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Support Vector Machines and Evolutionary Algorithms for Classification

Single or Together?

  • Catalin Stoean
  • Ruxandra Stoean

Part of the Intelligent Systems Reference Library book series (ISRL, volume 69)

Table of contents

  1. Front Matter
    Pages 1-12
  2. Catalin Stoean, Ruxandra Stoean
    Pages 1-4
  3. Support Vector Machines

    1. Front Matter
      Pages 5-6
    2. Catalin Stoean, Ruxandra Stoean
      Pages 7-25
  4. Evolutionary Algorithms

    1. Front Matter
      Pages 27-28
    2. Catalin Stoean, Ruxandra Stoean
      Pages 29-45
    3. Catalin Stoean, Ruxandra Stoean
      Pages 47-56
    4. Catalin Stoean, Ruxandra Stoean
      Pages 57-73
  5. Support Vector Machines and Evolutionary Algorithms

    1. Front Matter
      Pages 75-76
    2. Catalin Stoean, Ruxandra Stoean
      Pages 77-89
    3. Catalin Stoean, Ruxandra Stoean
      Pages 91-109
    4. Catalin Stoean, Ruxandra Stoean
      Pages 111-112
  6. Back Matter
    Pages 113-121

About this book

Introduction

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.

Keywords

Classification Evolutionary Algorithms Feature Selection Machine Learning Multimodal Optimization Rule Extraction Support Vector Machines

Authors and affiliations

  • Catalin Stoean
    • 1
  • Ruxandra Stoean
    • 2
  1. 1.Faculty of Mathematics and Natural Sci. Department of Computer ScienceUniversity of CraiovaCraiovaRomania
  2. 2.Faculty of Mathematics and Natural Sci. Department of Computer ScienceUniversity of CraiovaCraiovaRomania

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-06941-8
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-06940-1
  • Online ISBN 978-3-319-06941-8
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site
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