Meta-Learning in Decision Tree Induction
The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree indu
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Krzysztof Grąbczewski
Meta-Learning in Decision Tree Induction
498
Studies in Computational Intelligence Volume 498
Series Editor J. Kacprzyk, Warsaw, Poland
For further volumes: http://www.springer.com/series/7092
Krzysztof Gra˛bczewski
Meta-Learning in Decision Tree Induction
123
Krzysztof Gra˛bczewski Department of Informatics, Faculty of Physics, Astronomy and Informatics Nicolaus Copernicus University Torun´ Poland
ISSN 1860-949X ISBN 978-3-319-00959-9 DOI 10.1007/978-3-319-00960-5
ISSN 1860-9503 (electronic) ISBN 978-3-319-00960-5 (eBook)
Springer Cham Heidelberg New York Dordrecht London Library of Congress Control Number: 2013940294 Ó Springer International Publishing Switzerland 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. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
To my Family. In other words, to Love, the genuine Love Love is patient, love is kind. It is not jealous, (love) is not pompous, it is not inflated, it is not rude, it does not seek its own interests, it is not quick-tempered, it does not brood over injury, it does not rejoice over wrongdoing but rejoices with the truth. 1 Cor 13,4–6 God is love, and whoever remains in love remains in God and God in him. 1 J 4,16b
Foreword
The number of different machine learning methods has grown over the past years and so the
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