBN 978-1-4419-9877-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Robust Data Mining
Authors
Series Title
SpringerBriefs in Optimization
Copyright
2013
Publisher
Springer-Verlag New York
Copyright Holder
Petros Xanthopoulos,Panos M. Pardalos,Theodore B. Trafalis
eBook ISBN
978-1-4419-9878-1
DOI
10.1007/978-1-4419-9878-1
Softcover ISBN
978-1-4419-9877-4
Series ISSN
2190-8354
Edition Number
1
Number of Pages
XII, 59
Number of Illustrations and Tables
6 b/w illustrations
Topics