Hybrid Classifiers Methods of Data, Knowledge, and Classifier Combin
This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing
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Michał Woźniak
Hybrid Classifiers Methods of Data, Knowledge, and Classifier Combination
Studies in Computational Intelligence Volume 519
Series Editor Janusz Kacprzyk, Warsaw, Poland
For further volumes: http://www.springer.com/series/7092
Michał Wo´zniak
Hybrid Classifiers Methods of Data, Knowledge, and Classifier Combination
ABC
Michał Wo´zniak Department of Systems and Computer Networks Faculty of Electronics Wroclaw University of Technology Wroclaw Poland
ISSN 1860-949X ISBN 978-3-642-40996-7 DOI 10.1007/978-3-642-40997-4
ISSN 1860-9503 (electronic) ISBN 978-3-642-40997-4 (eBook)
Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2013948237 c Springer-Verlag Berlin Heidelberg 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.
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To my wife Alina
Preface
Man always desire to discover nature’s rules and apply them to automatize decision making. At present, there are lots of research works aim to develop highly efficient and accurate recognition algorithms, such as neural networks, statistical and symbolic learning, fuzzy methods and so on. Meanwhile, such methods are implemented in the form of computer software and applied in many practical areas, including character and speech recognition [296], machine vision [
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