文档介绍：Information Theory and Statistical Learning
Frank Emmert-Streib • Matthias Dehmer
Information Theory
and Statistical Learning
ABC
Frank Emmert-Streib Matthias Dehmer
University of Washington Vienna University of Technology
Department of Biostatistics Institute of Discrete Mathematics
and Department of Genome Sciences and Geometry
1705 NE Pacific St., Wiedner Hauptstr. 8–10
Box 357730 1040 Vienna, Austria
Seattle WA 98195, USA and
and University of Coimbra
Queen’s University Belfast Center for Mathematics
Computational Biology Probability and Statistics
and Machine Learning Apartado 3008, 3001–454
Center for Cancer Research Coimbra, Portugal
and Cell Biology matthias@
School of Biomedical Sciences
97 Lisburn Road, Belfast BT9 7BL, UK
v@
ISBN: 978-0-387-84815-0 e-ISBN: 978-0-387-84816-7
DOI: -0-387-84816-7
Library of Congress Control Number: 2008932107
c Springer Science+Business Media, LLC 2009
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Printed on acid-free paper
Preface
This book presents theoretical and practical results of information theoretic methods
used in the context of statistical learning. Its major goal is to advocate and promote
the importance and usefulness of information theoretic concepts for understanding
and developing the sophi