Overview
- 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
Part of the book series: Smart Innovation, Systems and Technologies (SIST, volume 13)
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Table of contents (18 chapters)
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PART A FOUNDATIONS
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PART B APPLICATIONS
Keywords
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. Â
Editors and Affiliations
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
DOI: https://doi.org/10.1007/978-3-642-28699-5
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-28698-8Published: 31 July 2012
Softcover ISBN: 978-3-642-43574-4Published: 09 August 2014
eBook ISBN: 978-3-642-28699-5Published: 31 July 2012
Series ISSN: 2190-3018
Series E-ISSN: 2190-3026
Edition Number: 1
Number of Pages: XXII, 498
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