Smart Innovation, Systems and Technologies

Emerging Paradigms in Machine Learning

Editors: Ramanna, Sheela, Jain, Lakhmi C., Howlett, Robert J. (Eds.)

  • State of the art of emerging paradigms in machine learning including some real world applications
  • Latest research in machine learning and biologically-based techniques for the design and implementation of intelligent systems
  • Written by leading experts in the field
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eBook $159.00
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  • ISBN 978-3-642-28699-5
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Hardcover $209.00
price for USA
  • ISBN 978-3-642-28698-8
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  • Usually dispatched within 3 to 5 business days.
Softcover $209.00
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  • ISBN 978-3-642-43574-4
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About this book

This  book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The  multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.  The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems.  Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.   

Table of contents (18 chapters)

  • Emerging Paradigms in Machine Learning: An Introduction

    Ramanna, Sheela (et al.)

    Pages 1-8

  • Extensions of Dynamic Programming as a New Tool for Decision Tree Optimization

    Alkhalid, Abdulaziz (et al.)

    Pages 11-29

  • Optimised Information Abstraction in Granular Min/Max Clustering

    Bargiela, Andrzej (et al.)

    Pages 31-48

  • Mining Incomplete Data—A Rough Set Approach

    Grzymala-Busse, Jerzy W. (et al.)

    Pages 49-74

  • Roles Played by Bayesian Networks in Machine Learning: An Empirical Investigation

    Hruschka, Estevam R. (et al.)

    Pages 75-116

Buy this book

eBook $159.00
price for USA (gross)
  • ISBN 978-3-642-28699-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $209.00
price for USA
  • ISBN 978-3-642-28698-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $209.00
price for USA
  • ISBN 978-3-642-43574-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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
Emerging Paradigms in Machine Learning
Editors
  • Sheela Ramanna
  • Lakhmi C. Jain
  • Robert J. Howlett
Series Title
Smart Innovation, Systems and Technologies
Series Volume
13
Copyright
2013
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-28699-5
DOI
10.1007/978-3-642-28699-5
Hardcover ISBN
978-3-642-28698-8
Softcover ISBN
978-3-642-43574-4
Series ISSN
2190-3018
Edition Number
1
Number of Pages
XXII, 498
Topics