Intelligent Systems Reference Library

Machine Learning Paradigms

Artificial Immune Systems and their Applications in Software Personalization

Authors: Sotiropoulos, Dionysios, Tsihrintzis, George A.

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  • Presents recent machine-learning methodologies based on artificial immune systems
  • Provides experimental justification about the validity of artificial immune systems as an alternative machine learning paradigm
  • Includes an extensive review of the state of the art of machine learning
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eBook $139.00
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  • ISBN 978-3-319-47194-5
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Hardcover $179.99
price for USA in USD
  • ISBN 978-3-319-47192-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.99
price for USA in USD
  • ISBN 978-3-319-83675-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems  of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process.  The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems.

The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

Table of contents (9 chapters)

  • Introduction

    Sotiropoulos, Dionisios N. (et al.)

    Pages 3-8

  • Machine Learning

    Sotiropoulos, Dionisios N. (et al.)

    Pages 9-50

  • The Class Imbalance Problem

    Sotiropoulos, Dionisios N. (et al.)

    Pages 51-78

  • Addressing the Class Imbalance Problem

    Sotiropoulos, Dionisios N. (et al.)

    Pages 79-106

  • Machine Learning Paradigms

    Sotiropoulos, Dionisios N. (et al.)

    Pages 107-129

Buy this book

eBook $139.00
price for USA in USD (gross)
  • ISBN 978-3-319-47194-5
  • 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 in USD
  • ISBN 978-3-319-47192-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.99
price for USA in USD
  • ISBN 978-3-319-83675-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning Paradigms
Book Subtitle
Artificial Immune Systems and their Applications in Software Personalization
Authors
Series Title
Intelligent Systems Reference Library
Series Volume
118
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-47194-5
DOI
10.1007/978-3-319-47194-5
Hardcover ISBN
978-3-319-47192-1
Softcover ISBN
978-3-319-83675-1
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XVI, 327
Number of Illustrations
53 b/w illustrations, 18 illustrations in colour
Topics