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Tutorial: Learning Topics in Game-Theoretic Decision Making Read chapter Read first chapter

2003 | OriginalPaper | Chapter

When Is Small Beautiful?

Authors : Amiran Ambroladze, John Shawe-Taylor

Published in: Learning Theory and Kernel Machines

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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The basic bound on the generalisation error of a PAC learner makes the assumption that a consistent hypothesis exists. This makes it appropriate to apply the method only in the case where we have a guarantee that a consistent hypothesis can be found, something that is rarely possible in real applications. The same problem arises if we decide not to use a hypothesis unless its error is below a prespecified number.

Metadata
Title
When Is Small Beautiful?
Authors
Amiran Ambroladze
John Shawe-Taylor
Copyright Year
2003
Publisher
Springer Berlin Heidelberg
Book
Learning Theory and Kernel Machines

Print ISBN: 978-3-540-40720-1

Electronic ISBN: 978-3-540-45167-9

Copyright Year: 2003

DOI
https://doi.org/10.1007/978-3-540-45167-9_53

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