Intelligent Systems Reference Library

Support Vector Machines and Evolutionary Algorithms for Classification

Single or Together?

Authors: Stoean, Catalin, Stoean, Ruxandra

  • Guides the reader from single methodologies, like support vector machines and evolutionary algorithms, to hybridization at different levels between the two, showing the benefits and drawbacks of each
  • Contains new approaches to classification personally developed and tested by the authors based on evolutionary algorithms and support vector machines
  • Fills the gaps between theoretical classification and the practical issues revolving around computer aided diagnosis
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eBook $99.00
price for USA (gross)
  • ISBN 978-3-319-06941-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-3-319-06940-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
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 4, 2016
  • ISBN 978-3-319-38243-2
  • Free shipping for individuals worldwide
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
About this book

When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame. Yet, their black box means to do so make the practical users quite circumspect about relying on it, without much understanding of the how and why of its predictions. The question raised in this book is how can this ‘masked hero’ be made more comprehensible and friendly to the public: provide a surrogate model for its hidden optimization engine, replace the method completely or appoint a more friendly approach to tag along and offer the much desired explanations? Evolutionary algorithms can do all these and this book presents such possibilities of achieving high accuracy, comprehensibility, reasonable runtime as well as unconstrained performance.

Reviews

From the book reviews:

“This book is intended for scholars, students, and developers who are interested and engaged in machine learning approaches and, particularly, in classification approaches via support vector machines (SVMs). … the book is recommended to those with advanced knowledge in machine learning and, in particular, SVMs as a hypothesis modeling classification approach. … the presentation of each topic remains systematic and the authors make good use of examples throughout the book.” (Epaminondas Kapetanios, Computing Reviews, November, 2014)

Table of contents (8 chapters)

  • Introduction

    Stoean, Catalin (et al.)

    Pages 1-4

  • Support Vector Learning and Optimization

    Stoean, Catalin (et al.)

    Pages 7-25

  • Overview of Evolutionary Algorithms

    Stoean, Catalin (et al.)

    Pages 29-45

  • Genetic Chromodynamics

    Stoean, Catalin (et al.)

    Pages 47-56

  • Cooperative Coevolution

    Stoean, Catalin (et al.)

    Pages 57-73

Buy this book

eBook $99.00
price for USA (gross)
  • ISBN 978-3-319-06941-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-3-319-06940-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
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 4, 2016
  • ISBN 978-3-319-38243-2
  • Free shipping for individuals worldwide
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
Support Vector Machines and Evolutionary Algorithms for Classification
Book Subtitle
Single or Together?
Authors
Series Title
Intelligent Systems Reference Library
Series Volume
69
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-06941-8
DOI
10.1007/978-3-319-06941-8
Hardcover ISBN
978-3-319-06940-1
Softcover ISBN
978-3-319-38243-2
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XVI, 122
Number of Illustrations and Tables
31 b/w illustrations
Topics