Studies in Computational Intelligence

Feature Selection for Data and Pattern Recognition

Editors: Stańczyk, Urszula, Jain, Lakhmi C. (Eds.)

  • Recent research trends in feature selection for data and pattern recognition
  • Points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies
  • Presents approaches in feature selection for data and pattern classification using computational intelligence paradigms
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eBook $119.00
price for USA (gross)
  • ISBN 978-3-662-45620-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA
  • ISBN 978-3-662-45619-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: November 11, 2016
  • ISBN 978-3-662-50845-9
  • Free shipping for individuals worldwide
About this book

This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition.

Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks.

This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.

Reviews

“The content of the book is outstanding from the point of view of the novelty of the exposed methods, the clarity of the discourse, and the variety of the illustrative examples. … The book is aimed at researchers and practitioners in the domains of machine learning, computer science, data mining, statistical pattern recognition, and bioinformatics.” (L. State, Computing Reviews, June, 2015)


Table of contents (14 chapters)

  • Feature Selection for Data and Pattern Recognition: An Introduction

    Stańczyk, Urszula (et al.)

    Pages 1-7

  • All Relevant Feature Selection Methods and Applications

    Rudnicki, Witold R. (et al.)

    Pages 11-28

  • Feature Evaluation by Filter, Wrapper, and Embedded Approaches

    Stańczyk, Urszula

    Pages 29-44

  • A Geometric Approach to Feature Ranking Based Upon Results of Effective Decision Boundary Feature Matrix

    Diamantini, Claudia (et al.)

    Pages 45-69

  • Weighting of Features by Sequential Selection

    Stańczyk, Urszula

    Pages 71-90

Buy this book

eBook $119.00
price for USA (gross)
  • ISBN 978-3-662-45620-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA
  • ISBN 978-3-662-45619-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: November 11, 2016
  • ISBN 978-3-662-50845-9
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Feature Selection for Data and Pattern Recognition
Editors
  • Urszula Stańczyk
  • Lakhmi C. Jain
Series Title
Studies in Computational Intelligence
Series Volume
584
Copyright
2015
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-662-45620-0
DOI
10.1007/978-3-662-45620-0
Hardcover ISBN
978-3-662-45619-4
Softcover ISBN
978-3-662-50845-9
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XVIII, 355
Number of Illustrations and Tables
54 b/w illustrations, 20 illustrations in colour
Topics