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Bias and the Probability of Generalization

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Permanent URL	http://hdl.lib.byu.edu/1877/2415
Title	Bias and the Probability of Generalization
BYU Creator	Martinez, Tony R. Wilson, D. Randall
Keywords	learning algorithm; generalization; bias
Description/Abstract	In order to be useful, a learning algorithm must be able to generalize well when faced with inputs not previously presented to the system. A bias is necessary for any generalization, and as shown by several researchers in recent years, no bias can lead to strictly better generalization than any other when summed over all possible functions or applications. This paper provides examples to illustrate this fact, but also explains how a bias or learning algorithm can be “better” than another in practice when the probability of the occurrence of functions is taken into account. It shows how domain knowledge and an understanding of the conditions under which each learning algorithm performs well can be used to increase the probability of accurate generalization, and identifies several of the conditions that should be considered when attempting to select an appropriate bias for a particular problem.
Source	Wilson, D. R. and Martinez, T. R., "Bias and the Probability of Generalization", Proceedings of the 1997 International Conference on Intelligent Information Systems, pp. 108-114, 1997.;
Publisher	IEEE
Date Original	1997
Date Digital	2010-09-09
Language	English eng en
Publication Type	Peer-Reviewed Articles Conference Proceedings
Type	Text
Format	application/pdf
Owning Institution	Brigham Young University
BYU College	College of Physical and Mathematical Sciences
BYU Department	Computer Science
Copyright Status	(c) 1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.;
Copyright Use Information	http://www.lib.byu.edu/generic_copyright.html

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