文档介绍：Learning Kernel Classifiers
putation and Machine Learning
Thomas G. Dietterich, Editor
Christopher Bishop, David Heckerman, Michael Jordan, and Michael Kearns, Associate Editors
Bioinformatics: The Machine Learning Approach, Pierre Baldi and Søren Brunak
Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
Graphical Models for Machine Learning and munication, Brendan
J. Frey
Learning in Graphical Models, Michael I. Jordan
Causation, Prediction, and Search, second edition, Peter Spirtes, Clark Glymour,
and Richard Scheines
Principles of Data Mining, David Hand, Heikki Mannilla, and Padhraic Smyth
Bioinformatics: The Machine Learning Approach, second edition, Pierre Baldi and
Søren Brunak
Learning Kernel Classifiers: Theory and Algorithms, Ralf Herbrich
Learning with Kernels: Support Vector Machines, Regularization, Optimization,
and Beyond, Bernhard Schölkopf and Alexander J. Smola
Learning Kernel Classifiers
Theory and Algorithms
Ralf Herbrich
The MIT Press
Cambridge, Massachusetts
London, England
≡c 2002 Massachusetts Institute of Technology
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means
(including photocopying, recording, or information storage and retrieval) without permission in writing from the
publisher.
This book was set in Times Roman by the author using the LATEX document preparation system and was printed
and bound in the United States of America.
Library of Congress Cataloging-in-Publication Data
Herbrich, Ralf.
Learning kernel classifiers : theory and algorithms / Ralf Herbrich.
p. cm. —(putation and machine learning)
Includes bibliographical references and index.
ISBN 0-262-08306-X (hc. : alk. paper)
1. Machine learning. 2. Algorithms. I. Title. II. Series.
.H48 2001
2
1—dc21
2001044445
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