Pair Attribute Learning: Network Construction Using Pair Features

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Permanent URL	http://hdl.lib.byu.edu/1877/2434
Title	Pair Attribute Learning: Network Construction Using Pair Features
BYU Creator	Martinez, Tony R.
Creator	Henderson, Eric K.
Keywords	pair attribute; learning algorithm
Description/Abstract	We present the Pair Attribute Learning (PAL) algorithm for the selection of relevant inputs and network topology. Correlations on training instance pairs are used to drive network construction of a single-hidden layer MLP. Results on nine learning problems demonstrate 70% less complexity, on average, without a significant loss of accuracy.
Source	Henderson, E., and Martinez, T. R., "Pair Attribute Learning: Network Construction Using Pair Features", Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN'02, pp. 2556-2561, 2002.;
Publisher	IEEE
Date Original	2002
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) 2002 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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Pair Attribute Learning: Network Construction Using Pair Features

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