2003 | OriginalPaper | Buchkapitel
When Is Small Beautiful?
verfasst von : Amiran Ambroladze, John Shawe-Taylor
Erschienen in: Learning Theory and Kernel Machines
Verlag: Springer Berlin Heidelberg
Enthalten 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.