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Twin Support Vector Machines

Models, Extensions and Applications

  • Book
  • © 2017

Overview

Authors:
  1. Jayadeva

    1. Department of Electrical Engineering, Indian Institute of Technology (I.I.T), New Delhi, India

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  2. Reshma Khemchandani

    1. Department of Computer Science, Faculty of Mathematics and Computer Science, South Asian University (SAU), New Delhi, India

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  3. Suresh Chandra

    1. Department of Mathematics, Indian Institute of Technology (I.I.T), New Delhi, India

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  • Presents models, extensions, and applications of twin support vector machines (TWSVM)
  • Offers a systematic and focused study of the various aspects of TWSVM and related developments for classification and regression
  • Discusses most of the basic models of TWVSM as well as important and challenging applications of the tools
  • Includes a chapter on "Additional Topics" to discuss kernel optimization and support tensor machine topics
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 659)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 1-24

  3. Generalized Eigenvalue Proximal Support Vector Machines

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 25-42

  4. Twin Support Vector Machines (TWSVM) for Classification

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 43-62

  5. TWSVR: Twin Support Vector Machine Based Regression

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 63-101

  6. Variants of Twin Support Vector Machines: Some More Formulations

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 103-123

  7. TWSVM for Unsupervised and Semi-supervised Learning

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 125-152

  8. Some Additional Topics

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 153-192

  9. Applications Based on TWSVM

    • Jayadeva, Reshma Khemchandani, Suresh Chandra
    Pages 193-206

  10. Back Matter

    Pages 207-211
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Keywords

About this book

This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.

Authors and Affiliations

  • Department of Electrical Engineering, Indian Institute of Technology (I.I.T), New Delhi, India

    Jayadeva

  • Department of Computer Science, Faculty of Mathematics and Computer Science, South Asian University (SAU), New Delhi, India

    Reshma Khemchandani

  • Department of Mathematics, Indian Institute of Technology (I.I.T), New Delhi, India

    Suresh Chandra

Bibliographic Information

  • Book Title: Twin Support Vector Machines

  • Book Subtitle: Models, Extensions and Applications

  • Authors: Jayadeva, Reshma Khemchandani, Suresh Chandra

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-46186-1

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2017

  • Hardcover ISBN: 978-3-319-46184-7Published: 24 October 2016

  • Softcover ISBN: 978-3-319-83462-7Published: 05 July 2018

  • eBook ISBN: 978-3-319-46186-1Published: 12 October 2016

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XIV, 211

  • Number of Illustrations: 1 b/w illustrations, 20 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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